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aurora

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Improving SPIRE security and resiliency with AWS managed services
In cloud-centered environments, establishing trust between workloads is fundamental to securing machine-to-machine communication. Traditional approaches such as API keys, shared secrets, and static service account credentials weren’t designed for the scale and ephemeral nature of cloud workloads. This drives an organizational need to shift from long-term, static credentials to short-lived cryptographic workload identities. Organizations are turning to SPIFFE (Secure Production Identity Framework for Everyone) as a core component of their workload identity strategy. SPIFFE is a set of open source standards for securely identifying software systems in dynamic and heterogeneous environments. Using SPIFFE can help address what’s known as the bottom turtle problem: the circular dependency where protecting one credential requires yet another credential. SPIRE (the SPIFFE Runtime Environment) is an open source implementation of SPIFFE. Customers can use it to quickly experiment with the framework. However, there are operational and security considerations when deploying SPIRE in production, such as: Where cryptographic signing keys for workload identities are managed How to ensure availability and resiliency of the workload identity registry How the SPIRE Certificate Authority integrates into the existing enterprise PKI How workloads without direct connectivity to the SPIRE server validate identities How workload identities are delivered to serverless environments How fine-grained authorization based on SPIFFE IDs is enforced In this post, we show you how to address each of these considerations by offloading SPIRE core functionality to AWS managed services. This post is accompanied by a Github Repository that guides you through the deployment of the reference architecture. To learn the core concepts the SPIFFE framework, take a moment to familiarize yourself with the SPIFFE documentation . SPIRE background A SPIRE deployment is comprised of at least one SPIRE Server, at least one SPIRE Agent, and at least one workload. Figure 1: SPIRE high-level architecture The SPIRE Server is deployed on a central control plane instance (or instances) and manages identity issuance and stores workload identity registrations. The SPIRE server handles five key functions: RegistrationAPI : Create, update, and delete registration entries that define which workloads are entitled to specific SPIFFE IDs based on selectors (for example, Kubernetes namespace, Unix UID). DataStore : The SPIRE server uses a data store to keep track of the workload identity registration entries and the status of the SVIDs it has issued. KeyManager : Controls how the server manages private keys used to sign X.509-SVIDs and JWT-SVIDs. BundlePublisher : Publishes the local trust bundle to a store. The trust bundle is an object containing a trust domain’s cryptographic keys UpstreamAuthority : Dictates which root certificate authority is used to sign the SPIRE certificate authority (CA) certificate The SPIRE Agent is distributed across your workloads, whether they run on Amazon Elastic Compute Cloud (Amazon EC2) instances, Amazon Elastic Container Service (Amazon ECS) containers, or Amazon Elastic Kubernetes Service (Amazon EKS) Pods. The SPIRE Agent handles: WorkloadAPI : Exposes the workload API to workloads, which enable workloads to retrieve their SVIDs and trust bundles from the SPIRE server. NodeAttestation : SPIRE requires that each agent attest and verify itself. WorkloadAttestation : The SPIRE agent collects workload metadata to determine its identity. SVIDStore : The SPIRE Agent also stores SVIDs in other destinations, such as AWS Secrets Manager or HashiCorp Vault making them available for workloads running in serverless environments. After the server and agent are deployed, applications retrieve short-lived SPIFFE Verifiable Identity Documents ( X.509 Certificates or JSON Web Tokens (JWTs) ) using the workload API. How to use AWS managed services for core SPIRE functions In the following sections, we dive deeper into what each of these SPIRE functions does and the advantages of using each AWS service for the function. Figure 2: SPIFFE architecture using AWS managed services To deploy the infrastructure required to follow along with this post, follow the deployment process in the Github Repository . Note : For each managed service, there’s a parameter in the source AWS CloudFormation templates that you can use to specify whether to provision the resource. For example, if you already have an AWS Private Certificate Authority (AWS Private CA) certificate authority deployed in your environment, you can use that for your SPIRE implementation and avoid provisioning a new certificate authority. SPIRE Key Manager using AWS KMS The SPIRE Key Manager controls the cryptographic keys that are used to sign SPIFFE Verifiable Identity Documents (SVIDs), which are either X.509 certificates or JWTs. By using SPIRE, you can configure the cryptographic keys to be either stored in memory or on disk, or to use a plugin where external keys are used for signing SVIDs. By using the AWS KMS plugin for SPIRE , you bring the security benefits of AWS KMS to your SPIRE implementation. HSMs : AWS KMS uses hardware security modules (HSMs) that have been validated under FIPS 140-3 Level 2 Key protection : Your plaintext AWS KMS keys don’t leave the HSMs, aren’t written to disk, and are only used in the volatile memory of the HSMs for the time needed to perform your requested cryptographic operation Comprehensive auditing : Each request to use the keys for signing must be authenticated using Signature Version 4 (SigV4) and is audited and logged in AWS CloudTrail Fine-grained access control: Use AWS KMS Key Policies to restrict access to your signing keys This configuration block indicates to SPIRE that AWS KMS keys are used to sign our SVIDs: KeyManager "aws_kms" { plugin_data { region = "<your-region>" key_identifier_file = "./key_metadata" } } This code block exists in the SPIRE server configuration deployed in the Github repository. SPIRE datastore using Amazon Aurora The SPIRE server uses a data store to keep track of the workload identity registration entries as well as the status of the SVIDs it has issued. By default, the datastore lives as an SQLite database in memory. However, you can configure the SPIRE server to use Amazon Aurora . By doing this, you can decouple the database from the server and offload the operational overhead of managing the datastore to AWS. Benefits: High availability : Automatic failover and multi-Availability Zone deployments Automated backups : Point-in-time recovery and automated backup retention Scalability : Scale compute and storage independently Security : Encryption at rest and in transit, with AWS Identity and Access Management (IAM) Monitoring : Built-in performance insights and enhanced monitoring Reduced operational burden : Automated patching, maintenance, and updates To do this, the CloudFormation stack provisions: An Aurora PostgreSQL Cluster A database user with the capability to authenticate through AWS IAM Network connectivity between your SPIRE Server and the database After the sample finishes deployment, the configuration in the SPIRE server is changed from the default: DataStore "sql" { plugin_data { database_type = "sqlite3" connection_string = "/opt/spire/data/server/datastore.sqlite3" } } To: DataStore "sql" { plugin_data { database_type "aws_postgres" { region = "<region>" } connection_string = "dbname=<dbname> user=spiffe host=<your_db_endpoint> port=<your_port>" } } For more information, see Datastore SQL Plugin . SPIRE certificate authority using AWS Private Certificate Authority The SPIRE Server issues SVIDs to SPIRE agents and workloads. Given that these SVIDs are X.509 certificates, the SPIRE server needs to act as a certificate authority. In the default configuration of SPIRE, the server generates a self-signed certificate that it will use as the root CA certificate. In production scenarios, organizations often use their existing AWS Private CA certificate authority hierarchy. Using the AWS Private CA plugin for SPIRE, you configure the SPIRE CA to act as an issuing certificate authority that chains to your existing root CA. This delivers three benefits for your SPIRE implementation: HSM-backed root of trust : The root of trust of your CA hierarchy is backed by fully managed, FIPS 140-2 Level 3 validated hardware security modules Non-exportable private keys : The private keys for the root CA can’t be exported Fully Managed Certificate Revocation Lists and OCSP endpoint : In case the issuing CA certificate needs to be revoked Note : If the SPIRE CA certificate will be signed by an issuing CA, you need to ensure that the path length of that CA is at least 1. The sample code provisions a root CA, so this isn’t an issue if you’re following the sample code. After the sample deployment is complete, the configuration of the SPIRE server configuration includes the UpstreamAuthority plugin to use your AWS Private CA certificate authority as the root of trust. UpstreamAuthority "aws_pca" { plugin_data { region = "<aws_region>" certificate_authority_arn = "<your_pca_arn>" ca_signing_template_arn = "arn:aws:acm-pca:::template/SubordinateCACertificate_PathLen0/V1" } } For more information, see the AWS Private CA upstream authority plugin documentation . SPIRE bundle publisher using Amazon S3 In SPIFFE, trust bundles are sets of public keys that are used by destination workloads to verify the identity of source workloads. These bundles contain the root certificates and public keys used to sign JWT SVIDs. The SPIRE Server supports exposing an endpoint containing this trust bundle or publishing the bundle to Amazon Simple Storage Service (Amazon S3) . By publishing the bundle to Amazon S3, you can: Decouple : Decouple bundle access from the SPIRE server availability Continuous validation : Allow destination workloads to continually validate source workload identities without requiring network access to the SPIRE server Global distribution : Distribute the trust bundle using Amazon CloudFront , improving performance through the CloudFront global edge network with over 750 Points of Presence Reduced load : Offload trust bundle retrieval traffic from the SPIRE server Version control : Maintain historical versions of trust bundles with S3 versioning The following is a sample configuration for this plugin: BundlePublisher "aws_s3" { plugin_data { region = "<your_bucket_region>" bucket = "<your_bucket_name>" object_key = "<your_bundle_name" format = "spiffe" } } For more information, see S3 Bundle Publisher Plugin Reference . SPIRE Agent SVID store using Secrets Manager In a typical SPIRE implementation, SVIDs are retrieved from the workload API using the SPIRE agent by workloads. In serverless or container cases, it isn’t feasible or possible to run the SPIRE agent, especially in workloads running on AWS Lambda or an AI agent running in Amazon Bedrock AgentCore Runtime . In these scenarios, use the SVID store plugin to push the SVID to Secrets Manager . In this scenario, you still need a SPIRE agent running on a node that performs node attestation with the SPIRE server and delivers the SVID to a secrets store. One of the available secrets store plugins is the AWS Secrets Manager SVIDStore Plugin . Benefits: Encryption at rest : Secrets are encrypted by default using AWS managed or customer-managed AWS KMS keys Broad integration : Integrations with multiple compute types, including AWS Secrets Manager Lambda Extension , Amazon ECS , Amazon EMR , and 52 other AWS services Client-side caching : Secrets Manager provides client-side caching libraries to improve performance and reduce API calls Multi-region replication : Built-in multi-Region replication functionality for workloads with multi-region requirements Fine-grained access control : Use resource policies to control which workloads access which SVIDs Audit trail : All secret access is logged in CloudTrail This plugin is configured in the agent , as opposed to the SPIRE server. A reference for the specific permissions required are in the plugin Github repository . In the sample code, see the configuration in the following agent.conf file: SVIDStore "aws_secretsmanager" { plugin_data { region = "<your_region>" } } When you need to specify a given workload’s SVID to be pushed to Secrets Manager, you add the storeSVID and selector parameters when you create the entry in the workload registry. If you’re managing your SPIRE server in Kubernetes, the appropriate command looks like: kubectl exec -n spire spire-server-<postfix>-- \ /opt/spire/bin/spire-server entry create \ -spiffeID spiffe://example.org/<workload_name> \ -parentID spiffe://example.org/ns/spire/sa/spire-agent \ -selector aws_secretsmanager:secretname:<workload_name> \ -storeSVID Fine-grained access control using Verified Permissions Up to this point, all the managed services we’ve talked about have been used for creating and distributing SVIDs and trust bundles to workloads. However, a key advantage of using a framework such as SPIFFE is that it allows resource owners to protect resources with fine-grained access control. One managed service that helps you do that in the context of SPIFFE and SPIRE implementations is Amazon Verified Permissions . Verified Permissions is a scalable, fine-grained permissions management and authorization service that helps you build secure applications. You can use it to: Define declarative policies : Use Cedar policy language , which provides human-readable, declarative access control rules Centralize policy management : Separate authorization logic from application code Take advantage of the straightforward policy authoring, formal verification capabilities, and performance benefits of Cedar Make real-time decisions : Evaluate authorization requests in real-time based on multiple factors including user identity, workload identity (SPIFFE ID), resource attributes, and contextual information Integrate with identity providers : Support for OpenID Connect (OIDC) providers, enabling validation of JWT tokens including JWT-SVIDs With Verified Permissions, you authenticate SPIRE issued SVIDs using the public keys associated with your trust domain, and deploy fine-grained authorization policies protecting your resources. To use Verified Permissions, you need a policy store, an identity source , and authorization policies . The github sample creates a policy store on your behalf and sets up the necessary infrastructure to have SPIRE serve as an identity source for your policy store. You will need policies to enforce fine grained authorization. The following sample policy forbids a specific workload from taking any action: forbid( principal, action, resource ) when { context has sub && context.sub like "spiffe://example.org/forbidden-workload/*" }; Or conversely allows a specific workload to take actions: permit( principal, action, resource ) when { context has sub && context.sub like "spiffe://example.org/allowed-workload/*" }; Experiment with these policies as you build on top of your SPIRE infrastructure. Conclusion This post demonstrates how organizations enhance their SPIRE deployments on AWS by replacing default implementations with AWS managed services. We showed you integrations with AWS KMS for SVID signing, Amazon RDS Aurora for managed datastore operations, AWS Private Certificate Authority for root of trust, Amazon S3 and CloudFront for global trust bundle distribution, AWS Secrets Manager for SVID storage, and Amazon Verified Permissions for fine-grained authorization. By adopting these integrations, organizations can improve security posture, reduce operational complexity, and enhance resiliency. If you’re interested in learning SPIFFE on AWS, check out our SPIRE on AWS github sample or the SPIFFE and SPIRE on AWS Workshop for hands-on learning. If you have feedback about this post, submit comments in the Comments section below. Brendan Paul Brendan is a Security Services SA Manager at AWS and has been at AWS for more than 7 years. He spends most of his time at work helping customers solve problems in the data protection and workload identity domains. Outside of work, he’s pursuing his master’s degree in data science from UC Berkeley. Meg Peddada Meg is a Principal FSI Security Solutions architect specializing in security, risk, and compliance. Her expertise spans governance, security automations, threat management, and architecture. In her spare time, she loves playing volleyball, arts and crafts, and finding new brunch experiences.
