Code Defence Cyber security

GitHub Copilot “CamoLeak”: The New Risk in AI-Assisted Coding

Summary: Researchers have detailed the “CamoLeak” technique, where attackers use prompt injection to trick GitHub Copilot into exfiltrating private user data (like API keys) by rendering them as invisible pixels in a chat response.

Business Impact: This introduces “Shadow AI” risk directly into the development pipeline. Your developers’ private code and secrets could be siphoned off simply by interacting with a malicious pull request or poisoned repository, without them ever running the code.

Why It Happened: LLMs used in coding assistants often lack strict separation between “instructions” and “data,” allowing manipulated text (like a code comment) to override the model’s safety guardrails.

Recommended Executive Action: Update your “AI Coding Policy” to mandate that developers check for “Prompt Injection” signs in external code reviews. Ensure that your CI/CD pipelines strip secrets *before* code is ever exposed to an AI assistant context window.

Hashtags: #AppSec #GitHubCopilot #CamoLeak #PromptInjection #DevSecOps

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