Researcher Flags Three Security Flaws in Microsoft AutoGen and LlamaIndex AI Frameworks

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A developer has filed three security vulnerability reports against two widely used AI agent frameworks, Microsoft AutoGen and LlamaIndex, which together hold over 110,000 GitHub stars. The reported issues include a Docker code executor that mounts host filesystem paths into containers without proper trust boundary checks, an agent self-modification flaw in AutoGen's Canvas memory module, and 441 instances of unbounded recursive execution found across LlamaIndex's codebase. The vulnerabilities were discovered using AgentGuard v0.6.2, an open-source AI agent security scanning tool. The researcher categorizes these as systemic architectural gaps — not isolated bugs — affecting how autonomous agents handle resource limits, trust boundaries, and behavioral constraints. The findings were reported directly via GitHub Issues to maximize visibility and ensure actionable disclosure to framework maintainers and the broader developer community.

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