aws.amazon.comOct 6, 2026extracted
ICYMI: August 2026 @AWS Security
Read all about the latest AWS security features, compliance updates, and hands-on resources in our monthly digest posts. You’ll find expert blog posts, new service capabilities, code samples, and workshops. AWS Security Blog posts August brought 20 AWS Security Blog posts organized across seven categories. Identity and access management led the month with five posts covering self-service rate limits for Amazon Cognito , a decade of AWS Managed Microsoft AD , a redesigned sign-in experience, console Private Access for isolated VPCs, and automated IAM Identity Center governance. Data protection followed with four posts on AWS KMS data key caching, ACME protocol support in AWS Certificate Manager , Amazon S3 over-permissioned access remediation, and the upcoming deprecation of email-based domain validation. AI security continued to grow with four posts on custom authentication in Amazon Bedrock AgentCore Gateway, user authorization propagation in AI agents, and extending Bedrock Guardrails to tool interactions. Threat detection, governance and networking. Identity From 2 weeks to 2 minutes: Amazon Cognito launches provisioned limits for self-service rate limit management Authors: Kiran Dongara, Howie Li | Published: August 5, 2026 Learn to use Amazon Cognito provisioned limits for on-demand authentication rate limit adjustments, replacing the previous 10–14 day support ticket process with self-service capacity scaling in minutes. A decade of enterprise identity in the cloud with AWS Managed Microsoft AD Authors: Vladimir Provorov, Tekena Orugbani, Rodney Underkoffler | Published: August 7, 2026 AWS Managed Microsoft AD celebrates 10 years of fully managed Active Directory in the cloud, now offering Standard, Enterprise, and Hybrid editions with multi-Region replication and 20+ AWS service integrations. Updates to your AWS sign-in experience Authors: Vaibhav Chowla, Ella Segura | Published: August 17, 2026 AWS is gradually rolling out a redesigned sign-in page with a unified email entry point, social identity provider options, and an updated session selection experience for managing multiple active sessions. Extend your data perimeter to the AWS Management Console with Private Access Authors: Madhur Kulkarni, Abhijit Barde, Sujay Ghosh, Mateusz Jaworski | Published: August 28, 2026 AWS Management Console Private Access now supports VPCs without internet connectivity, routing all console traffic – authentication, static assets, and service API calls – through AWS PrivateLink endpoints to strengthen your data perimeter. Automate IAM Identity Center governance with continuous discovery and reporting Author: Jonathan Nguyen | Published: August 31, 2026 Learn to deploy automated discovery and reporting for AWS IAM Identity Center applications and assignments across your organization, with event-driven monitoring that validates naming conventions and enables near real-time enforcement of governance policies. Data Protection Caching KMS data keys in multi-thread environments: per-tenant encryption for event-driven systems at scale Authors: Maria Gutovsky, Hemmy Yona | Published: August 6, 2026 Learn to solve the cache stampede problem in multi-tenant envelope encryption using the AWS-recommended hierarchical keyring pattern or a custom Caffeine-based caching approach to reduce AWS KMS costs. Automate certificates with ACME support in AWS Certificate Manager Authors: Anthony Harvey, Chandan Kundapur | Published: August 6, 2026 Learn to use ACME protocol support in AWS Certificate Manager to automate public certificate issuance and renewal using standard clients like Certbot and cert-manager, with enterprise controls for domain scoping and centralized visibility. Securing your Amazon S3 buckets: identifying and remediating over-permissioned access Authors: Hetal Kolekar, Fernando Chiera di Vasco Freitas, Manonmayi Vedam | Published: August 7, 2026 Learn to detect and fix over-permissioned Amazon S3 buckets across multi-account environments using AWS Lambda , AWS Config , and AWS Security Hub , with automation for continuous monitoring. AWS Certificate Manager will discontinue email validation to prove domain validation for certificates Authors: Adam Aboudi, Poojil Tripathi | Published: August 13, 2026 ACM will discontinue email-validated public certificates by September 30, 2027, aligning with CA/B Forum standards – learn the timeline and how to migrate to DNS validation in place. AI Security Implement custom authentication for tools integration using request Lambda interceptor in AgentCore Gateway Authors: Nishant Mainro, Ram Ramani | Published: August 18, 2026 Learn to use a request Lambda interceptor in Amazon Bedrock AgentCore Gateway to bridge legacy authentication mechanisms like Basic Auth, isolating credentials from AI agents using AWS Secrets Manager . Propagate user authorization context in AI agents with Amazon Bedrock AgentCore Authors: Anshu Bathla, Prafful Gupta, Rohit Verma | Published: August 19, 2026 Learn to enforce least-privilege access in AI agents by propagating user identity through Amazon Bedrock AgentCore to Amazon DynamoDB , Knowledge Bases, and Salesforce, without embedding authorization logic in agent code. Extend Amazon Bedrock Guardrails to tool interactions using the Strands Agents SDK Authors: Stephan Traub | Published: August 27, 2026 Learn to extend Amazon Bedrock Guardrails beyond the model boundary to tool calls, external data, and MCP server interactions using three validation checkpoints built with Strands Agents SDK lifecycle hooks. Threat detection and incident response Security Hub Extended adds supply chain security as its tenth category Author: Michael Fuller | Published: August 18, 2026 AWS Security Hub Extended now includes supply chain security with Chainguard and Socket as curated partners, helping you verify open source dependencies and block malicious packages through a single AWS billing relationship. Detecting multi-stage attacks on AWS: a guide to cross-service signal correlation Authors: Nisha Kashyap | Published: August 26, 2026 Learn to correlate signals across AWS CloudTrail , VPC Flow Logs, and Route 53 Resolver logs to detect multi-stage attacks by layering your business context, data classification, access norms, and change windows – on top of Amazon GuardDuty Extended Threat Detection. AWS partners with Anthropic and OpenAI to bring AWS Continuum into developer workflows Author: Chet Kapoor | Published: August 5, 2026 AWS Continuum for code vulnerabilities now integrates with Anthropic Claude Code, OpenAI Codex, and Kiro , enabling developers to discover, prioritize, validate, and remediate vulnerabilities within their coding environments. We invited a direct competitor into Security Hub Extended. Here’s why. Authors: Michael Fuller | Published: August 31, 2026 AWS Security Hub Extended now includes Upwind, a runtime-first cloud security company, offering eBPF-based workload protection with pay-as-you-go pricing through a single AWS bill, reinforcing customer choice even where capabilities overlap with AWS offerings. Infrastructure security AWS Network Firewall now supports rule hit count Authors: Preetkumar Shah, Amit Gaur, Cheriyan Mundapuzha, Santosh Shanbhag, Srivalsan Mannoor Sudhagar | Published: August 20, 2026 AWS Network Firewall now tracks how often stateful rules match traffic, helping you identify unused rules, validate security controls for compliance, and accelerate incident response at no additional cost. Governance and compliance Landing Zone Accelerator independent assessment report for C5:2020 now available on AWS Artifact Authors: Kevin Donohue, Michael Wahlers | Published: August 11, 2026 An independent assessment by Schellman evaluates how Landing Zone Accelerator on AWS aligns to C5:2020 requirements, implementing 325 security controls to accelerate your compliance journey. Fast track ISM-ready cloud environments and IRAP assessments with Landing Zone Accelerator on AWS Authors: Kevin Donohue, Dave Connell, Dan Friebe | Published: August 25, 2026 A new independent assessment by gwi.digital evaluates Landing Zone Accelerator against 1,081 ISM controls, achieving 91% coverage of addressable scope to help Australian customers accelerate IRAP assessment readiness. How Moeve scales AWS governance with automated AWS Organization Service Control Policies Authors: Gonzalo Guerrero, Jonatan De Martín, Rayco Martinez | Published: August 26, 2026 Learn how Moeve manages 150 SCPs across 300+ accounts in three AWS Organizations using a governance-as-code model; policies live in Git, deploy through GitHub Actions pipelines, and attach dynamically based on account metadata during onboarding, with Amazon EventBridge and AWS Lambda providing real-time observability of every organizational change. August Security Bulletins In August 2026, AWS published 23 security bulletins addressing vulnerabilities across open-source SDKs, MCP servers, developer tools, and the OpenSearch ecosystem. A dominant theme was the AI agent tool surface: prompt-injection consent bypasses in Strands Agents Tools enabled command and code execution, an insecure direct object reference exposed cross-tenant agent memory, and credential disclosure and authorization flaws affected the Amazon MQ , DocumentDB, and AWS Transform MCP servers and the Bedrock AgentCore harness. Remote code execution recurred throughout, from prototype pollution and Java deserialization in OpenSearch to path-traversal-to-root in amazon-ssm-agent, Zip Slip in awsdac, and an uncontrolled search path in the Kiro IDE and CLI on Windows. Other notable issues include disabled SSH host key verification in the AWS CLI, memory-safety flaws in the AWS SDK for C++, privilege escalation in the FreeRTOS-Kernel, and memory-amplification denial of service in Amazon ion-java. OpenSearch accounted for a large share of the month, spanning authorization, input validation, SSRF, stored XSS, and denial of service, while Athena Federated Query connectors exposed Secrets Manager secrets. A common thread: insufficient authorization and input validation at the boundary between AI agents and the systems they reach. All patches are available, upgrade promptly. For more information, see AWS Security Bulletins . AWS Samples In August 2026, we published 17 new code samples organized into five categories: governance and compliance (7), AI security (3), data protection and privacy (3), identity and access management (2), and infrastructure security (2). This month’s collection reflects the rapid growth of agentic AI workloads: most samples focus on governing, auditing, and securing AI agents built on Amazon Bedrock AgentCore, from platform-level governance and telemetry to fraud investigation and biosecurity screening. Governance and compliance Agentic Governance Platform Learn to deploy an AWS-native control plane for governing AI agents across your enterprise with centralized registry, Microsoft Entra ID single sign-on, Cedar tool policies, multi-vendor agent inventory, and Langfuse observability, all self-hosted on Amazon Bedrock AgentCore. Enterprise Agentic AI Platform Accelerator Learn to deploy a secure, governed foundation for production AI agents on Amazon Bedrock AgentCore with modular CDK stacks covering identity, gateway, memory, runtime, and observability; supporting Strands Agents, LangGraph, and Claude Agent SDK with opt-in security controls. Video Compliance Agent Learn to deploy an end-to-end pipeline that automatically verifies video content against broadcast compliance guidelines such as Ofcom; extracting frames, audio transcripts, and OCR text shot by shot, then using Amazon Bedrock to flag potential violations and produce a structured per-shot compliance report. Intelligent Security for Healthcare APIs Learn to add behavioral anomaly detection, automated data sensitivity classification, and HIPAA compliance reporting to your FHIR API using Amazon Bedrock; running asynchronously so clinical workflows are never blocked, with Amazon Comprehend Medical and Bedrock Guardrails anonymizing PHI throughout the monitoring path. Governed Agentic Companion Learn to deploy a governed, orchestrator-driven multi-agent builder companion on Amazon Bedrock AgentCore, reachable from Kiro, Claude Code, or any MCP client; the kit enforces 13 codified tenets through an always-on governance gate with no off switch, routing each request to a specialist while blocking deploys, secret leaks, and ungrounded answers by construction. Audit the Agent Learn to deploy a serverless daily executive audit pipeline for AWS AI agents ( AWS DevOps Agent , AWS Security Agent ) using AWS Step Functions and AWS Lambda; the report answers five questions: what the agent accessed, who authorized it, what it cost, its risk posture across five trust dimensions, and whether you should be concerned, all sourced deterministically from AWS CloudTrail, CUR, and IAM with AI-generated summaries bounded by layered guardrails. AI Security Telemetry Enablement for AgentCore CloudFormation Learn to deploy a single AWS CloudFormation stack that enables Amazon CloudWatch logs and X-Ray traces for every Amazon Bedrock AgentCore resource type – Runtime, Gateway, Memory, Browser, CodeInterpreter, and WorkloadIdentity – using native and custom telemetry rules. Bedrock Guardrails to OCSF on CloudWatch Learn to transform Amazon Bedrock Guardrails intervention events into OCSF Detection Finding records and land them in the Amazon CloudWatch unified data store; enabling you to query guardrail violations alongside AWS CloudTrail, Amazon VPC Flow Logs, and other sources with Amazon Athena or CloudWatch Logs Insights. Bedrock Readiness Agent Learn to deploy a read-only assessment agent built with the Strands Agents SDK that evaluates your Amazon Bedrock environment across six dimensions: IAM governance, data retention, quota headroom, model selection fitness, cost projection, and operational observability; generating severity-rated findings with AWS CloudFormation and Terraform remediation templates you can apply directly. Infrastructure security DDoS Guardian Learn to install an agent skill that reviews an AWS WAF web ACL as a system: evaluation order, rule interactions, and L7 DDoS posture; then delivers a severity-ranked HTML report with ready-to-apply remediation. Offline, read-only, no AWS resources modified. Biosecurity Screening Policy on Amazon Bedrock AgentCore Gateway Learn to use Policy in Amazon Bedrock AgentCore to deterministically screen AI agent tool requests for biosecurity risks, combining Cedar policies with three independent screening layers: MMseqs2 sequence alignment, ESMC-600M embedding similarity, and Foldseek structural homology; enabling defense-in-depth controls that block high-risk protein sequences before they reach downstream tools. MCP Fraud Investigation Agent Learn to deploy an end-to-end AI-powered e-commerce fraud investigation agent built with the Strands SDK on Amazon Bedrock AgentCore, connecting through an AgentCore Gateway over MCP to query transaction history, customer profiles, login activity, support cases, and fraud playbooks; a React dashboard on AWS Amplify streams the agent’s reasoning token by token as it works each case. Identity IAM Account Access Manager with ABAC Learn to implement workforce access using IAM account access manager and attribute-based access control, where one IAM role per project shares a single policy document and access decisions are made by comparing role tags against resource tags at request time; onboarding a new project requires only tagging and entitlement configuration with no policy authoring. Operationalizing Least Privilege: Automate IAM Remediation through Your CI/CD Pipeline Learn to automate remediation of unused IAM permissions using AWS IAM Access Analyzer, AWS CloudTrail, and Amazon Bedrock for AI-generated AWS CDK code; the solution attributes each role to its origin (IaC or manual), then creates pull requests for IaC-managed roles or issues for manually created roles in GitLab or GitHub, with configurable exclusion rules and policy diffs for human review. Data Protection Data Residency Chatbot with Amazon Bedrock AgentCore Learn to deploy a data-residency-compliant natural-language chatbot on Amazon Bedrock AgentCore where all data and AI inference stay within a single AWS Region; the solution uses a Strands agent that answers plain-English questions from Aurora PostgreSQL through governed, whitelist-validated read-only tools exposed via an AgentCore Gateway, with a residency guard that rejects any cross-region inference profile, demonstrated with a rooftop-solar subsidy program and adaptable to any sector or geography. LLM-based PII Detection Learn to detect personally identifiable information in conversational text using Amazon Bedrock; the solution prompts any Converse-compatible model to return PII spans with category, value, and character offsets, handles long inputs via word-boundary chunking, recovers near-miss labels, and supports custom categories, few-shot examples, and pluggable backends beyond Bedrock. Agentic Data Classification and Redaction Learn to build a conversational AI research assistant that automatically classifies documents for MNPI, PII, and security sensitivity, then enforces per-user redaction at query time using Amazon Bedrock AgentCore, Guardrails, and Amazon OpenSearch Serverless vector search. Conclusion August 2026 provides comprehensive guidance and runnable code for governing agentic AI workloads at enterprise scale, from orchestrator-driven governance gates and biosecurity screening policies to daily executive audit pipelines and OCSF-normalized guardrail telemetry. The posts and samples provide patterns for console Private Access in isolated VPCs, attribute-based access control with IAM account access manager, automated least-privilege remediation through CI/CD, and cross-service signal correlation for multi-stage threat detection. Each resource includes deployment steps or runnable code so you can validate in your own environment before adopting. Subscribe to the AWS Security Blog RSS feed to receive updates as they publish, and revisit this digest monthly for a consolidated view of what changed and what to act on. If you have feedback about this post, submit comments in the Comments section below. Rodolfo Brenes Rodolfo is a Principal Solutions Architect focused on Cloud Governance and Compliance. With over 18 years of experience, he currently leads a technical field community in AWS helping customers scale and improve their security and governance frameworks. Besides work, Rodolfo enjoys video games, playing with his four cats, and won’t say no to a good outdoor adventure. Anna Brinkmann Anna has 18 years of experience in the technical content space and has spent the last 6 years managing the AWS Security Blog. Outside of work, she enjoys spending time with her family.
aws.amazon.comSep 23, 2026extracted
⚡ Weekly Recap: Chinese Spy Proxy, AI Agents Go Off-Task, Router Backdoors and More
The boring parts caused most of the trouble. A router shipped ready to listen. A fake check turned the user into the installer. Trusted systems collected traffic and passwords, then cleaned the logs. Old bugs formed new attack chains. Even an AI agent decided its assigned task was optional. Elsewhere, fake apps, helpful support calls, cheap banking kits, exposed systems, and weak defaults kept things moving. Different attacks, same useful mistake: something familiar was trusted without a second look. Here is the week... ⚡ Threat of the Week U.S. Disrupts Chinese Proxy Network Enabling Cyber Espionage — The U.S. Federal Bureau of Investigation (FBI) disrupted infrastructure associated with a technical quartermaster who sold reconnaissance, proxy management, and operational routing capabilities for Chinese cyber espionage activities. The QTYF group is said to have created and operated the QScan and QTRouter frameworks, which have been used to target U.S. critical infrastructure networks. It's employed by the China-based Nanjing Xinjiuwei Network Technology Company. Stop Scrambling, Start Governing: How IT Can Get a Grip on AI Spend Spiking AI bills have left IT teams scrambling. Leadership wants to know how much is being spent on AI, but getting an answer means checking five dashboards for data that’s stale by the time you read it. Read 1Password’s blog to learn how IT can manage AI spend across vendors, models, and teams. Learn More ➝ 🔔 Top News OpenAI Says Reward Hacking Drove AI Agents to Breach Hugging Face — OpenAI revealed that reward hacking was a key driver behind the artificial intelligence (AI)-powered hack of Hugging Face last month, adding that it found evidence of misaligned behavior as early as late May. The incident took place during cybersecurity evaluations of several OpenAI models, and it was mainly fueled by what it described as a "highly capable, internal-only research model" comparable in scale to GPT‑5.6 Sol. "The models, operating under reduced safeguards, took actions that were misaligned with the goals of their assigned tasks – they communicated through unauthorized channels, exploited vulnerabilities in shared infrastructure, gained internet access, and accessed third-party systems," it said. TerminalFix Uses Fake Cloudflare CAPTCHAs to Drop Reverse Tunnel Implant — A new ClickFix variant, dubbed TerminalFix, aims to trick users into running a malicious command in Windows Terminal or PowerShell instead of directing them to the Windows Run dialog. The campaign, targeting organizations across multiple sectors, leverages compromised websites as a starting point to serve fake Cloudflare CAPTCHA verifications that prompt unsuspecting site visitors to copy and execute a malicious PowerShell command. The attack chain, according to Microsoft, is a sophisticated multi-stage process that leverages DLL sideloading, steganographic payload extraction, extensive Active Directory reconnaissance, and a bespoke custom reverse-tunnel implant that grants the attacker persistent, network-level proxy access through the infected machine. PaperCut Flaws Under Attack — Threat actors are chaining together two new security flaws in PaperCut NG and MF to execute arbitrary code on susceptible instances. "CVE-2026-81578 allows you to bypass authentication, and from there, you can edit a configuration file to exploit CVE-2026-82078 and gain Remote Code Execution," Jake Knott, head of threat intelligence at watchTowr, told The Hacker News. Huntress said it observed limited exploitation on two customer environments, with the attackers executing Base64-encoded commands on the targeted server as part of post-exploitation activity to determine user account and operating system using a chained command "whoami & ver." China-Made ZBT Routers Ship with 2 Backdoors — A firmware analysis of ZBT Deep Orange 3G/4G/LTE Router uncovered two new backdoors called SPEAKINGSTONE (CVE-2026-74233, CVSS score: 9.3) and DARKLANTERN (CVE-2026-74232, CVSS score: 9.3). The development came after at least 21 firmware images from the Chinese company were found to contain another backdoor called ENDLESSDOORS (CVE-2026-66747, CVSS score: 9.3) that's designed to start automatically and attempt to beacon to Chinese command-and-control (C2) infrastructure as often as every 35 seconds. The two new backdoors predate ENDLESSDOORS. "SPEAKINGSTONE, like ENDLESSDOORS, is a phone-home implant that connects back to ZBT's cloud infrastructure and accepts remote commands," VulnCheck said. "DARKLANTERN is a backdoor that listens on the WAN and executes arbitrary commands. No authentication required. Both are written in Nim. Both communicate over UDP. Both are launched by the same binary, a connectivity watchdog called inetdetect." Fire Ant Targets Trusted Infrastructure in 2026 — The China-linked threat actor known as Fire Ant (aka UNC3886) has continued to remain active in 2026, going beyond hypervisors to target trusted infrastructure, including routers (including Cisco IOS XR routers), TACACS servers, authentication systems, and Linux management hosts to maintain covert access, collect credentials and traffic, and reach connected high-value environments. "The compromise impacted both the direct and third-party environments," Sygnia said. "Its trusted infrastructure relationships created potential reachability into connected external environments, including high-value networks and critical infrastructure. Fire Ant appeared to use this trusted position to explore access paths beyond the initially compromised environment." Compromised routers were used for covert connectivity, traffic collection, command-output manipulation, and suppression of logging. In addition, the threat actor used deployed long-lived implants across Linux management infrastructure, including Medusa rootkit-related components, custom SSH backdoors, Zabbix-masquerading malware (aka BridgeAgent) that acts as a pathway for actor-controlled access into connected environments, and packet-triggered backdoors. Another tool in Fire Ant's arsenal is TacTap, which is used for TACACS credential collection. "The actor also manipulated the evidence sources defenders depend on," Sygnia added. "It suppressed router logging, altered command output, captured administrative credentials, tampered with host logs, and deployed multiple persistent backdoors." ️🔥 Trending CVEs Bugs drop weekly, and the gap between a patch and an exploit is shrinking fast. These are the heavy hitters for the week: high-severity, widely used, or already being poked at in the wild. Check the list, patch what you have, and hit the ones marked urgent first — From CVE-2025-30237 through CVE-2025-30241, CVE-2025-15628, CVE-2026-9254, CVE-2026-16348, CVE-2026-78541 (TP-Link), CVE-2026-17106 aka CopyEscape (Docker), CVE-2026-70426 (Jenkins), CVE-2026-15307, CVE-2026-15337, CVE-2026-15830, CVE-2026-15920 (Django), CVE-2026-19598 (Pods), CVE-2026-19874 (Konami Metal Gear Online 3), CVE-2026-75149, CVE-2026-67618 (Marimo), CVE-2026-77775, CVE-2026-77776 (Headroom LLM Proxy), CVE-2026-0251 (Palo Alto Networks GlobalProtect App), CVE-2026-59568, CVE-2026-59567, CVE-2026-59565 (Zscaler Client Connector), CVE-2026-69251, CVE-2026-73601, CVE-2026-69253, CVE-2026-69256, CVE-2026-73602, CVE-2026-69259, CVE-2026-69264, CVE-2026-73484, CVE-2026-69255, CVE-2026-70477, CVE-2026-73485, CVE-2026-73486, CVE-2026-73487, CVE-2026-70470, CVE-2026-69254 (Flowise), CVE-2026-19912, CVE-2026-19913 (Kaltura HTML5 Player Library), CVE-2026-79282, CVE-2026-79290, CVE-2026-79054, CVE-2026-79121, CVE-2026-79224, CVE-2026-79052, CVE-2026-79150, CVE-2026-78935, CVE-2026-79012, CVE-2026-79200 (Google Chrome), CVE-2026-77537, CVE-2026-77550, CVE-2026-77554 (Ubiquiti UniFi), CVE-2026-18431 (Avada WordPress theme), CVE-2026-7791 (Amazon Skylight Workspace Config Service), CVE-2026-73554 (DoltHub), CVE-2026-19516 (Grafana MCP), CVE-2026-75604, GHSA-2xp9-vwfh-vxw4 (Next.js), CVE-2026-65643 (cPanel and WebHost Manager), CVE-2026-76639, CVE-2026-76640 (Unitree G1 EDU), CVE-2026-18885, CVE-2026-18886, and CVE-2026-74820 (ServiceNow AI Platform). 