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The Risks of Code Assistant LLMs: Harmful Content, Misuse and Deception

We recently looked into AI code assistants that connect with integrated development environments (IDEs) as a plugin, much like GitHub Copilot. We found that both users and threat actors could misuse code assistant features like chat, auto-completion and writing unit tests for harmful purposes. This misuse includes injecting backdoors, leaking sensitive information and generating harmful content. We discovered that context attachment features can be vulnerable to indirect prompt injection. To set up this injection, threat actors first contaminate a public or third-party data source by inserting carefully crafted prompts into the source. When a user inadvertently supplies this contaminated data to an assistant, the malicious prompts hijack the assistant. This hijack could manipulate victims…

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unit42.paloaltonetworks.com
Published
Sep 15, 2025
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language: en
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