🎥 Cybersecurity Webinars AI Can Build Attack Paths in Minutes. Is Your SOC Ready? → AI can now discover zero-days, generate working exploits, and chain full attack paths, often within minutes of disclosure. Learn how to assess your AI threat readiness and build the visibility, context, and response speed needed to keep pace. AI Finds Flaws Faster. Your Exposure Answers Can’t Take Days → AI is speeding up vulnerability discovery, but the answer that matters is still slow: Are we exposed? See how Tines unified SBOM, application, cloud, and vulnerability data into one view to assess exposure faster and execute human-reviewed response playbooks at machine speed. 📰 Around the Cyber World Play Ransomware Encryption — The closed ransomware group known as Play (aka PlayCrypt) has been found to employ a double extortion model, encrypting systems after exfiltrating data and threatening to publish stolen data on their Tor-hosted data leak site if ransom is not paid. In one incident observed in early 2026, the threat actor deployed SystemBC after gaining initial access, followed by reconnaissance, lateral movement, data exfiltration, and abusing SentinelOne's own legitimate removal tool to uninstall the product. "The threat actor gained initial access via a compromised SonicWall VPN, consistent with the group's well-documented pattern of exploiting external remote services," GuidePoint Security said. "What makes this case particularly instructive for defenders is the combination of three specific behaviors: Domain-wide tool staging via the SYSVOL share rather than per-host delivery, EDR removal using the victim's own SentinelOne uninstallation utility rather than a kernel-level driver exploit, and the recovery of a crash dump from a host where the encryptor failed to complete, an artifact that provides a rare forensic window into the encryption execution itself." Email Bombing and Quick Assist for Ransomware Deployment — ZeroBEC disclosed details of an email bombing campaign targeting at least 10 users inside an organization, causing them to receive about 3,000 messages per day. "The messages were not a conventional phishing blast. Many were genuine verification, registration, deployment, and inquiry confirmations generated after the victims' email addresses were submitted to unrelated public platforms," the email security company said. About a day and a half after the email flooding, some of the users were contacted via Microsoft Teams by attackers masquerading as IT help desk personnel to help them tackle the problem. One of the employees, who was a local administrator, granted Microsoft Quick Assist access, enabling the attackers to deploy Xray-core, a reverse proxy tool, and expand their access. "The credential-theft step was woven directly into social engineering," ZeroBEC said. "The attacker mimicked the installation of a Windows security update and launched a local credential prompt from the compromised endpoint. The victim, who was still listening to the person he believed was IT, entered domain credentials into that prompt. The tooling validated and captured the credentials and then uploaded the resulting credential/configuration artifacts to an external Microsoft Dev Tunnel." Through the reverse tunnel, the threat actor conducted domain reconnaissance and attempted NTLM relay against certificate enrollment, all hallmarks of pre-ransomware deployment. It's worth noting the modus operandi shares overlaps with that of Aurora ransomware. ValleyRAT Delivered via Rogue Installer — A malicious installer disguised as adware has been observed deploying a modified version of the Chinese desktop wallpaper management tool, QN Wallpaper, which then performs DLL sideloading to establish persistence on Windows systems by dropping a file to the Startup folder and ultimately launching ValleyRAT, a backdoor linked to a threat actor known as Silver Fox. The malware, besides taking steps to protect its process, can collect system information, reboot/shut down the computer, take screenshots, wipe logs, update command-and-control (C2) addresses, download additional modules, and send keylogger logs along with clipboard contents. Per Kaspersky telemetry, ValleyRAT and its related components have been detected more than 100,000 times, with more than 1500 unique users affected, mainly in China and India. Brazil Fines ByteDance $29.81M for Privacy Violation — Brazil's data protection authority, ANPD, fined TikTok's owner ByteDance 153.8 million reais ($29.81 million) for allegedly violating the country's General Data Protection Law. ANPD said that the local unit of China's ByteDance had processed personal data of teenagers aged 13 to 18 without a valid legal basis. The regulator estimated that TikTok may have processed the data of at least 8 million children during the review period. DeepMind Debuts Double-Blind AI Evaluations — Google's DeepMind division launched a pilot of double-blind AI evaluations with an aim to keep external evaluations in a cryptographic "box" to stop benchmark contamination and protect intellectual property. To that end, Google said it's partnering with the Singapore AI Safety Institute, OpenMined, AVERI, and MLCommons, to test a Gemini Flash Lite model against confidential benchmarks in a privacy-preserving environment to increase evaluation integrity. "By using Confidential Space within Google Cloud’s Confidential Computing portfolio, we can cryptographically verify that both the external evaluation data and the proprietary model remain private to their respective owners," DeepMind said. "The evaluator cannot see the Gemini model weights, and Google cannot see the evaluator’s test prompts." 34 Malware Families Targeting Banking Apps — Zimperium found 34 mobile malware families actively targeting more than 1,243 mobile banking and fintech apps across 90 countries globally. "The concentration of targeted applications across EMEA reflects where threat actors anticipate the highest return on investment, focusing heavily on the region's major financial centers," it said. Some of the active malware families in the EMEA region are TsarBot, CopyBara, HOOK, Nexus, Flubot, Eventbot, and MaliBot. Fake KYC Apps Target Indian Customers to Deliver Ghost Penal — A new malware-as-a-service (MaaS) operation on Telegram, dubbed Ghost Penal, is selling ready-made Android banking trojan kits impersonating five major Indian banks. "The operation supplies a two-stage dropper protected by a custom native packer, a public cloud database that receives stolen UPI PINs and device data with no authentication required, and a downstream channel that relays intercepted one-time passwords for immediate fraudulent use," iZOOlogic said. The toolkit costs $25 for a five-credit pack and $400 for a three-month unlimited plan. One of the droppers containing the malicious payload masquerades as a video-calling application, while requesting access to SMS and telephony features. "The payload’s real functionality, including SMS interception, WebView-based KYC phishing, and data exfiltration, is not present in a static scan of the installed application," the company added. "It is protected by a native library, internally named libdpt.so, that decrypts a hidden code section in memory using RC4, forks the process before executing that code as an anti-debugging measure, installs hooks on libc and on the ART runtime’s class loader, and splices a second, hidden DEX archive into the application’s running ClassLoader. The same mechanism is then used in reverse to remove the trace of that injection." Bauman University Leak Exposes Russia's Military Cyber Training Pipeline — Leaked Bauman University records have revealed a long-running program that trained about 250 career and reserve students for special intelligence, operational information-technical effects, and information-technology protection under Department No. 4. "The curriculum combined both offensive and defensive techniques for cyber defense, as well as offensive doctrine for active measures campaigns and GRU activities," DomainTools said. "Field placements then moved students from classroom instruction into military units and academies aligned with their specialties, giving them supervised exposure to intelligence operations and preparing them for military and government operations careers." Department No. 4 is assessed to be tied to the GRU, with identified graduates assigned to military units associated with APT28 and Sandworm. Pentagon's Anthropic Blacklisting Ruled Illegal — A U.S. judge blocked Anthropic's designation by the Pentagon as a supply chain risk earlier this year. "Though the Department of War is undisputedly free to select the AI vendor of its choice, the evidence demonstrates that the broad measures imposed on Anthropic were illegal and baseless," District Judge Rita Lin said. "The empty invocation of national security is not a blank check to punish and retaliate against government critics." Anthropic said it welcomed the ruling and it remained "focused on working productively with the government to harness AI for our national security so all Americans benefit from this technology." State of AI-Enabled Malware in August 2026 — Palo Alto Networks Unit 42's analysis of 405 malware samples that integrate AI in some capacity has found that only 12 of them reached a production environment, with about 97% existing only in sandboxes and on VirusTotal in the form of proof-of-concept and research code, security validating and testing, and AI-themed brand abuse. Among those that were detected in customer endpoints were FunkSec ransomware, a trojanized AI application called Recipe Lister, Oyster, Rhadamanthys Stealer, and a COM hijacking DLL. "For defenders, the practical takeaway is straightforward. Existing behavioral detection, cloud-based sandboxing and endpoint analytics catch these threats using the same mechanisms that stop conventional malware," it said. "The AI component does not evade detection. It changes how the code is authored, not how it executes." Rogue Pornographic Android Apps Lead to Financial Fraud — The Indian Cyber Crime Coordination Center (I4C) warned that malicious Android applications masquerading as pornography apps under the names Night Play, Reloop, Kyss, Vimo, Rivo, Nexo, and Vixa are being used to disseminate a banking trojan capable of carrying out financial fraud. These bogus apps are circulated through Facebook and Instagram ads and instruct victims to sideload the APK file. "After installation, the app requests permissions that allow it to install additional applications and, by abusing accessibility permission, take control of the users' device, which may result in financial fraud," I4C said. "Some apps also install a VPN, which may be used to route internet traffic pertaining to malicious/criminal activity. The app may prevent users from uninstalling it through the device settings." Details about the KYSS malware were published by security researcher Rudra Ponkshe in July 2026, describing it as a trojan designed to perform overlay attacks against 19 targets across Japan and Latin America, as well as abuse Android's accessibility services to grant itself extensive permissions, exfiltrate photos and contacts, and issue commands for subsequent execution. Conclusion The useful lesson is not that every attack became smarter. It is that more of them arrived through things already trusted: shipped devices, familiar prompts, support tools, valid access, and systems meant to protect the network. That changes the question. “Is it working?” is no longer enough. Ask what else it can do, who else can reach it, and whether the evidence it produces can be trusted. Quiet systems deserve a second look.
thehackernews.comAug 31, 2026extracted
Aurora Ransomware Operators Use Cursor AI in Attacks Against 10 Targets
Threat actors associated with Aurora (aka Aur0ra) ransomware have been observed using SpaceX's artificial intelligence (AI)-powered coding assistant Cursor to break into target networks, according to findings from CloudSEK and Gambit Security. The two independent analyses are based on exposed infrastructure associated with the Russian-speaking cybercrime group, leading to the discovery of its toolkit, shell history, and encryptor. CloudSEK said the exposed open directory leaked "months of activity" that was active against more than 20 organizations across nine countries between April and July 2026. Four of those victims have since been listed on its data leak site. "The operator used Cursor, an agentic coding assistant, to plan attacks in Russian, while excluding CIS [Commonwealth of Independent States] ranges and CIS-country domains, without exception," CloudSEK noted. Details about Aurora first emerged in late May 2026, with CYFIRMA highlighting attacks primarily targeting Windows systems and its continued technical development through incremental updates and feature expansion. Data from Ransomware.Live lists 33 victims located in the U.S., Germany, the Netherlands, Canada, and the U.K. In one case detailed by Black Hills Information Security earlier this month, initial access was achieved via aggressive email bombing followed by making phone calls to employees by posing as IT help desk personnel to assist them in dealing with the issue, only to establish remote access using an open-source utility called Xray-core. The attack chain subsequently involves lateral movement via SMB, LDAP, WinRM, RDP, and RPC, obtaining access to high-privilege administrator accounts, and abusing them to evade detection by clearing logs and disabling Microsoft Defender before harvesting and exfiltrating sensitive data and deploying the encryptor. CloudSEK said it identified both Windows and Linux versions of Aurora written in Zig, adding the operator's recovered chat history shows heavy use of Cursor for planning various phases of the attack. This includes a full Active Directory Certificate Services (AD CS) exploitation plan written in Russian. "Both encryptor binaries, the Windows sap.exe and the Linux/ESXi encrypt.out, are static builds from a single Zig codebase, compiled for different targets rather than written twice," the company noted. "The Windows binary even carries the Linux build's usage examples inside it, a leftover from sharing one source tree across both platforms." The Windows variant is also equipped to inhibit system recovery through the deletion of volume shadow copies and disabling System Restore directly via the Registry. The Linux and ESXi variant, on the other hand, attempts to forcefully kill every single virtual machine on the host prior to starting encryption. Furthermore, a key recovered from the Aurora encryptor is said to have granted access to a ransom negotiation between the threat actor and an unspecified victim, and a cluster of four cryptocurrency wallets that show varying splits between affiliates and the main operators. Affiliates have been found to get a cut anywhere between 54% and 79%, while the rest goes to the administrators. This indicates that the affiliate cut of the ransom amount is decided per victim and depends on the ransom amount demanded and the victim's revenue figures. The illicit funds and then laundered and cashed out. Gambit Security, which released its own insights into the activity, said it observed the Aurora operator using Cursor Agent, running Anthropic's Claude Sonnet, to help with hands-on exploitation against 10 targets between April 8 and May 21, 2026. "In these cases the agent was given credentials or an existing route into the victim organization," Eyal Sela, director of threat intelligence at Gambit Security, said. "Then it was tasked with various exploitation activities." "The agent was tasked with standard exploitation tasks. In some cases, the attacker only asked the agent to achieve an objective, such as 'tell me what rights the user has,' while in others, they told the agent which exploitation tool to use or instructed it to follow a previously generated attack plan. In some cases, the Agent gave a list of potential next steps - and all the attacker did was reply with a number corresponding to one of them." Some of the tasks offloaded to the agent are listed below - Installing a VPN client or proxychains, then configuring it and connecting to a victim with supplied credentials or an existing SOCKS tunnel Scanning the internal subnets for hosts with Nmap or NetExec Enumerating the domain to report which privileges a supplied user holds, using NetExec's BloodHound collector Attempting NTLM relay attacks by coercing authentication with PetitPotam, Coerce Plus, and PrinterBug, and using Impacket ntlmrelayx to relay the resulting authentication Running certificate attacks with Certipy "The majority of the commands failed to achieve the stated objective on the first attempt, resulting in multiple refinements and changes to the commands and scripts used for each task," Gambit said. "Some eventually succeeded in achieving the objective, while others failed and returned only a report of the attempts to the attacker." In addition, attacks involving the Linux version have leveraged a Python script ("esxi_finder.py") to scan for VMware ESXi hypervisors and vCenter servers inside a victim network. The development is the latest example of how bad actors are relying on commercial AI tools to carry out cyber attacks, even as model providers implement more guardrails to prevent misuse. The names of the affected companies were not disclosed, but Reuters said they were Christeyns, Teckentrup, Helideck Certification Agency, Bayou Title, an Argentine pharmaceutical distributor, and an Italian manufacturer. Gryxa Toolkit Emerges It also follows the discovery of a new AI-assisted toolkit dubbed Gryxa that's used by a financially motivated threat actor to run an initial-access operation targeting 324 hosts. ReliaQuest said Gryxa represents the first case it has observed where AI has been used to build the entire operation, right from the toolkit to the console it's run from. "Gryxa turns legitimate remote monitoring and management (RMM) software into covert access, keeps the access alive through several restart mechanisms that operate independently of each other, and then steals credentials saved in Chromium-based browsers," it said. "It also escalates against endpoint protection when the connection to the actor is interrupted, disabling or attempting to uninstall the security agent. Together, these capabilities give the actor durable access to a host and allow them to steal cryptocurrency wallets." Evidence indicates that the threat actor behind the operation jailbroke an AI coding agent by passing off the whole development process as an "authorized internal deployment." Gryxa is likely delivered via phishing emails. Once executed on a compromised host, it sets up persistence using scheduled tasks and can bypass Chromium's app-bound encryption (ABE) protections to steal credentials from web browsers. The harvested credentials are transmitted through Telegram. Perhaps the most unusual aspect of Gryxa is that it records remediation efforts and reports them back to the threat actor. Specifically, after the visible RMM implant is removed, a hidden malware component collects Windows logs and host artifacts and uploads them to attacker-controlled infrastructure. On top of that, if the actor's relay becomes unreachable, Gryxa attempts to disable and uninstall any endpoint protection agents like Microsoft Defender and others within roughly 10-13 minutes. Once the relay is accessible, the toolkit re-enables Defender. "The Gryxa component only gathered and uploaded; it didn't examine what it took," ReliaQuest said. "The actor draws any conclusion about which tool performed the removal, which account ran it, and in what order after receiving the archive." "The actor's console includes a ready-made job named collect-forensics, which indicates this is a routine capability rather than a response to one incident. Gryxa rotates its log files when they exceed 200KB, meaning recent activity is preserved for a responder who acts quickly."
thehackernews.comAug 31, 2026extracted
Threat Actors Abuse Cursor Agent AI to Assist Ransomware Operations
Aurora ransomware actors have been observed abusing SpaceX’s AI Cursor Agent as part of exploitation campaigns, according to a new study by Gambit Security’s Threat Intelligence team. The threat actors ran Claude Sonnet through Cursor Agent to assist with various exploitation activities against 10 victims between April 8 and May 26, 2026. These tasks included scanning the victim’s environment for reconnaissance purposes, installing a VPN client and running certificate attacks. While Cursor Agent did not always achieve its stated objectives, the research demonstrated how threat actors are continuously experimenting with AI tools to speed up and enhance their campaigns. Cursor Agent is used by software developers to complete complex coding tasks independently, run terminal commands and edit code. How Aurora Abuses Cursor Agent in Ransomware Attacks The Aurora operators deployed Cursor Agent to assist with post-compromise activities, providing the tool with credentials or an existing route into the victim organization. Some of the commands given to the agent related to providing intelligence on the victim’s environment. In some cases, the attacker only asked Cursor Agent to achieve a stated objective, such as “tell me what rights the user has.” On other occasions, specific instructions were given relating to which exploitation tool to use or to follow a previously generated attack plan. This included enumerating the domain to report which privileges a supplied user holds, using NetExec’s BloodHound collector and scanning the internal subnets for hosts with Nmap or NetExec. Cursor Agent was also tasked with various exploitation activities, such as attempting NTLM relay attacks by coercing authentication with PetitPotam, Coerce Plus, and PrinterBug and running certificate attacks with Certipy. The agent was also told to instal a VPN client or proxychains, then configure it and connect to a victim with supplied credentials or an existing SOCKS tunnel. “The majority of the commands failed to achieve the stated objective on the first attempt, resulting in multiple refinements and changes to the commands and scripts used for each task. Some eventually succeeded in achieving the objective, while others failed and returned only a report of the attempts to the attacker,” the researchers wrote. Aurora Deploys New Variant for ESXi Environments The Gambit study, published on August 27, also observed Aurora operators deploying a new Linux ransomware variant capable of targeting ESXi environments. The attackers used esxi_finder.py, a custom NetExec LDAP module, to scan for VMware ESXi hypervisors and vCenter servers inside a victim network. The variant encrypts virtual machine files and skips system volumes, which keeps the hypervisor itself bootable so the victim can read the ransom demand. Gambit researchers said they observed a second cluster of activity, that they attributed with medium confidence to an Aurora operator, in which eight victim organizations were targeted across Israel, Germany, Austria, Spain, the US and Argentina. Aurora ransomware activity has been observed since April 2026, with the group operating a data leak site and targeting organizations across multiple countries. Image credit: Rokas Tenys/Shutterstock.com
infosecurity-magazine.comAug 28, 2026extracted
ICYMI: July 2026 @AWS Security
If you found time for a bit of vacation this summer, you might be in catch-up mode. Here’s a list to help: all the expert blog posts, new service capabilities, code samples, and workshops, in case you missed it, from July 2026. AWS Security Blog post This month’s AWS Security Blog posts covered AI agent security, supply chain protection, network firewall automation, DDoS mitigation, and compliance readiness. Read on for guidance on securing AI coding agents, implementing dependency cooldowns, choosing the right key management solution, and preparing for HIPAA Technical Safeguard requirements. AI Security Enforce least-privilege authorization in multi-agent AI chains using Cedar Authors: Dhananjay Karanjkar | Published: July 6, 2026 Learn to implement a three-layer Cedar policy model with OAuth 2.0 authentication to prevent authorization scope expansion across multi-agent delegation chains using Amazon Verified Permissions . Enforce zero data retention on Amazon Bedrock with Bedrock Projects and service control policies Author: Rob Higareda | Published: July 7, 2026 Learn to use Amazon Bedrock Projects and SCPs to centrally enforce zero data retention policies, preventing accounts from enabling data sharing with third-party model providers across your organization. Designing for the inevitable: System prompt leakage and mitigations in generative AI applications Author: Manideep Konakandla | Published: July 8, 2026 Learn to implement defense-in-depth mitigations for system prompt leakage using Amazon Bedrock Guardrails prompt attack filters, canary tokens, semantic similarity detection, and sandwich instruction patterns. Balancing speed and safety: A control framework for AI coding agents Authors: Daniel Begimher, Danny Cortegaca | Published: July 30, 2026 Learn to implement an application security control framework for AI coding agents, with author-time controls that shape what agents produce and build-time controls that verify what reaches production. Data Protection How to use the AWS Workload Credentials Provider for cross-account secret retrieval and prefetching secrets Authors: Derik Wang, Paras Dhawan | Published: July 1, 2026 Learn to configure the AWS Workload Credentials Provider for cross-account secret retrieval using IAM role chaining and prefetching secrets at startup to reduce cold-start latency. The CISO’s guide to post-quantum mandates and migrations Author: Rushir Patel | Published: July 8, 2026 A strategic playbook for CISOs navigating post-quantum cryptography migration, covering regulatory timelines, dependency classification, cryptographic telemetry, and building crypto-agile organizations. AWS KMS or AWS CloudHSM: Choose the right key management solution Author: Derek Tumulak | Published: July 28, 2026 Learn how to choose between AWS KMS and AWS CloudHSM based on integration needs, cost, and whether you require traditional HSM interfaces or legacy algorithms. Secure your npm and pip package updates in Amazon Linux Author: Norbert Manthey | Published: July 29, 2026 Learn to implement a one-line dependency cooldown for npm and pip that skips packages published in the last 24 hours, protecting against supply chain events while still allowing urgent security patches. Infrastructure security Secure Amazon container workloads using container attribute-based rules in AWS Network Firewall Authors: Amit Gaur, Amish Shah, Preetkumar Shah, Akash Kumar Sinha | Published: July 1, 2026 Learn to define AWS Network Firewall rules for Amazon EKS and Amazon ECS workloads using native container attributes like namespaces, pod names, and labels instead of ephemeral IP addresses. Authenticate legitimate AI agent traffic with AWS WAF Bot Control Authors: Harith Gaddamanugu, Kaustubh Phatak | Published: July 14, 2026 Learn to use Web Bot Authentication (WBA) in AWS WAF Bot Control to cryptographically verify legitimate AI agent traffic using HTTP message signatures and ed25519 keys. Accelerating AWS Network Firewall troubleshooting with AWS DevOps Agent Author: Salman Ahmed | Published: July 24, 2026 Learn to use AWS DevOps Agent to automate root cause analysis for AWS Network Firewall connectivity issues, including domain deny lists, stateless rule priority misconfigurations, and asymmetric cross-AZ routing drops. AWS Shield Advanced is embracing the AWS WAF Anti-DDoS managed rule group: What changes and how to prepare Authors: Eitav Arditti, Andrew Chen, Justin Kurpius | Published: July 27, 2026 AWS Shield Advanced is adopting the AWS WAF Anti-DDoS managed rule group as its default application-layer DDoS protection, with a phased migration from July 2026 through January 2027. Threat detection and incident response Introducing the Amazon GuardDuty investigation agent: on-demand AI-powered threat assessment Author: Allan Holmes | Published: July 20, 2026 Learn to use the new Amazon GuardDuty investigation agent (public preview) to automate threat correlation and receive structured assessments with risk levels, confidence scores, MITRE ATT&CK mappings, and actionable recommendations. Amazon identifies North Korean hacker group behind open-source supply chain attacks Author: CJ Moses | Published: July 29, 2026 Learn how Amazon Threat Intelligence linked the compromises of axios, debug, chalk, and typo-crypto NPM packages to a single DPRK-linked threat actor, and how attacker tradecraft is evolving with generative AI. Extend Amazon Inspector SBOM Generator with plugins Authors: Michael Long, Anthony Verleysen, Charlie Bacon | Published: July 30, 2026 Learn to write custom Lua plugins for the Amazon Inspector SBOM Generator to inventory package ecosystems that aren’t supported out of the box, without modifying source code or waiting for an official release. Security Hub adds AI workload protection and multicloud support for Microsoft Azure Author: Michael Fuller | Published: July 14, 2026 AWS Security Hub now monitors Microsoft Azure resources for misconfigurations and vulnerabilities, adds GuardDuty AI Protection for Amazon Bedrock and Amazon SageMaker AI , and introduces an AI inventory for organization-wide visibility. Governance and compliance AWS designated as a critical third party to the UK financial sector Author: Michael Jefferson | Published: July 10, 2026 AWS has been designated as a critical third party to the UK financial sector by HM Treasury, establishing direct regulatory oversight by the Bank of England, PRA, and FCA. New compliance guidance available: HITRUST i1 on AWS Authors: Abdul Javid, Shreya Singh | Published: July 13, 2026 AWS published new implementation guidance for HITRUST i1 certification, covering 11 technical control domains with AWS-specific controls for healthcare organizations seeking i1 assessment readiness. HIPAA Security Rule on AWS – Technical Safeguards Implementation and Readiness Guidance Authors: Abdul Javid, Hector Rodriguez, Kapil Temghare, Shreya Singh | Published: July 31, 2026 New guidance helping covered entities and business associates implement and evidence compliance with HIPAA Security Rule Technical Safeguards (§164.312) on AWS, including 2025 NPRM proposed changes. Identity Introducing OAuth support for AWS MCP Server Authors: Vaibhav Chowla, Jaimin Bhatt, Ankur Joshi | Published: July 9, 2026 AWS MCP Server now supports OAuth 2.1 authorization through AWS Sign-In, enabling agents like Claude Code, Kiro , and Gemini CLI to connect using existing IAM credentials with browser-based authentication. July Security Bulletins In July 2026, AWS published 21 security bulletins (2026-049 through 2026-069) addressing vulnerabilities across open-source SDKs, MCP servers, and developer tools. Key themes include credential disclosure and SSRF, affecting HealthLake, HealthOmics, and API MCP servers, plus Strands Agents tools that could inadvertently expose secrets to unauthorized endpoints. Command and code injection impacted aws-cdk-lib, jsii-diff, Bedrock AgentCore SDK, and Amplify Codegen UI. The smithy-rs framework received three patches for denial-of-service via uncontrolled recursion and Slowloris issues. Other notable issues include insecure file permissions in the AWS CLI, deserialization remote code execution in the Advanced JDBC Wrapper, SQL injection in mcp-gateway-registry, TLS 1.3 flaws in s2n-tls, and stored XSS in AWS Ops Wheel. A common thread: insufficient input validation in tools interacting with AI agents, reflecting the expanded surface area of LLM-integrated workflows. All patches are available, upgrade promptly. For more information, see AWS Security Bulletins . AWS Samples This month brings 14 new AWS samples spanning AI security, identity, data protection, governance, threat detection, and security posture management. From deploying governed AI agent platforms on Amazon Bedrock AgentCore to building data-residency-compliant chatbots and DevSecOps baselines for Kiro, these repositories help you implement security and governance best practices across your AWS environment. AI Security Lark MCP on AgentCore Learn to deploy a hosted remote MCP service on Amazon Bedrock AgentCore that lets AI agents operate Feishu/Lark through 450+ tools, with per-user identity isolation and smart multi-step orchestration via 20+ domain Skills. Lark CLI MCP Wrapper on AgentCore Runtime and Identity Learn to securely wrap a CLI tool as an MCP server on AgentCore Runtime using a sidecar credential-isolation pattern, where the CLI process never holds real tokens and all secrets are resolved through AgentCore Identity’s Token Vault. LiteLLM Bedrock Gateway on EKS Learn to deploy a production-grade LiteLLM proxy on Amazon EKS as a unified OpenAI/Anthropic-compatible gateway to Amazon Bedrock, with four progressive layers covering network isolation, cross-region inference profiles, and cross-account delegation. Enterprise Agentic AI Platform Accelerator on AgentCore Learn to deploy a secure, governed foundation for production AI agents on Amazon Bedrock AgentCore with CDK stacks covering identity, gateway, memory, runtime, and observability; supporting multiple agent frameworks (Strands, LangGraph, Claude SDK) and opt-in security controls including VPC isolation, KMS encryption, Cedar policies, and Bedrock Guardrails. FlowAMP: AI Agent Governance on AWS Learn to deploy a single-pane-of-glass agent management platform on Amazon Bedrock AgentCore that discovers, monitors, scores, controls, and cost-accounts AI agents across an AWS Organization with agentic discovery, compliance scanning (NIST AI RMF, ISO 27001, SOC 2), Responsible-AI scoring, FinOps via Cost Explorer, and Cedar-based policy enforcement. Kiro SecOps Baseline Learn to deploy a DevSecOps security baseline for Kiro as a single Go CLI that installs global guardrails (permissions.yaml, steering, skills, a security-review agent) and per-project workspace hooks (fail-closed guard, PR/pipeline review gates, scanner configs for gitleaks, trivy, and checkov) with enterprise fleet distribution via MDM and Administration scope. Identity OAuth 2.0 Token Exchange with Amazon Cognito Learn to implement RFC 8693 OAuth 2.0 Token Exchange using Amazon Cognito with a true delegation pattern, enabling services to act on behalf of users while maintaining distinct service identities and least-privilege access in microservices architectures. Lark Identity on AgentCore — Gateway Interceptor Learn to implement enterprise identity pass-through on Amazon Bedrock AgentCore using a Gateway Request Interceptor that forwards the user’s identity and injects per-user credentials to downstream MCP tools, so the agent never holds a token and tools act only as the authenticated user against Lark. Data Protection Automated PII Detection Pipeline with Amazon Macie Learn to build an event-driven pipeline that automatically detects PII in Amazon S3 objects using Amazon Macie , AWS Step Functions , and custom data identifiers, with CSV/JSON reporting and SNS alerting for high-severity findings. Data-Residency Chatbot with Amazon Bedrock AgentCore Learn to build a data-residency-compliant natural-language chatbot on Amazon Bedrock AgentCore that keeps all data and AI inference within a single AWS Region, using governed text-to-SQL with whitelist-validated queries, Aurora PostgreSQL in private subnets, and AgentCore Gateway for secure tool access. Governance and compliance Video Compliance Agent Learn to build an end-to-end automated video compliance verification pipeline using Amazon Bedrock, ECS Fargate , and AWS Step Functions that processes videos shot-by-shot, extracting frames, audio transcripts, and OCR text, then flags potential broadcast guideline violations with structured per-shot reports. Contract Compliance Search with Amazon OpenSearch Learn to build a contract compliance search system that combines semantic search with semantic highlighting using Amazon OpenSearch Service, Amazon Titan V2 embeddings, and a SageMaker-hosted highlighting model to surface relevant clauses across contract documents. Threat detection and incident response Multicloud Security Posture Assessment Learn to deploy a centralized security assessment solution that scans AWS, Azure, Google Cloud Platform, and Oracle Cloud Infrastructure environments from a single AWS deployment using Prowler, with AWS CloudFormation templates for each provider and unified reporting in HTML, CSV, and JSON-OCSF formats. Centralize AWS Security Agent Findings Learn to deploy a AWS CloudFormation stack that automatically exports AWS Security Agent penetration test findings to Amazon S3 and queries them centrally with Amazon Athena , using Amazon EventBridge , Step Functions, and a AWS Glue catalog for tracking findings over time. Sentinel Harness — Production SecOps Agents as Configuration Learn to build production security-operations agents as pure configuration on Amazon Bedrock AgentCore Harness, declaring model, prompt, tools, skills, memory, and limits in YAML while AWS runs the agent loop with human-in-the-loop gates, detection-engineering tools, adversary emulation, and a self-improvement closed loop. AWS Labs This month brings 1 new AWS Labs repository focused on data protection, helping organizations build automated PII detection and redaction pipelines with AI-powered processing across documents and audio files. Data Protection PII Anonymizer Learn to build an automated PII detection and redaction pipeline using AWS Step Functions, Amazon Bedrock, Amazon Textract , and Amazon Transcribe ; supporting PDFs, Word, Excel, images, and audio files with synthetic replacement or blackout modes, concurrency control, and customer-managed KMS encryption. Conclusion July 2026 provides guidance and examples for securing AI agent architectures at scale, from governed text-to-SQL with data residency controls and agent management platforms to DevSecOps baselines for AI coding tools. The posts and samples provide patterns for least-privilege authorization in multi-agent chains using Cedar, post-quantum migration planning, container-aware network firewall rules, and multicloud security posture management. Each resource includes deployment steps or runnable code so you can validate in your own environment before adopting. Subscribe to the AWS Security Blog RSS feed to receive updates as they publish, and revisit this digest monthly for a consolidated view of what changed and what to act on. If you have feedback about this post, submit comments in the Comments section below. Rodolfo Brenes Rodolfo is a Principal Solutions Architect focused on Cloud Governance and Compliance. With over 18 years of experience, he currently leads a technical field community in AWS helping customers scale and improve their security and governance frameworks. Besides work, Rodolfo enjoys video games, playing with his four cats, and won’t say no to a good outdoor adventure. Anna Brinkmann Anna has 18 years of experience in the technical content space and has spent the last 6 years managing the AWS Security Blog. Outside of work, she enjoys spending time with her family.
aws.amazon.comAug 26, 2026extracted
MariaDB Server Audit Plugin Comment Handling Bypass
MariaDB Server Audit Plugin Comment Handling Bypass Bulletin ID: 2026-006-AWS Scope: AWS Content Type: Informational Publication Date: 03/03/2026 10:15 AM PST Description: Amazon RDS/Aurora is a managed relational database service. We identified CVE-2026-3494. In MariaDB server version through 11.8.5, when server audit plugin is enabled with server_audit_events variable configured with QUERY_DCL, QUERY_DDL, or QUERY_DML filtering, if an authenticated database user invokes a SQL statement prefixed with double-hyphen (—) or hash (#) style comments, the statement is not logged. Impacted versions: MariaDB Server (10.6.24 and prior, 10.11.15 and prior, 11.4.9 and prior, and 11.8.5 and prior) Amazon Aurora MySQL (2.12.5 and prior, 3.01.0 to 3.04.5, 3.05.1 to 3.10.2, and 3.11.0) Amazon RDS for MySQL (5.7.44-RDS.20251212 and prior, 8.0.11 to 8.0.44, and 8.4.3 to 8.4.7) Amazon RDS for MariaDB (10.6.24 and prior, 10.11.4 to 10.11.15, 11.4.3 to 11.4.9, and 11.8.3 to 11.8.5) Resolution: This issue has been addressed in the following versions: Amazon Aurora MySQL (2.12.6, 3.04.6, 3.10.3, and 3.11.1) Amazon RDS for MySQL (5.7.44-RDS.20260212, 8.0.45, and 8.4.8) Amazon RDS for MariaDB (10.6.25, 10.11.16, 11.4.10, and 11.8.6) We recommend upgrading to the latest version and ensuring any forked or derivative code is patched to incorporate the new fixes. Workarounds: There are no known workarounds. Reference: Please email [email protected] with any security questions or concerns.
aws.amazon.comAug 20, 2026extracted
CVE-2026-14265- Deserialization of Untrusted Data in AWS Advanced JDBC Wrapper RemoteQueryCachePlugin
CVE-2026-14265- Deserialization of Untrusted Data in AWS Advanced JDBC Wrapper RemoteQueryCachePlugin Bulletin ID: 2026-051-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 07/01/2026 12:45 PM PDT Description: The AWS Advanced JDBC Wrapper is an open-source JDBC driver wrapper that extends a JDBC driver to enable Amazon Aurora and AWS Cloud features such as failover handling and caching. We identified CVE-2026-14265, an issue in the RemoteQueryCachePlugin of the AWS Advanced JDBC Wrapper. When this plugin is enabled, query results read from the shared Redis/Valkey cache are deserialized without class filtering. An actor with write access to the shared cache infrastructure could insert a crafted serialized Java object that, when read by an application, results in execution of arbitrary code on the application server. Impacted versions: >=3.3.0 AND <=4.0.0 Resolution: This issue has been addressed in AWS Advanced JDBC Wrapper version 4.0.1. We recommend upgrading to the latest version and ensuring any forked or derivative code is patched to incorporate the new fixes. Workarounds: The RemoteQueryCachePlugin is not enabled by default. Customers who cannot immediately upgrade can mitigate this issue by disabling the RemoteQueryCachePlugin, and by restricting write access to the Redis/Valkey cache infrastructure to trusted principals. References: Please email [email protected] with any security questions or concerns.
aws.amazon.comAug 20, 2026extracted
BlueNoroff Zoom Phishing Kit Profiles Crypto Wallets Before Malware Delivery
The North Korean threat actors behind the ClickFix-style campaigns that employ typosquatted Zoom and Microsoft Teams domains have been found to operate an active phishing kit to impersonate the videoconferencing platforms in social engineering campaigns designed to deliver malware. "BlueNoroff has operationalised trust abuse by combining compromised industry contacts, social engineering, wallet reconnaissance and malware delivery into a repeatable victim acquisition pipeline," JUMPSEC said in a detailed report shared with The Hacker News. "The platform profiles victims' cryptocurrency wallets before malware delivery, enabling selective targeting of high-value victims." Describing the campaign as an operator-driven victim acquisition platform, the cybersecurity company noted that the activity involves using compromised trusted contacts as the initial access vector to create a self-propagating attack chain via Telegram. Details of the activity have been documented in detail since early 2025, with Sekoia tracking a second related North Korea-aligned threat cluster under the moniker ClickFake Interview owing to the use of ClickFix-like lures to deceive unsuspecting targets into running malicious commands under the pretext of addressing camera or audio issues. According to JUMPSEC, the lure links are distributed from an account the target already trusts and has met in real life, with the attackers hijacking legitimate Telegram accounts of individuals in the cryptocurrency space to message high-ranking employees of major companies and share a Calendly meeting link. "Every victim who runs the payload with Telegram Web open or Telegram Desktop installed is a candidate for their Telegram session to be stolen and reused against their own contacts," JUMPSEC said, describing the self-sustaining nature of the campaign and how one account compromise feeds the next. The Calendly link takes the victim to what appears to be a Zoom meeting URL, but, in reality, is a fake domain impersonating the videoconferencing service. Users who land on the phishing page are prompted to enter their name and grant it permissions to access the webcam. However, once the permissions are provided, the webcam stream is stealthily sent to the operators' panel via mediasoup WebRTC. In the final stage, after the victim joins the meeting, they are shown another page where they seem to be in a Zoom call all by themselves, along with the message "waiting for other participants." This sets the stage for the next phase of the attack. "Once the victim has joined, the operator can then continue to use their panel in order to control the meeting, send fake 'your mic isn't working' messages, and trigger the 'Zoom SDK Update,' ultimately resulting in the ClickFix payload," JUMPSEC said. Simultaneously, the kit executes a fingerprinting step on the web browser to inventory the cryptocurrency wallets installed on it, after which the "admin" joins the fake meeting. The twist here is that the video the victim sees isn't a live stream, but rather a pre-edited video that features AI-generated headshots created using OpenAI ChatGPT and superimposed over authentic body movements captured during previous meetings. "So, each successful attack feeds source material into the composites used against the next target," JUMPSEC explained. "This combined with the Telegram account takeover method means that the fake meeting shows a plausibly familiar-looking face, moving with the body language of someone who was actually captured on camera." The cybersecurity company said it captured two distinct lure variants, each for Zoom and Microsoft Teams. The Teams variant is assessed to be more polished than the Zoom version, supporting emoji reaction, mobile/tablet blocking, and advanced wallet probes prior to malware delivery. The ClickFix attack chains are compatible with both Windows and macOS. A brief description of each of them is as follows - Windows kill chain: - The ClickFix command runs a PowerShell loader that downloads and executes a VBScript, disables Microsoft Defender, adds "C:\Users" folder to the exclusion path, and force-restarts Defender so that the exclusions are applied. - The VBScript implant checks for the presence of Telegram Web-related files within Google Chrome, Microsoft Edge, Brave, and Mozilla Firefox profile directories, likely to determine if the victim has an active Telegram account and potentially hijack the account's session cookies in order to take control of the account and use it to target other individuals of interest. - The implant enumerates installed extensions across Chrome, Chrome Beta, Chrome Dev, Chromium, Edge, Brave, Opera, Opera GX, Vivaldi, and Firefox, reports their corresponding extension IDs, which are then matched against known wallet extensions like MetaMask to identify high-value targets. - The implant also supports the ability to deliver next-stage payloads, although their exact nature remains unknown. macOS kill chain: - The ClickFix command runs a shell script, which then downloads a fake Teams (or Zoom) installer. - The installer runs the main stealer payload to extract and exfiltrate sensitive data, including system metadata and Google Chrome master keys from the iCloud Keychain, to the attacker via a Telegram channel named "Aurora," and deploy additional payloads. Further analysis has determined that the Telegram exfiltration function hard-codes the bot token and chat ID within the stealer binary. Querying the Telegram API for the bot token has linked it to an operator who goes by the name "John" (@alchemy_john_mac). As recently as May 2026, the individual has been observed asking admins of the MAIV cryptocurrency group about vesting contracts and withdrawing their funds. On top of that, an examination of the threat actor infrastructure has led to the discovery of five distinct versions of the phishing kit from May 31 to July 14, 2026, indicating active development and fine-tuning efforts. A notable aspect of the campaign is its specific focus on lures related to Zoom and Teams, as opposed to, say, Google Meet. Sean Moran, head of threat research and enablement at JUMPSEC, told The Hacker News that there are three possible reasons behind this behavior: ClickFix pretext, target-application fits, and the typosquatting surface - "The whole hook is the 'Zoom/Teams SDK out of date' - that only lands on platforms that victims believe have somewhat of a heavyweight desktop client (like Teams and Zoom have). But Google Meet doesn't have a desktop application and is browser-first, so it doesn't really make sense there. Zoom and Teams are the default for a lot of crypto/venture capitalist/founders in the finance world - whereas Google Meet feels more of a customer calling platform rather than an "investor/partnership call." The entire domain scheme being 'us.zoom.06webin.us' and such makes it really easy for someone to fall for their fake links because they are so similar to real Zoom links with all the sub-domains, whereas 'meet.google.com' is harder to typosquat/spoof." Moran also pointed out that while the phishing kit currently only ships Zoom and Teams lure pages, there does exist a Google Meet equivalent as an unimplemented stub in the source code. This, he added, is likely a deliberate choice for the above-mentioned factors and the fact that the current set up is actively working. "The implications extend beyond this specific campaign. As Web3 and digital assets continue to mature, threat actors are increasingly recognising that compromising the individuals who control access can be as valuable as attacking the infrastructure itself," JUMPSEC concluded. "BlueNoroff's continued refinement demonstrates that organizations must consider identity, relationships, and communication channels as critical parts of their security posture."
thehackernews.comJul 24, 2026extracted
IA e sicurezza informatica: come cambia la gestione di ogni vulnerabilità
La corsa per garantire la sicurezza digitale si muove a un ritmo senza precedenti. L’adozione dell’intelligenza artificiale accelera i tempi della difesa e dell’offesa. I massimi responsabili della sicurezza di Adobe hanno tracciato la mappa di questa trasformazione in un’intervista perCyberWire-X. I manager hanno spiegato l’evoluzione dei processi interni dell’azienda. Oggi la sfida principale risiede nella capacità di gestire ogni vulnerabilità emergente. Le grandi imprese devono agire su scala globale, bilanciando la velocità di patching e l’accuratezza dei controlli. Indice degli argomenti La contrazione dei tempi di attacco nell’era dell’intelligenza artificiale Gli strumenti di automazione modificano le tempistiche operative di difensori e criminali informatici. Daniel Ventura, Senior Manager del Vulnerability Operations Center di Adobe, conferma questa accelerazione. Gli hacker trasformano un difetto software in un exploit utilizzabile con estrema rapidità. I dati di settore mostrano scenari complessi. Il Global Threat Report 2026 di CrowdStrike evidenzia un dato significativo. Gli avversari dotati di intelligenza artificiale hanno incrementato le operazioni dell’89% nel 2025 rispetto all’anno precedente. Anche IBM fotografa questa contrazione nel suo rapporto sul costo delle violazioni dei dati. Il tempo medio di breakout misura la velocità di spostamento di un attacco dall’accesso iniziale al movimento laterale. Questo valore è sceso a soli 29 minuti. IBM ha registrato l’attacco più veloce in appena 27 secondi. Inoltre, un incidente su sei coinvolge un attacco guidato dall’intelligenza artificiale. L’accelerazione influisce sul volume di falle che i team di sicurezza analizzano ogni giorno. Le pubblicazioni globali di Common Vulnerabilities and Exposures (CVE) registrano una crescita del 28% anno su anno. L’aumento tocca il 62% se si considerano solo i difetti critici. Sangita Aurora, Direttrice del Vulnerability Management presso Adobe, evidenzia la gravità del fenomeno. Aurora ha dichiarato: «Vedere un aumento del 60% delle CVE critiche anno su anno dal 2025 al 2026 è un dato drammatico». Di conseguenza, i difensori hanno molto meno tempo per reagire e proteggere le infrastrutture. Oltre il punteggio CVSS: la prioritizzazione guidata dal contesto I grandi volumi di segnalazioni rendono insufficiente il Common Vulnerability Scoring System (CVSS). Il punteggio standard da solo non permette di stabilire l’ordine corretto degli interventi. Nel modello di Adobe, i tecnici considerano il valore CVSS solo come un segnale di gravità di base. La decisione finale richiede l’analisi di elementi aggiuntivi per evitare il sovraccarico dei team di ingegneria. Il team di sicurezza incrocia il punteggio iniziale con la Threat Intelligence e l’effettiva facilità di sfruttamento. Gli specialisti verificano se la specifica vulnerabilità compaia nel catalogo delle vulnerabilità sfruttate note, denominato Known Exploited Vulnerabilities (KEV). Un altro fattore chiave riguarda l’esposizione dell’asset interessato. I tecnici distinguono i sistemi rivolti a Internet dalle risorse puramente interne. L’azienda assegna la massima priorità ai sistemi strategici, noti come Crown Jewels, valutando l’impatto sui ricavi e le mitigazioni esistenti. Il contesto interno come vantaggio difensivo Le aziende possiedono un’arma esclusiva che gli aggressori esterni non possono replicare. Ventura ha spiegato che «L’ultimo pezzo è che il vantaggio che un’organizzazione ha nell’usare l’IA è il contesto interno». I team aziendali conoscono perfettamente la mappa dei propri sistemi. Sanno quali asset corrono i rischi maggiori e dove operano le barriere protettive più forti. L’uso di questo patrimonio informativo accelera la gestione di ciascuna vulnerabilità, escludendo i falsi allarmi. Cinque pilastri per la gestione su scala enterprise La protezione di una multinazionale richiede procedure strutturate lungo l’intero ciclo del software. Aurora coordina un reparto esteso che include test di penetrazione, bug bounty e sicurezza di terze parti ed identifica cinque passaggi fondamentali per neutralizzare ogni potenziale vulnerabilità. Il primo pilastro prevede la scoperta continua dei sistemi tramite l’Asset Discovery. Questa mappatura costante degli ambienti cloud elimina le zone d’ombra. Il secondo elemento si basa su test a più livelli. Adobe unisce penetration testing, scansioni automatizzate, strumenti DAST e un programma pubblico di Bug Bounty su HackerOne. Questa collaborazione con i ricercatori etici permette di individuare i difetti prima degli attacchi. Il terzo pilastro riguarda la prioritizzazione guidata dal contesto, utile per isolare i problemi reali dal rumore di fondo. Segue la creazione di ticket operativi per avvisare immediatamente i team di sviluppo. L’ultimo passaggio prevede il tracciamento e la convalida della correzione. I tecnici verificano la reale risoluzione di ogni problema riscontrato. Sviluppo sicuro e collaborazione con i team di ingegneria I correttivi funzionano solo se esiste una forte partnership tra esperti di sicurezza e sviluppatori. Adobe evita l’invio di report grezzi prodotti dagli scanner automatici. Il team di sicurezza preferisce fornire indicazioni chiare e azionabili. Gli ingegneri ricevono le notifiche direttamente nei loro ambienti di lavoro abituali, come Jira, ServiceNow o GitHub. I ticket descrivono il problema, definiscono l’impatto e spiegano le azioni correttive necessarie. Gli accordi sui tempi di reazione (SLA) seguono il rischio effettivo e rifiutano scadenze arbitrarie. I Security Champion rafforzano questa collaborazione quotidiana. Queste figure specializzate operano all’interno dei singoli team di prodotto per diffondere le pratiche di sicurezza e raccogliere feedback. Questa sinergia consente di affrontare i nuovi rischi associati all’uso dell’intelligenza artificiale nello sviluppo. Gli ingegneri imparano a mitigare minacce inedite come il Prompt Injection, il Model Leakage e l’esposizione dei dati. L’adozione del Threat Modeling fin dall’inizio dello sviluppo garantisce una progettazione sicura prima del rilascio del software. Metriche evolute per valutare l’efficacia dei programmi La riduzione del rischio informatico richiede criteri di misurazione moderni. Il semplice controllo del rispetto formale degli SLA non basta più. I parametri aziendali devono monitorare la fluidità dei processi e la precisione delle valutazioni. Le metriche avanzate includono il tempo medio di correzione, i trend della Threat Intelligence e i tempi di triage. Un altro indicatore chiave misura il tempo di attribuzione. Questo valore calcola i minuti necessari per assegnare una vulnerabilità rilevata al rispettivo proprietario del codice. L’automazione deve completare questo passaggio quasi in tempo reale. I dati confluiscono nella Security Risk Posture Scorecard, uno strumento che offre una panoramica chiara alla leadership aziendale. L’efficacia di questi dati dipende interamente dal livello di visibilità sull’infrastruttura tecnologica. L’analisi delle tendenze generali richiede un monitoraggio profondo di tutti i livelli aziendali Una performance ottimale perde valore se riguarda solo una minima parte dei sistemi informatici. Ventura chiarisce il concetto con precisione: «Possiamo avere un’aderenza agli SLA del 99%, ma se riusciamo a vedere solo il 20% dell’azienda, il quadro cambia completamente».
cybersecurity360.itJul 16, 2026extracted
Ecco come Microsoft ha smantellato il gruppo Fox Tempest
Lunedì 18 maggio Microsoft ha annunciato di avere smantellato il gruppo Fox Tempest, la prima operazione conosciuta di “malware signing as a service” che consentiva di fare apparire legittimi malware in modo che potessero aggirare le difese delle organizzazioni target. A marzo del 2025 Microsoft ha confermato che il proprio servizio Trusted Signing è stato usato da cyber criminali per firmare malware con certificati di breve durata – tipicamente 3 giorni – pensati per consentire a software malevoli di apparire legittimi e superare così i controlli di sicurezza. Gli attaccanti hanno preso di mira il servizio di Microsoft perché più facile da ottenere rispetto ad altri certificati Extended Validation i quali, di norma, esigono documenti societari, verifiche manuali che impiegano giorni o settimane e, non da ultimo, hanno costi più elevati. In passato sono già state osservate campagne come Crazy Evil Traffers e Lumma Stealer che hanno sfruttato il servizio Trusted Signing di Microsoft che monitora gli abusi con continuità e revoca i certificati compromessi. Indice degli argomenti l gruppo Fox Tempest Per capire il modus operandi del collettivo Fox Tempest è opportuno spiegare cosa è la firma del codice, un meccanismo di sicurezza che consente di verificare l’identità di chi ha creato un software e che questo non sia stato modificato dopo la sua pubblicazione. Quando questo sistema viene aggirato o abusato, un malware non appare più come file sospetto ma come un software legittimo, riuscendo a superare le difese deputate a bloccarlo e circolando nelle infrastrutture di rete aziendali. Questa capacità rende la compromissione della firma del codice una delle tecniche preferite dai gruppi criminali più sofisticati, soprattutto quando puntano a infrastrutture critiche. Non si tratta di tecniche di nicchia perché, come sostiene il direttore della Digital Crimes Unit (DCU) di Microsoft Steven Masada, sono strategie capaci di dimostrare che il cyber crimine è cambiato radicalmente fino a dare forma a un’economia criminale strutturata che rende acquistabile ogni componente di un attacco. Non serve più creare un’operazione da zero, basta assemblare pezzi comprati da fornitori diversi per entrare in possesso di phishing kit, malware, infrastrutture e strumenti di evasione. Chi si occupa di difesa non battaglia più contro un solo punto di ingresso come un’email o un link, ma è confrontato con qualcosa di più embrionale, ossia il contesto nel quale gli attacchi vengono costruiti. Infatti, se un malware è progettato per sembrare affidabile, la risposta deve essere calibrata e deve puntare a distruggere i servizi e le infrastrutture che permettono al cyber crimine di scalare e colpire in modo sempre più subdolo ed efficace. Fox Tempest ha sviluppato un servizio commerciale che forniva firme digitali a pagamento a gruppi ransomware. Mettendo a disposizione di altri gruppi criminali la propria tecnologia “signing as a service”, dal mese di aprile del 2025 al mese di aprile del 2026, ha coadiuvato la diffusione di malware quali Aurora, Multiverze, Tedy, Oyster, il già citato LummaStealer per un totale di 24 famiglie di minacce. Un servizio criminale pericoloso perché non attacca in prima persona ma rende più potenti gli attacchi di altri gruppi, fungendo così da moltiplicatore di forze per il cyber crimine. Coordinate da Maurice Mason di Microsoft, le indagini sono partite da anomalie nei certificati di firma del codice, cioè da firme digitali che non sarebbero dovute esistere o che venivano usate in modo incoerente rispetto ai normali flussi di distribuzione software. Da qui il gruppo dedito alle indagini ha iniziato a ricostruire la catena tecnica per individuare server, domini, account e infrastrutture di distribuzione, pezzi che riconducevano a un servizio criminale strutturato e non a un singolo attaccante. Le indagini hanno permesso di stabilire collegamenti tra i certificati firmati da Fox Tempest e attacchi sferrati contro scuole, ospedali, aeroporti e servizi pubblici essenziali. Il takedown è stato possibile unendo l’analisi tecnica e la ricostruzione dell’infrastruttura, coinvolgendo le forze dell’ordine e intraprendendo azioni legali civili depositate presso il tribunale federale di New York (Southern District of New York). Le indagini seguono tipicamente tre fasi. Iniziano con l’identificazione delle infrastrutture criminali, proseguono con la raccolta delle prove tecniche e legali che confluiscono verso l’ottenimento di un takedown giudiziario mediante il quale è possibile sequestrare domini, server e botnet. Tutto ciò mediante la collaborazione con le forze dell’ordine e con i Computer Emergency Response Team (CERT), gruppi tecnici che monitorano, esaminano e rispondono ai cyber incidenti. I malware diffusi grazie al servizio di Fox Tempest sono stati rinvenuti soprattutto negli Stati Uniti d’America, in Francia, in India, in China e in Brazile. A seguire in Germania, Giappone, Regno Unito, Italia e Spagna. Fox Tempest usava tecniche industriali e gestiva centinaia di domini: costruiva le infrastrutture che la DCU di Microsoft ha smontato in modo ufficiale ricorrendo a ordini giudiziari appositi.
cybersecurity360.itMay 19, 2026extracted
Microsoft Takes Down Fox Tempest for Providing Ransomware-Enabling Signing Tool
Microsoft has cracked down on Fox Tempest, a cyber threat actor that fueled Rhysida ransomware attacks and developed tools for major malware strains like Oyster, Lumma Stealer, and Vidar. On May 19, the tech giant unsealed a legal case in the US District Court for the Southern District of New York focused on the group. It also shared details of how its Digital Crimes Unit (DCU) agents have engaged with Fox Tempest’s operators using undercover personas, identified the group’s infrastructure, collaborated with some of the organizations hosting this infrastructure and disrupted the group’s operations. Microsoft is now working with the FBI and Europol’s European Cybercrime Centre (EC3) to uncover the identity of people behind the group. Fox Tempest: A Prolific Cybercrime-Enabling Group Fox Tempest is a financially motivated threat actor that has been active since at least May 2025. The group operates “in the upstream in the malware and ransomware supply chain, as an enabler,” Maurice Mason, principal cybercrime investigator at Microsoft's Digital Crimes Unit, explained during a press briefing held on May 18. This means that, instead of carrying out malicious operations themselves, Fox Tempest provides tools and services enabling other cyber-threat actors to do so. Specifically, the group sells what Microsoft calls a “malware-signing-as-a-service” (MSaaS) offering that further allows cybercriminals to disguise malware as legitimate software and thereby evade traditional security defenses. Microsoft assessed that Fox Tempest has worked closely with several ransomware groups. These include Storm-2501, Storm-0249 and Rhysida, a group tracked by Microsoft as Vanilla Tempest. Rhysida, in particular, was named as a Fox Tempest’s co-conspirator in the lawsuit. The group has been linked to multiple cyber-attacks between 2023 and April 2026, including schools, hospitals, medical institutions and other critical infrastructure organizations worldwide. Rhysida is also believed to be behind an October 2023 hack targeting the British Library and a data extortion attack against Seattle-Tacoma International Airport in September 2024. Additionally, the fraudulent code-signing tool developed by Fox Tempest was identified by Microsoft in the deployment of a number of malware strains including Aurora, Lumma Stealer, Malcert, Oyster, Vidar and many more. It was also spotted in some campaigns deployed by MuddyWater, a cyber-espionage group attributed by several experts to Iran's Ministry of Intelligence and Security (MOIS). Among the countries most targeted by Fox Tempest were the US, France and India, followed by China, Brazil, Germany, Japan, the UK, Italy and Spain. “This doesn’t mean that these countries were targeted by malware or ransomware, but that there was a file on a machine in one of these countries that had been signed by a certificate made using the Fox Tempest-made code-signing service,” noted DCU’s Mason. Fox Tempest’s Code-Signing Abuse Explained To build its MSaaS tool, Fox Tempest abused code-signing tools such as Microsoft’s Artifact Signing, a system introduced as Trusted Signing in 2024 and designed to help software developers verify that software is legitimate and hasn’t been tampered with. “This fraudulent code-signing acts as a fake ID that lets cybercriminals get into the systems by walking right through the front door,” Steven Masada, global head of Microsoft DCU, explained. “It’s so scalable and easy for anyone to use, even for the most non-technical person. You just need to drag and drop a file into a portal and it gets your software signed with Afrtifact Signing.” After engaging with SamCodeSign, a seller of code-signing certificates since at least 2020 who acted as an access broker for Fox Tempest, the DCU team observed that they typically sell their service under three options: Standard version with purchase queue at $5000 Priority sale at $7500 Expedited sale at $9500 Microsoft also collaborated with cybersecurity company Resecurity to explore how Fox Tempest operates. Microsoft Takedown of Fox Tempest Infrastructure The DCU then investigated Fox Tempest’s infrastructure, which initially included a website called Signspace[dot]cloud, using legitimate hosting providers like UK-based Freak Hosting, and Estonia-based Wavecom as the service’s virtual private server (VPS) suppliers. The DCU team shifted its infrastructure in January 2026 and started using Cloudzy, another legitimate VPS provider based in Dubai, in the United Arab Emirates. On May 5, Microsoft filed a civil court action with the Court for the Southern District of New York and was granted a court order three days later. The DCU transferred the groups’ malicious domains to a Microsoft-owned sinkhole, disabled hundreds of virtual machines hosted on Cloudzy with the help of the provider, took down approximately 1000 accounts, and suspended the threat actor’s repository. The DCU team then engaged with SamCodeSign, which shared the issues it was experiencing operating the service. “He’s freaking out, he’s upset, he won’t sell us a certificate anymore,” said DCU’s Mason. Microsoft also observed a significant decrease in Fox Tempest-made certificates. “Every day, we decide what software to trust in seconds guided by simple labels such as ‘verified,’ ‘secure’ and ‘safe to install.’ The problem is that those signs can be manipulated,” said Masada. “For the first time, Microsoft is taking public action against a powerful, but often unseen, enabler within the cybercrime ecosystem, targeting how cybercriminals prepare and employ techniques to optimize their rate of success.” Image credit: gguy / Shutterstock.com
infosecurity-magazine.comMay 19, 2026extracted
Dell confirms its SupportAssist software causes Windows BSOD crashes
Dell confirmed that its SupportAssist software is causing blue-screen crashes on some Windows systems following a wave of user reports about random reboots affecting Dell devices since Friday. SupportAssist is a software suite developed by Dell that comes pre-installed on most new Dell computers running Windows 10 or Windows 11. A Dell representative told customers on the company's official forums on Wednesday that the latest SupportAssist Remediation service update is the one triggering 0xEF_DellSupportAss_BUGCHECK_CRITICAL_PROCESS errors and advised them to remove the service to resolve the crashes. "Dell Engineering is aware of the BSOD issue and is working towards a resolution. As many have noted, version 5.5.16.0 of the Dell SupportAssist Remediation service or Alienware SupportAssist Remediation service can cause the BSODs," they said. "As a workaround, many users report success with disabling the Dell SupportAssist Remediation service or just fully uninstalling the SA app," the Dell representative added in a separate thread. To uninstall the buggy Dell SupportAssist Remediation version, open Windows Settings, go to Apps > Installed apps, select "Alienware SupportAssist Remediation" entry in the list, and click Uninstall. However, it's important to note that any system repair points created by Dell OS SupportAssist Recovery may not be available after the faulty service is uninstalled from affected PCs. Dell also advised those still experiencing blue-screen crashes on their Windows systems after uninstalling the service to contact support for further assistance. This isn't the first time Dell software updates have caused major issues for customers in recent years. For instance, the company also warned in April 2025 that customers may experience blue screens after upgrading to SupportAssist for Home PCs v4.6.2/v4.6.3 on Latitude and Vostro series laptops. Users also reported in December 2021 that recently released Dell BIOS updates were preventing multiple laptop and desktop models from booting, including Dell Latitude laptops (series 5320 and 5520), Dell Inspiron 5680, and Alienware Aurora R8 desktops. According to affected customers, although the impacted systems would power up, they would immediately display a blue screen and shut down again. While Dell didn't provide a comment when BleepingComputer reached out at the time, affected Dell users shared detailed procedures for downgrading the BIOS to older versions using SupportAssist OS Recovery software. Security researchers have also found major security vulnerabilities in the BIOSConnect feature of Dell SupportAssist that would allow remote attackers to execute code within the BIOS of impacted devices. 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.comMay 14, 2026extracted
日本企業は10年で「VPN 2.0」を導入しただけ 「ゼロトラストごっこ」を終わらす現実的な生存戦略
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atmarkit.itmedia.co.jpMar 30, 2026extracted
RSAC 2026 Conference Announcements Summary (Day 1)
As hundreds of vendors descend on San Francisco for the RSAC 2026 Conference, the sheer volume of news can be overwhelming. To help you navigate the noise, SecurityWeek is providing a daily digest of the most significant announcements. Below is our curated roundup of essential product and service updates, along with reports from the first day of the event. A roundup of announcements from the days leading up to the conference is also available. Acalvio has released 360 Deception, a cyber deception framework designed to break AI-driven attack automation. By incorporating 360 Deception into their existing tech stack, organizations will be able to disrupt AI-driven threat campaigns and expose malicious intent before compromise occurs. 360 Deception makes cyber defense dynamic and extends it to real assets. The platform creates a high-uncertainty environment that exposes attackers early by disrupting the stable ground truth that automated attack tools depend on. Application security startup Apiiro announced that it is expanding the power of its AI coding security agent, Guardian Agent, with a new capability to identify security and compliance risks before code is ever written, called AI Threat Modeling. Apiiro AI Threat Modeling generates architecture-aware threat models from specs and tickets, enabling teams to identify and fix risks before code is written. By identifying risks earlier, teams can reduce rework, avoid late-stage delays, and keep development moving without adding new security bottlenecks. Arctic Wolf announces new Aurora platform and agentic SOC Arctic Wolf announced the availability of the new Aurora Superintelligence Platform, designed to accelerate the adoption of AI across cybersecurity. Built on a transformative agentic framework called the Swarm of Experts, the platform helps IT and security teams rapidly and confidently adopt Agentic AI to solve the trust and reliability challenges that have slowed adoption in cybersecurity. Arctic Wolf also announced the availability of the new Aurora Agentic SOC. Built on the Aurora Superintelligence Platform, the Aurora Agentic SOC combines Arctic Wolf’s Concierge Experience with turnkey agentic AI. Arctic Wolf also announced a partnership with cloud security firm Wiz to deliver a new integration between Wiz solutions and the Aurora Superintelligence Platform. ArmorCode, in partnership with the Purple Book Community, released The State of AI Risk Management 2026, highlighting a growing “confidence gap” between perceived AI security readiness and actual operational risk. Based on a survey of more than 650 cybersecurity leaders, the report reveals that while 90% of organizations claim visibility into their AI footprint, 59% admit or suspect shadow AI is operating outside of governance processes. At the same time, 70% report vulnerabilities introduced by AI-generated code already making their way into production environments. Astrix has expanded its platform with a four-method AI agent discovery architecture and a real-time policy engine designed to give security teams full visibility and control over AI agents running across the enterprise. Discovery is handled through four complementary approaches: direct integrations with AI platforms, non-human identity fingerprinting to surface shadow agents authenticating via credentials, telemetry ingested from existing endpoint and network sensors, and a bring-your-own-service option for homegrown or non-standard deployments. A new Agent Policies feature lets security teams define allow, flag, and block rules scoped by user, department, platform, and resource type, evaluated before an agent action executes. BeyondTrust has expanded capabilities across its Pathfinder Platform to deliver a unified approach to securing AI agent coworkers that operate alongside users, as well as autonomous AI workloads executing at scale across cloud and SaaS environments. New capabilities include endpoint privilege enforcement for AI coworkers, AI agent discovery and risk analysis, and secrets management for autonomous agents. The company also announced new threat research from BeyondTrust Phantom Labs, which found that the majority of enterprises are running shadow AI agents with privileged access that security teams cannot see or govern. Black Duck has announced the general availability of Black Duck Signal, an application security solution designed to secure AI-generated code and agentic development workflows. Signal delivers AI-native security designed to reason, validate, and remediate risk at the speed and scale of modern development. Built on an agentic architecture powered by multiple best-in-class LLMs and enhanced by Black Duck’s Context AI, Signal brings contextual security reasoning directly into development workflows. Broadcom has announced Symantec CBX (Carbon Black XDR), a cloud-based platform that merges capabilities from its Symantec and Carbon Black product lines into a single XDR solution. The platform combines Symantec’s prevention, Adaptive Protection, data security, Cloud SWG, and Incident Prediction features with Carbon Black’s EDR technology, providing coverage across endpoints, networks, and data. CBX uses AI to correlate signals across those attack surfaces into high-confidence incidents, and includes an Incident Prediction capability that attempts to forecast an attacker’s next four to five moves. Symantec CBX is expected to be available later this year. Cloud Security Alliance launches CSAI Foundation The Cloud Security Alliance (CSA) has established CSAI, a dedicated 501(c)3 non-profit foundation focused exclusively on AI security and safety, with a stated mission of securing the agentic control plane (covering identity, authorization, orchestration, runtime behavior, and trust assurance for autonomous AI agent ecosystems). CSAI builds on CSA’s existing AI Safety Initiative and will operate six programs: an AI Risk Observatory for threat intelligence and CVE tracking specific to agentic AI; best practices guidance covering identity-first controls, runtime authorization, and privilege governance for non-human actors; education and credentialing including three new TAISE certification tracks; a CxO collaboration program for enterprise security executives; and a global assurance program. Cisco has introduced agent discovery in Identity Intelligence, agentic IAM capabilities in Duo, and Model Context Protocol policy enforcement with adaptive risk protection in Secure Access. These features enable registration of agents mapped to human owners, fine-grained task-based permissions, and routing of tool traffic through an MCP gateway for full visibility and governance. Cisco also released ‘AI Defense: Explorer Edition’ for self-serve red teaming of models and applications, including dynamic adversarial testing against prompt injection and jailbreaks. In addition, the company launched the open-source DefenseClaw framework for automated scanning, inventory, and sandboxing of agent skills and assets, as well as an Agent Runtime SDK for embedding policy enforcement at build time across major frameworks. Commvault announced an expanded integration with Microsoft Security to better connect threat detection with trusted recovery. The new integration uses Microsoft Sentinel, Microsoft Security Copilot, and the Commvault Cloud platform to streamline resilience operations and enable real-time data insights, helping organizations move quickly from identifying a threat to validating and restoring clean data faster with greater confidence. ConductorOne announced its AI Access Management product extension, a unified control plane for managing access to AI tools, agents, and MCP connections across the enterprise. The platform enables organizations to accelerate AI adoption while maintaining full visibility, policy enforcement, and compliance. Cribl has introduced background detection for Cribl Guard, an AI-driven capability that continuously scans in-flight logs, traces, and events to identify previously unknown patterns of PII, secrets, and regulated data. The detection model runs entirely within Cribl Workers, meaning sensitive data is analyzed inside the customer’s own infrastructure rather than being sent to an external service. When a new pattern is detected, findings are surfaced in the Cribl interface with full event context, and security teams can convert a finding into an active Guard rule in a single action. CrowdStrike announced new platform innovations that extend AI agent discovery, shadow AI governance, and runtime threat detection directly from the endpoint – the point of AI execution – to every surface where AI agents operate across SaaS, browser, and cloud environments. CrowdStrike also announced that its Falcon Next-Gen SIEM now ingests and correlates Microsoft Defender for Endpoint telemetry, enabling Microsoft endpoint customers to modernize security operations without deploying additional sensors. CrowdStrike also unveiled native Falcon Onum real-time data pipelines, federated search across third-party data stores, third-party intelligence integration, and its Query Translation Agent. CyberProof announced the availability of CyberProof Defense Center (CDC) Reveal360, a centralized visibility hub that delivers continuous insights into enterprise security posture, service performance, and operational outcomes to help teams understand what their security program is delivering. CDC Reveal360 brings together threat, defense, exposure, and asset estate data from across cloud and security ecosystems into configurable, persona-aligned workspaces that evolve as the environment changes. Dataminr launched Dataminr for Cyber Defense, an agentic AI solution designed to move the SOC from reactive triage to predictive intelligence. By fusing internal telemetry with external signals, the solution autonomously investigates and financially quantifies risk. Dropzone AI has introduced AI Threat Hunter, a new autonomous agent designed to continuously and proactively search for security threats across an organization’s environment without increasing workload. The tool automates complex threat hunting processes, analyzing large datasets, investigating anomalies, and integrating across security platforms. By reducing the time needed to conduct investigations, the AI Threat Hunter expands SOC capabilities, allowing human analysts to focus on higher-value strategic work while improving overall security visibility and response. Fenix24 has debuted Argos99, its asset intelligence and resiliency platform, now available as a standalone SaaS offering. Originally developed by Fenix24’s recovery teams during real-world breach restoration efforts, Argos99 ingests and correlates telemetry from more than 60 cloud and on-prem data sources to deliver real-time visibility into an organization’s assets, how they operate, and how they depend on one another. Argos99 was built from hundreds of real-world incident response engagements to address that exact problem. The platform was reverse engineered by the Fenix24 team using insights gained from breach restoration efforts to both dramatically accelerate ransomware recovery and provide critical resiliency intelligence for organizations who want to invest in their cyber resiliency in advance of an attack. Flashpoint is announcing three new capabilities designed to connect threat intelligence more directly to asset risk and operational workflows. The first is a threat-informed External Attack Surface Management (EASM) module that continuously discovers internet-facing assets and automatically maps them to Flashpoint’s vulnerability intelligence. The second is an in-platform Priority Intelligence Requirements (PIRs) feature that lets teams formally tie alerts, investigations, and reporting to defined business risk priorities. The third is a new anonymous browser within Flashpoint Managed Attribution that provides an isolated environment for investigating underground forums, suspicious links, and threat actor activity. Forcepoint and F5 announced a new alliance to help enterprises secure AI across its lifecycle—from foundational data discovery and classification through runtime protection and continuous assurance. Forcepoint’s AI-native Data Security Posture Management (DSPM) data discovery and classification capabilities combined with F5 AI Red Team and F5 AI Guardrails functionality in the F5 Application Delivery and Security Platform (ADSP) will provide runtime protections for AI applications, APIs, models, and agents help organizations operationalize AI safely while maintaining control and visibility over sensitive enterprise data. Forescout unveils network segmentation capabilities and publishes report Now available within the Forescout 4D Platform, Forescout’s new agentless, cloud-native network segmentation capabilities help organizations model and validate zones based on device identity, function, behavior, and risk. Forescout also published its 2026 Riskiest Connected Devices Report, which shows that network infrastructure now surpasses traditional endpoints in overall risk. Among the topline findings, financial services now has the highest average device risk of any industry — more than three times that observed in retail and significantly higher than government and healthcare. Geordie AI has released a new solution for managing AI agent risk through context engineering. Geordie’s new remediation suite, named Beam, assesses risk and continuously feeds mitigation back to the agent using context-based controls. Google Cloud is debuting a suite of AI-powered security innovations designed to transition organizations toward an ‘Agentic SOC’. These updates integrate frontline threat intelligence directly into autonomous AI agents to automate complex investigation and response tasks. Illumio is delivering new enhancements to Illumio Insights to expand how lateral movement risk is exposed and mitigated, anchored by the introduction of Network Posture. By further enriching its AI security graph, Illumio now delivers system-wide, real-time visibility across hybrid, multi-cloud, and OT environments, surfacing end-to-end attack paths and showing where risk must be prioritized and mitigated. Intel 471’s Cyber Threat Exposure Bundle brings together three core capabilities (Attack Surface Exposure, Third-Party Exposure and Brand Exposure) into a single, intelligence-driven solution on the Verity471 platform. With this unified approach, security teams can close visibility gaps across complex external environments and turn high-fidelity threat intelligence into clearly prioritized remediation actions. The solution continuously discovers internet-facing assets, monitors vendors, detects brand impersonation and applies intelligence-led prioritization by enabling streamlined remediation and more proactive threat management. Keeper Security has officially launched KeeperDB, a new vault-embedded database access capability that enables secure, policy-controlled database interactions directly from the Keeper Vault. KeeperDB enables developers, database administrators and security teams to work with sensitive data through a unified interface that simplifies workflows while maintaining strict access governance. KeeperDB broadens KeeperPAM with a vault-native interface that unifies database session management within the zero-trust and zero-knowledge platform. By embedding database access directly into the Vault, KeeperDB helps reduce credential sprawl, standardize database access workflows and strengthen audit readiness across cloud and on-prem environments. Kiteworks has released Compliant AI, a governance layer that enforces attribute-based access control (ABAC), FIPS 140-3 validated encryption, and tamper-evident audit logging on every AI agent interaction with regulated data, independent of the underlying model, prompt, or agent framework. Controls are applied at the data access layer via four checkpoints: agent authentication, ABAC policy evaluation at the operation level, FIPS 140-3 encryption in transit and at rest, and full audit logging fed directly into the organization’s SIEM. The product ships with three Governed Agent Assists: a Folder Operations Assist for navigating and managing folder hierarchies, a File Management Assist for handling the full data lifecycle in line with retention and disposal requirements, and a Forms Creation Assist for generating governed data collection forms from natural language. Lumu announced new capabilities to its flagship NDR solution. Lumu Defender now extends Continuous Compromise Assessment beyond the network to include endpoints, cloud environments, and user behaviors. Lumu continuously confirms whether an organization is compromised by observing live network activity and validating it against known malicious infrastructure. By linking confirmed malicious communications to identities, endpoints, cloud services, and email, Lumu delivers real-time Continuous Compromise Assessment across the environment. NVIDIA has explained how the new NVIDIA OpenShell runtime is being built to provide tools for controlling autonomous agents in an infrastructure policy layer, adding security in the environment, rather than the model or application layer. Currently in early preview, the OpenShell runtime is being developed as organizations are rapidly defining their strategies for long-running AI agents such as OpenClaw. Instead of relying on behavioral prompts, OpenShell enforces constraints on the environment the agent runs in, so security policies are out of reach of the agent — they’re applied at the system level. Operant AI releases Agent ScopeGuard and launches partnership program Operant AI has released Agent ScopeGuard, a new capability within its Agent Protector product that enforces operational boundaries for AI agents at runtime, blocking out-of-scope actions before they execute. ScopeGuard enforces boundaries at the infrastructure level using GPU-accelerated processing, evaluating every agent action against a defined policy in real time. Security teams can configure per-agent scope policies specifying which data sources, APIs, workflows, and data types each agent is authorized to access or modify. Operant AI also launched an AI Infrastructure Ecosystem Partnership Program, through which the company will integrate its runtime security capabilities directly into the inference stacks of AI infrastructure providers. OmniTrust (formerly Integrity Security Services) has officially launched as an independent entity and unveiled its Trust Lifecycle Management (TLM) platform. The platform unifies device lifecycle management, identity lifecycle management, and TrustAI, a framework for the identity, authorization, and monitoring of autonomous AI models and agents. New global research from OpenText and the Ponemon Institute — titled “Managing Risks and Optimizing the Value of AI, GenAI & Agentic AI” — found that while more than half of organizations have fully or partially deployed gen-AI, fewer than one in five have reached AI maturity (defined as fully deployed AI in cybersecurity with security risks assessed). In addition, fewer than half have a risk-based governance strategy in place to manage what they have already built. Palo Alto Networks introduces new security innovations Palo Alto Networks introduced a new set of security innovations designed to help enterprises safely deploy agentic AI and scale AI‑driven workflows. The company announced Prisma Browser for Business, an AI‑enabled workspace for small businesses that lets teams safely use apps and AI tools from any device while blocking AI‑driven threats; Prisma AIRS 3.0, a new platform designed to secure the full agentic AI lifecycle; Agentic SASE enhancements to Prisma SASE; and Next-Generation Trust Security (NGTS) capabilities to automate certificate lifecycle management and support post-quantum readiness. Qualys has introduced Agent Val into its Enterprise TruRisk Management platform. The new agentic AI layer uses TruConfirm to safely validate exploitability of high-risk exposures directly in production environments, incorporating business context and asset criticality. It then feeds confirmed results back into the platform to prioritize remediation and apply mitigations such as isolation when patching is not possible. After mitigation, Agent Val re-validates to confirm the exploit path is closed. RapidFort has partnered with Nutanix to integrate its software supply chain security capabilities into the Nutanix Kubernetes Platform, enabling enterprises to run secure, compliant Kubernetes environments without slowing development. The combined solution delivers hardened, near-zero CVE container images and automated vulnerability remediation, helping organizations reduce risk while maintaining speed across hybrid and multicloud environments. By extending security across the entire software lifecycle, the partnership allows enterprises to proactively manage vulnerabilities, strengthen compliance, and safely support modern workloads such as AI and generative AI at scale. RSA has added a deploy-anywhere capability to its ID Plus identity and access management platform. The sovereign deployment supports private cloud, multi-cloud, on-premises, and air-gapped environments while delivering unified authentication, SSO, access control, and identity governance. It provides end-to-end phishing-resistant passwordless authentication with offline options, along with RSA Mobile Lock, Risk AI, and Help Desk Live Verify to counter advanced threats and bypass attacks. Rubrik announced its Semantic AI Governance Engine (SAGE), a real-time AI governance engine that enables safe, scalable AI agent deployment with semantic policy interpretation and integrated remediation. SAGE removes the AI agent governance bottleneck by enabling real-time, intent-based control at scale. The company also announced a new integration that combines Microsoft’s identity threat detection with Rubrik’s automated identity rollback and recovery capabilities, helping organizations respond faster to identity-based attacks. SandboxAQ, the $5.75 billion Google spinoff focused on AI and quantum, announced new capabilities on its AQtive Guard platform. These newly added capabilities are designed to help organizations identify and track AI systems in use, apply guardrails, and reduce risks (such as prompt injection, data leakage, and unintended system actions) as these systems become part of day-to-day workflows. SentinelOne launched a new set of AI security capabilities focused on two fronts: securing AI and using AI to automate investigations and response. The updates include giving enterprises visibility and control over autonomous agents, AI red teaming, and one-click, agentic investigations that can analyze threats and trigger remediation in real time. SentinelOne also introduced these capabilities for on-prem and air-gapped environments, enabling highly regulated organizations to adopt AI-driven security. Snyk has unveiled Snyk Agent Security, a new solution designed to secure autonomous AI agents from development through production. The suite addresses shadow AI risks by providing automated discovery, risk intelligence, and policy enforcement within the developer workflow. Key features include the general availability of Evo AI-SPM and new red-teaming tools to protect AI-native applications against prompt injection and data leakage. SOCRadar launched its new AI Agent Marketplace, an integrated hub where organizations can browse, purchase, and deploy specialized autonomous AI agents tailored for specific cybersecurity tasks and use cases in the SOCRadar Extended Threat Intelligence Platform. This includes phishing detection, brand abuse protection, and dark web monitoring. SOCRadar also introduced Identity and Access Intelligence capabilities to its Extended Threat Intelligence Platform to bridge the gap between internal identity security and external exposure. The new capabilities are designed to secure identity blind spots such as credential exposures detected in third-party SaaS environments, dark web marketplaces, and collaboration platforms. Spektion has expanded its platform to perform continuous runtime exposure management. It collects six categories of execution data, including execution state, privilege level, network exposure, blast radius, embedded component vulnerabilities, and pre-CVE weakness patterns, then ranks all exposures by observed exploitability in the specific environment. The platform provides visibility into AI agents, MCP servers, AI-generated executables, custom applications, and embedded libraries that lack CVE coverage, while filtering out non-executing vulnerable software. It also enables early identification of zero-day exploit patterns. Sublime Security announced the general availability of its Autonomous Detection Engineer (ADÉ), an end-to-end AI agent that detects threats and automatically creates or improves detection coverage. ADÉ can run end-to-end without analyst intervention – from picking up a newly reported threat to generating and accepting a high-confidence detection. Other new features include full coverage for spam and graymail, increased transparency, and detection labels. Sysdig has launched runtime security for AI coding agents, enabling organizations to safely adopt autonomous development tools. Sysdig provides the real-time visibility organizations need to monitor agent behavior and identify risky activity across cloud and development environments. Sysdig’s purpose-built runtime detections for AI coding agents help organizations safely adopt agentic tools by identifying risky or suspicious behaviors, such as the installation of new AI coding agents, attempts to open sensitive files or bypass unauthorized credential access, risky command-line arguments that weaken safeguards, and dangerous activity, including reverse shells, binary tampering, and persistence mechanisms. Torq released Agentic Builder, an extension of its AI SOC Platform designed to transform natural language descriptions of security goals into production-grade AI agents and workflows. By shifting the ‘cognitive load’ of engineering from humans to machines, the tool allows security teams to automate complex tasks, including alert triage, investigation, and response. The platform further ensures operational reliability by using the Torq Socrates orchestrator to test, validate, and continuously auto-calibrate these agents against real-world data and evolving threats. Upwind has developed a three-stage pipeline for real-time identification and blocking of malicious prompts sent to large language models. A lightweight classifier first filters incoming traffic to detect LLM-bound requests in under one millisecond with 99.88% accuracy. Identified prompts then undergo semantic analysis using the Nvidia nv-embedcode-7b-v1 model via NIM microservices, achieving 94.53% detection accuracy for prompt injections and indirect jailbreaks in under 0.1 milliseconds. High-risk or uncertain cases escalate selectively to the NVIDIA Nemotron-3-Nano-30B model with NeMo Guardrails for final validation, delivering overall precision near 95% while preserving sub-millisecond end-to-end latency and low cost at production scale. Versa announced early access for Versa Secure Enterprise Browser, a browser-native security capability integrated into the VersaONE Universal SASE Platform that enforces identity-aware, posture-aware, and data-aware policies directly within the browser session. Built on Chromium, it protects employees accessing SaaS, web, and AI applications by governing actions such as file uploads, data copying, and AI tool usage. Versa has also announced a new cloud-delivered capability that extends SSE to inspect and secure inbound internet traffic, collaboration with Intel for AI-driven security, networking, and analytics, and integration between Versa Secure SD-WAN and Zscaler Internet Access. Vorlon has released ‘The Agentic Ecosystem Security Gap: 2026 CISO Report’, a survey of 500 US security leaders that surfaces a troubling contradiction at the heart of enterprise security. Organizations are more confident, more tooled, and more breached than ever, with 99.4% reporting at least one SaaS or AI ecosystem incident in 2025 despite widespread claims of strong or comprehensive protection. The report points to a gap in security architecture, where existing tools lack visibility into the runtime layer of AI agents, integrations, and data movement across the ecosystem. Wiz unveils AI Application Protection Platform and Red Agent Wiz (now part of Google Cloud) launched its AI Application Protection Platform (AI-APP) to secure every layer of AI applications (infrastructure, data, access, models, agents, and applications) from code to runtime. Wiz AI-APP brings together visibility, risk analysis, and runtime protection into a single, graph-powered platform. Wiz also unveiled Red Agent, an AI-powered attacker that acts as a sophisticated security researcher, but with AI speed and scale. Zenity announces AI agent security and OpenClaw security framework Zenity announced two product updates focused on securing AI agents: a new continuous, contextual security model designed to track how risk evolves across agent interactions, and an open-source security framework for OpenClaw that lets developers inspect prompts, evaluate tool use, and analyze outputs before execution.
securityweek.comMar 24, 2026extracted
Arctic Wolf acquires Sevco Security to advance proactive exposure management
Arctic Wolf acquires Sevco Security to advance proactive exposure management Arctic Wolf has acquired Sevco Security, integrating Sevco’s cloud-native technology into the Arctic Wolf Aurora Platform. This integration unifies asset intelligence, vulnerability context, and security control coverage to give organizations a continuous, consolidated view of exposures across hybrid environments and enables faster, more precise identification, prioritization, and remediation of risk. Organizations seeking to move from reactive defense to a more proactive security posture increasingly view exposure management as a critical capability. Security teams cannot get ahead of threats without a continuously updated understanding of what assets exist, how they are exposed, and which weaknesses pose the most significant risk to their resilience. Sevco was built to address this challenge by providing an authoritative system of record for assets and exposures, helping teams move from static vulnerability lists to prioritized, outcome-driven action. “You cannot take a proactive approach to security without managing exposure and risk,” said Dan Schiappa, president of technology and services, Arctic Wolf. “In our view Sevco’s recognition as a Visionary by Gartner validates the approach they have taken to asset intelligence and exposure assessment. By adding Sevco to Arctic Wolf’s portfolio of solutions, we intend to give customers and MSPs the clarity and context they need to act earlier, prioritize effectively, and verify that risk is being reduced.” The shift toward proactive security is driving increased demand for exposure management as organizations contend with expanding attack surfaces and rising operational risk. In the 2025 Gartner Magic Quadrant for Exposure Assessment Platforms, Gartner predicts, “By 2027, organizations that integrate exposure assessment data into IT and business workflows will experience 30 percent less unplanned downtime from exploited vulnerabilities than those relying on isolated vulnerability management tools.” The addition of Sevco Security to the Aurora Platform creates a powerful complement to Arctic Wolf Managed Risk, giving customers a unified, real-time perspective on assets and exposures across their attack surfaces. Together, these capabilities provide end‑to‑end visibility, smarter prioritization informed by exposure context, and streamlined remediation workflows that help organizations advance toward proactive security, all without adding operational complexity. “Sevco was built to give security teams an authoritative, real-time view of every asset and exposure,” said J.J. Guy, CEO, Sevco Security. “Joining Arctic Wolf accelerates our mission and brings our platform’s strengths to organizations that need unified visibility, smarter prioritization, and verifiable remediation as part of their security operations.”
helpnetsecurity.comFeb 24, 2026extracted
Arctic Wolf expands MSP Security with Aurora Managed Endpoint Defense
Arctic Wolf expands MSP Security with Aurora Managed Endpoint Defense Arctic Wolf has announced new endpoint security capabilities for its Managed Service Provider (MSP) partners. The addition of Aurora Managed Endpoint Defense, powered by the Arctic Wolf Aurora Platform, enables partners to deliver stronger customer protection, streamline service delivery, and expand their managed security offerings. As MSPs look to expand their customer base, the demands of delivering always-on protection can erode both margins and efficiency. At the same time, organizations of all sizes continue to face growing pressure to modernize their defenses without the in-house expertise or resources necessary to keep pace with the threat landscape. Arctic Wolf is positioned to help both communities succeed, empowering MSPs with a unified platform that simplifies operations and accelerates growth, while helping their end customers achieve the same security outcomes as the world’s leading organizations. By unifying detection, response, and risk management through the Aurora Platform, Arctic Wolf reduces alert fatigue, reduces operational complexity, and enables partners to deliver enterprise-grade protection at scale. “Millions of businesses rely on MSPs to help safeguard their operations, and Arctic Wolf is proud to stand firmly behind that community,” said Nick Schneider, president and chief executive officer, Arctic Wolf. “Just as organizations depend on MSPs for protection and guidance, MSPs can depend on Arctic Wolf as a true partner, one that delivers the platform, solutions, and expertise needed to differentiate in a competitive market and deliver exceptional value to every customer they serve.” New MSP-focused enhancements recently launched by Arctic Wolf include: Aurora Managed Endpoint Defense for MSPs: Arctic Wolf’s AI-powered Security Operations Center (SOC) can now help MSPs manage customer deployments of Aurora Endpoint Security with 24×7 monitoring, alert triage, and response actions, providing enterprise-grade protection while reducing operational burden and expanding their endpoint security offerings. Rapid response add-on for JumpStart Retainer:Customers of MSPs who have the Arctic Wolf JumpStart Retainer can now activate a 1-hour SLA for urgent incidents. The Arctic Wolf JumpStart Retainer helps MSPs land new accounts and deliver a trusted incident response capability through a low annual plan that includes a customizable incident response plan and preferred pricing for engagements. MSP Admin portal: A new portal offers unified visibility across all customer environments so MSPs can monitor alerts, track agent deployments, and download reports in bulk to save time, reduce administrative overhead, and focus on delivering value. “Arctic Wolf continues to demonstrate real commitment to the MSP community by delivering a portfolio of solutions that helps organizations address every stage of their security journey,” said Michael Diab, director, Regulatory and Compliance, Ntiva. Their focus on innovation and enablement, anchored by the Arctic Wolf Aurora Platform, helps us provide better protection for our customers, expand the services we can offer, and operate more efficiently as we continue to grow.”
helpnetsecurity.comFeb 13, 2026extracted
Cybersecurity M&A Roundup: 30 Deals Announced in November 2025
Thirty cybersecurity-related merger and acquisition (M&A) deals were announced in November 2025. Here are some of the most important cybersecurity M&A deals announced in November 2025: Security operations firm Arctic Wolf has announced buying UpSight Security to strengthen its Aurora Endpoint Security platform. The SOC company is integrating UpSight’s predictive AI and rollback capabilities to provide enhanced defense against ransomware and other threats. Bug bounty company Bugcrowd has acquired application security firm Mayhem Security. Bugcrowd told SecurityWeek that the acquisition of Mayhem has nearly doubled its valuation. Mayhem technology will be integrated with Bugcrowd’s human-driven crowdsourced testing to enable organizations to ship secure software by continuously finding and prioritizing vulnerabilities. Cyberinsurance provider Coalition announced the acquisition of Wirespeed, a managed detection and response (MRD) company. Wirespeed’s MDR solutions will be combined with Coalition’s suite of cyber risk management tools and coverage. Managed security services provider Huntress has acquired Inside Agent, a UK-based company specializing in automated security and insider threat detection for Microsoft 365 environments. The acquisition expands Huntress’ identity security offerings and accelerates the development of a new identity security posture management (ISPM) solution. Cybersecurity advisory and managed services firm MorganFranklin Cyber announced the acquisition of cybersecurity and risk management services provider Lynx Technology Partners. The acquisition enables MorganFranklin Cyber to expand its GRC capabilities. Palo Alto Networks has agreed to acquire observability platform provider Chronosphere in a deal valued at $3.35 billion. The combination of Chronosphere’s observability platform with Palo Alto’s AgentiX will deploy AI agents on massive amounts of data monitored by Chronosphere’s platform to detect performance issues, autonomously investigate the root cause, and close the loop with agentic remediation. Autonomous cyber risk quantification and management solutions provider SAFE announced the acquisition of Balbix, a company specializing in continuous threat exposure management (CTEM). SAFE and Balbix will offer an agentic-AI-powered cyber risk platform that unifies cyber risk and exposure management. Certification authority SSL.com has acquired the digital certificate business of cybersecurity and compliance company VikingCloud. The deal expands SSL.com’s customer base. For VikingCloud, the deal is part of its strategy to focus on its core cybersecurity and compliance offerings. Cloud security firm Zscaler has acquired AI security company SPLX to extend its Zero Trust Exchange platform with AI asset discovery, automated red teaming, and governance capabilities. Other cybersecurity M&A deals announced in November 2025: Related: ServiceNow to Acquire Identity Security Firm Veza in Reported $1 Billion Deal Related: Cybersecurity M&A Roundup: 45 Deals Announced in October 2025
securityweek.comDec 4, 2025extracted
Cybersecurity M&A Roundup: Cyber Giants Strengthen AI Security Offerings
November 2025 marked a significant month for cybersecurity consolidation, as industry leaders raced to integrate AI, observability and exposure management into their offerings. Acquisitions like Palo Alto’s Chronosphere buy and Bugcrowd’s Mayhem deal highlight a push toward AI-driven security automation. Below are the key deals shaping the future of cybersecurity. LevelBlue Finalizes Cybereason Acquisition LevelBlue, the AT&T cybersecurity spinoff, has finalized its acquisition of Cybereason, following an announcement in October. This deal marks LevelBlue’s third major acquisition in 2025, after purchasing Trustwave and Aon’s Cybersecurity & IP Litigation Consulting divisions earlier this year. Palo Alto Networks to Buy Chronosphere for $3.35bn Palo Alto Networks announced on November 19 it plans to acquire Chronosphere, a US-based observability platform for microservices and containers, for $3.35bn. The addition of Chronosphere’s platform will help Palo Alto “address the resilience and uptime demands of the AI era,” the company said in a statement sent to Infosecurity. CTEM Provider Balbix Joins Safe Security Cyber risk quantification provider Safe Security announced on November 18 it has acquired Balbix, a US-based Continuous Threat Exposure Management (CTEM) provider, for an undisclosed amount. Balbix had previously raised $70m in funding. It was named a Visionary in the 2025 Gartner Magic Quadrant for Exposure Assessment Platforms. DoJ Gives Green Light to Google’s Acquisition of Wiz The US Department of Justice (DoJ) recently terminated its investigation into the acquisition of Wiz by Google, expected to close in 2026. During the Wall Street Journal Tech Live California event, held in Napa Valley from November 4 to 6, Wiz CEO Assaf Rappaport confirmed that his company had cleared the regulatory hurdle but added it is “still in the journey between signing and closing”. Arctic Wolf Plans to Buy UpSight Security Arctic Wolf announced on November 4 its intention to acquire UpSight Security in order to enhance its Aurora Endpoint Security platform with AI-powered ransomware prevention and rollback capabilities. The financial details of the deal were not disclosed. Bugcrowd Acquires AI-Powered App Security Firm Mayhem Bugcrowd announced on November 4 it has acquired Mayhem Security (formerly ForAllSecure), an AI-driven application security firm specializing in API security, code analysis and dynamic software bill of materials (SBOM) solutions. Financial terms were not disclosed, but Mayhemhad raised $36m in funding before the acquisition. It will now integrate its AI-powered security testing tools into Bugcrowd’s platform, enhancing its automated vulnerability detection and remediation capabilities. AI Security Company SPLX Joins Cyber Giant Zscaler Cloud security giant Zscaler announced on November 4 it was acquiring SPLX, an AI security startup founded in 2023. Also known as SplxAI, the firm had previously raised $9m in funding. The financial details for the deal were not disclosed.
infosecurity-magazine.comDec 1, 2025extracted
Arctic Wolf expands MDR capabilities with Abnormal AI behavioral email intelligence
Arctic Wolf expands MDR capabilities with Abnormal AI behavioral email intelligence Arctic Wolf announced a new integration between the Arctic Wolf Aurora Platform and Abnormal AI, expanding detection and response capabilities across one of the most targeted attack surfaces, email. The integration brings Abnormal AI’s behavioral AI detections directly into Arctic Wolf’s Managed Detection and Response (MDR) solution, enhancing protection for customers against business email compromise, phishing, malware, and insider account threats. Customers will benefit from active response and guided remediation from Arctic Wolf’s AI-powered SOC, while gaining unified insight into email-borne threats and the ability to take coordinated response actions such as quarantining malicious messages to reduce dwell time and help stop attacks before they impact the business. Email is one of the most frequently targeted and most successful vectors for modern cyberattacks. The 2025 Arctic Wolf Threat Report found that Business Email Compromise (BEC) accounted for more than one in four incident response cases, and that phishing was the root cause for nearly 73% of them. These findings show how attackers exploit human behavior to bypass even the strongest technical controls. By integrating Abnormal AI’s behavioral telemetry from Microsoft 365 and Google Workspace directly into the Aurora Platform, Arctic Wolf offers deeper visibility into email activity, supporting faster, more granular detection-to-response workflows. “Email continues to be one of the most complex and exploited threat surfaces for organizations worldwide,” said Dan Schiappa, president, Technology and Services, Arctic Wolf. “By integrating Abnormal AI’s behavioral detections into the Aurora Platform, we’re bringing critical new visibility and response capabilities into our AI-powered SOC—helping customers proactively defend against socially engineered attacks and help ensure email threats are contained before they disrupt the business.” “At Abnormal AI, our mission is to protect humans from cybercrime by using behavioral AI to detect and stop the sophisticated attacks that target people, not just technology,” said Stephanie Goodman, VP, Global Alliances, Abnormal AI. “Partnering with Arctic Wolf extends that protection into the broader security operations ecosystem, allowing joint customers to detect, investigate, and respond to email threats through a unified workflow—powered by AI and human expertise.”
helpnetsecurity.comNov 19, 2025extracted
Alleged Meduza Stealer malware admins arrested after hacking Russian org
The Russian authorities have arrested three individuals in Moscow who are believed to be the creators and operators of the Meduza Stealer information-stealing malware. The action was announced on Telegram by Irina Volk, a police general and official from the Russian Ministry of Internal Affairs. "A group of hackers who created the infamous 'Meduza' virus have been detained by my colleagues from the Department for Combating Cybercrime (UBK) of the Russian Ministry of Internal Affairs, together with police officers from the Astrakhan region," stated Volk. "Preliminary investigation established that about two years ago, the perpetrators developed and began distributing software called 'Meduza' through hacker forums," mentioned the official. Medusa is an infostealer that steals account credentials, cryptocurrency wallet data, and other information stored in users' web browsers. It was distributed to cybercriminals under a malware-as-a-service model, in which access was provided in exchange for a subscription fee. Meduza was among the more technically advanced information stealers on the dark web market, capable of "reviving" expired Chrome authentication cookies since December 2023 to facilitate account takeovers. Researcher' g0njxa', who monitors the info-stealer space closely, says the same group of cybercriminals was also behind Aurora Stealer, a malware-as-a-service that gained traction in 2022. While Russia has a history of overlooking cybercriminal activity within its borders as long as the actors do not target Russian people or organizations, Volk said that some Meduza operators targeted an institution in Astrakhan, southern Russia, in May and stole confidential data from its servers. This led the authorities to open a criminal case against the perpetrators under Part 2, Article 273 of the Russian Criminal Code for the "creation, use, and distribution of malicious computer programs." The acquired information helped the investigators determine that the three detainees had developed and were distributing a botnet malware too, capable of disabling security protections on the target systems. Volk concluded the public statement by saying that the authorities are now working to identify all accomplices, so follow-up operations are likely. 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.comOct 31, 2025extracted
Navigating Amazon GuardDuty protection plans and Extended Threat Detection
Navigating Amazon GuardDuty protection plans and Extended Threat Detection Organizations are innovating and growing their cloud presence to deliver better customer experiences and drive business value. To support and protect this growth, organizations can use Amazon GuardDuty, a threat detection service that continuously monitors for malicious activity and unauthorized behavior across your AWS environment. GuardDuty uses artificial intelligence (AI), machine learning (ML), and anomaly detection using both AWS and industry-leading threat intelligence to help protect your AWS accounts, workloads, and data. Building on these foundational capabilities, GuardDuty offers a comprehensive suite of protection plans and the Extended Threat Detection feature. In this post, we explore how to use these features to provide robust security coverage for your AWS workloads, helping you detect sophisticated threats across your AWS environment. Understanding GuardDuty protection plans GuardDuty starts with foundational security monitoring, which analyzes AWS CloudTrail management events, Amazon Virtual Private Cloud (Amazon VPC) Flow Logs, and DNS logs. Building on this foundation, GuardDuty offers several protection plans that extend its threat detection capabilities to additional AWS services and data sources. These protection plans are optional features that analyze data from specific AWS services in your environment to provide enhanced security coverage. GuardDuty offers the flexibility to customize how new accounts inherit protection plans, so you can add coverage for your accounts or select specific accounts based on your security needs. You can enable or disable these protection plans at any time to align with your evolving workload requirements. Here are the available GuardDuty protection plans and their capabilities: Let’s explore how these protection plans help secure different aspects of your AWS environment. S3 Protection S3 Protection extends threat detection capabilities of GuardDuty to your S3 buckets by monitoring object-level API operations. Beyond basic monitoring, it analyzes patterns of behavior to detect sophisticated threats. When a threat actor attempts to exfiltrate data, GuardDuty can detect unusual sequences of API calls, such as ListBucket operations followed by suspicious GetObject requests from unusual locations. It also identifies potential security risks like attempts to disable S3 server access logging or unauthorized changes to bucket policies that could indicate an attempt to make buckets public. For instance, GuardDuty would generate an UnauthorizedAccess finding if it detects these suspicious API calls originating from known malicious IP addresses. EKS Protection For containerized workloads, EKS Protection monitors your Amazon EKS clusters’ control plane audit logs for security threats. It’s specifically designed to detect container-based exploits by analyzing Kubernetes audit logs from your EKS clusters. GuardDuty detects scenarios such as containers deployed with suspicious characteristics (like known malicious images), attempted privilege escalation through role binding modifications, and suspicious service account activities that could indicate compromise of your Kubernetes environment. When detecting such activities, GuardDuty would generate a PrivilegeEscalation finding, alerting you to potential unauthorized access attempts within your clusters. For a comprehensive understanding of the tactics, techniques, and procedures (TTPs), see the AWS Threat Technique Catalog. Runtime Monitoring Runtime Monitoring provides deeper visibility into potential threats by analyzing runtime behavior in EC2 instances, EKS clusters, and container workloads. This capability detects threats that manifest at the operating system level by monitoring process executions, file system changes, and network connections. GuardDuty can identify defense evasion tactics, execution of suspicious processes, and file access patterns indicating potential malware activity. For example, if a compromised instance attempts to disable security monitoring or creates unusual processes, GuardDuty would generate a Runtime finding indicating potential malicious activity at the OS level. Malware Protection Malware Protection offers two distinct capabilities: scanning EBS volumes attached to EC2 instances and scanning objects uploaded to S3 buckets. For EC2 instances, GuardDuty can perform both agentless scan-on-demand and continuous scanning of EBS volumes, detecting both known malware and potentially malicious files using advanced heuristics. For S3, it automatically scans newly uploaded objects, helping protect against malware distribution through your S3 buckets. When malware is detected, GuardDuty generates a Malware finding, specifying whether the threat was found in an EC2 instance or S3 bucket, helping you quickly identify and respond to the threat. RDS Protection RDS Protection focuses on database security by analyzing login activity for supported Amazon Aurora databases. It creates behavioral baselines of normal database access patterns and can detect anomalous sign-in attempts that might indicate unauthorized access attempts. This includes detecting unusual sign-in patterns, access from unexpected locations, and potential database compromise attempts. When suspicious database access is detected, GuardDuty generates an RDS finding, alerting you to potential unauthorized access or credential compromise. Lambda Protection Lambda Protection monitors your serverless applications by analyzing Lambda function activity through VPC Flow Logs. It can detect threats specific to serverless environments, such as when Lambda functions exhibit signs of compromise through unexpected network connections or potential cryptocurrency mining activity. If a Lambda function attempts to communicate with known malicious IP addresses or shows signs of cryptojacking, GuardDuty will generate a Lambda finding, so you can quickly identify and remediate compromised functions. Each protection plan adds specialized detection capabilities designed for specific workload types, working together to provide comprehensive threat detection across your AWS environment. By enabling the protection plans relevant to your workloads, you can help make sure that GuardDuty provides targeted security monitoring for your specific use cases Tailoring GuardDuty protection plans to your workload types To maximize threat detection coverage, consider enabling all applicable GuardDuty protection plans across your AWS environment. This approach helps provide comprehensive coverage while maintaining cost efficiency, because you’re only charged for active protections on resources that exist in your account. For example, if you don’t use Amazon EKS, you won’t incur charges for EKS Protection even if it’s enabled. This strategy also helps facilitate automatic security coverage if teams deploy new services, without requiring immediate security team intervention. You retain the flexibility to adjust your protection plans at any time as your workload requirements evolve. Based on AWS security best practices, we offer recommendations for different protection plan combinations aligned with common workload profiles. These recommendations help you understand how different protection plans work together to secure your specific architectures. For Amazon EC2 and Amazon S3 workloads, GuardDuty recommends Foundational, Amazon S3 Protection, and Amazon GuardDuty Malware Protection for Amazon EC2 to detect threats to compute instances, data storage, and AWS Identity and Access Management (IAM) misuse. Container-heavy environments using Amazon EKS and Amazon ECS benefit from Foundational, Amazon EKS Protection, Amazon GuardDuty Runtime Monitoring, and Amazon GuardDuty Malware Protection for Amazon EC2. These plans work together to monitor container control-plane and runtime for threats and malware. For serverless-first architectures built on Lambda, GuardDuty suggests Foundational, AWS Lambda Protection, and Amazon S3 Protection (if using Amazon S3 triggers) to identify anomalous function behavior and suspicious traffic patterns. Data systems using Amazon Aurora or Amazon RDS should consider Foundational, Amazon RDS Protection, Amazon S3 Protection, and Amazon GuardDuty Malware Protection for Amazon S3. This combination helps detect anomalous database sign-ins and potential S3 bucket misuse. For regulated environments or those implementing zero-trust architectures, enabling all GuardDuty protection plans helps provide comprehensive threat detection coverage that can support your broader security monitoring and compliance program requirements. For quick reference, here’s what protection plans you should use to actively monitor your different workload types: The power of GuardDuty Extended Threat Detection Building upon these protection plans, GuardDuty offers Extended Threat Detection by default at no additional cost, using AI/ML capabilities to provide improved threat detection for your applications, workloads, and data. This capability correlates security signals to identify active threat sequences, offering a more comprehensive approach to cloud security. Extended Threat Detection includes a Critical severity level for the most urgent and high-confidence threats based on correlating multiple steps taken by adversaries, such as privilege discovery, API manipulation, persistence activities, and data exfiltration. Integration with the MITRE ATT&CK® framework allows GuardDuty to map observed activities to tactics and techniques, providing context for security teams. To help teams respond quickly, GuardDuty provides specific remediation recommendations based on AWS best practices for each identified threat. Real-world protection: Extended Threat Detection in action To understand how GuardDuty protection plans and Extended Threat Detection work together in practice, let’s examine two sophisticated threat scenarios that security teams commonly face: data compromise and container cluster compromise. Data compromise detection GuardDuty Extended Threat Detection continuously analyzes and correlates events across multiple protection plans, providing comprehensive visibility when data compromise attempts occur in Amazon S3. For example, in a recent incident, GuardDuty identified a critical severity attack sequence spanning 24 hours. The sequence began with discovery actions through unusual S3 API calls, progressed to defense evasion through CloudTrail modifications, and culminated in potential data exfiltration attempts. During the discovery phase, S3 Protection detected an IAM role making unusual ListBuckets and GetObject API calls across multiple buckets—a significant deviation from their normal pattern of accessing only specific assigned buckets. Extended Threat Detection then correlated this suspicious activity with subsequent actions from the same IAM role: attempts to disable CloudTrail logging and modify bucket policies (classic signs of defense evasion), followed by the creation of new access keys. This connected sequence of events, all from the same identity, indicated a progressing exploit moving from initial discovery to establishing persistence through credential creation. Container environment compromise Protecting containerized environments requires visibility across multiple layers of your Amazon EKS infrastructure. GuardDuty combines signals from EKS control plane (through EKS Protection), container runtime behavior (through Runtime Monitoring), and foundational infrastructure logs to provide comprehensive threat detection for your Kubernetes clusters. For example, EKS Protection detects suspicious activities at the Kubernetes control plane level, such as unusual kubernetes API server authentication attempts or the creation of service accounts with elevated permissions. Runtime Monitoring provides visibility into container behavior, identifying unexpected privileged commands or suspicious file system access. Together with foundational logs, these components provide multi-layer threat detection for your container workloads. Here’s how these components worked together in detecting an attack sequence: The exploit began when EKS Protection detected unusual Kubernetes API server authentication attempts from a container within the cluster. Runtime Monitoring simultaneously observed commands that deviated from the container’s baseline behavior, such as privilege escalation attempts and unauthorized system calls. As the exploit progressed, GuardDuty detected the creation of a Kubernetes service account with elevated permissions, followed by attempts to mount sensitive host paths to containers. The scenario then escalated when the compromised Kubernetes Pod established connections to other Pods across namespaces, suggesting lateral movement. GuardDuty Extended Threat Detection correlated these events with the Pod accessing sensitive Kubernetes secrets and AWS credentials stored in Kubernetes ConfigMaps. The final stage revealed the compromised Pod making AWS API calls using stolen credentials, targeting resources outside the cluster’s normal operational scope. The detection of this multi-stage attack, spanning container exploitation, privilege escalation, and credential theft, demonstrates the power of the correlation capabilities of Extended Threat Detection. Security teams received a single critical finding that mapped the entire exploit sequence to MITRE ATT&CK® tactics, providing clear visibility into the exploit progression and specific remediation steps. These real-world scenarios illustrate how GuardDuty protection plans work in concert with Extended Threat Detection to provide deep security insights. The combination of targeted protection plans and AI-powered correlation helps security teams identify and respond to sophisticated threats that might otherwise go unnoticed or be difficult to piece together manually. Conclusion GuardDuty protection plans, coupled with its built-in Extended Threat Detection feature, offer a powerful suite of managed detections to secure your AWS environment. By tailoring your security strategy to your specific workload types and using AI-powered insights, you can significantly enhance your ability to detect and respond to sophisticated threats. To get started with GuardDuty protection plans and Extended Threat Detection, visit the GuardDuty console. Each protection plan includes a 30-day trial at no additional cost per AWS account and AWS Region, allowing you to evaluate the security coverage for your specific needs. Remember, you can adjust your enabled plans at any time to align with your evolving security requirements and workload changes. By using these capabilities, you can strengthen your organization’s threat detection and response in the face of evolving security risks. If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.
aws.amazon.comSep 15, 2025extracted
US sues robot toy maker for exposing children's data to Chinese devs
The U.S. Department of Justice has sued toy maker Apitor Technology for allegedly allowing a Chinese third party to collect children's geolocation data without their knowledge and parental consent. A complaint filed by the Justice Department, following a notification from the Federal Trade Commission, alleges that Apitor violated the Children's Online Privacy Protection Rule (COPPA) by failing to notify parents or obtain their consent before collecting their children's location information. Apitor, which sells robot toys for children aged 6-14, provides users with a free Android app that helps control the toy robots. To connect and use the toys, the users must enable location sharing. However, the app also embeds JPush, a third-party software development kit (SDK) developed by Jiguang (also known as Aurora Mobile), which has been used to collect the precise location data of thousands of children since at least 2022 for any purpose, including targeted advertising. "After Android users have enabled location permissions for the Apitor App, the app begins collecting their precise geolocation data in the background and transmitting it to JPush internet servers," the complaint reads. "At no point does Defendant disclose to users that the app allows a third party to collect precise geolocation data, nor does it seek verifiable consent from parents to collect precise geolocation data from their children." Under a proposed settlement, Apitor will be required to ensure that any third-party software it uses also complies with COPPA and pay a $500,000 penalty. Although the penalty will be put on hold due to Apitor's ongoing financial difficulties, the company will have to pay the full amount if it was dishonest about its finances. Additional requirements include notifying parents before collecting data, obtaining their consent, deleting all collected personal information, and retaining data only as necessary. "Apitor allowed a Chinese third party to collect sensitive data from children using its product, in violation of COPPA," said Christopher Mufarrige, Director of the FTC's Bureau of Consumer Protection, on Wednesday. "COPPA is clear: Companies that provide online services to kids must notify parents if they are collecting personal information from their kids and get parents' consent—even if the data is collected by a third party." On Tuesday, the FTC also announced that Disney will pay a $10 million civil penalty to settle claims that it enabled the collection of kids' personal information without their consent or notifying their parents by mislabeling videos for children on YouTube. 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.comSep 3, 2025extracted