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Prompt injection isn't the bug, AI agent frameworks are

Check Point researchers Yarden Porat and Shahar Tal disclosed 11 vulnerabilities across major AI agent frameworks (LangChain, LangGraph, CrewAI, AutoGen, Microsoft Agent Framework, Google ADK), arguing that the real risk is how frameworks handle prompt injection rather than injection itself. Their findings include classic flaw classes—insecure deserialization, SSRF, path traversal, use-after-free—such as a critical checkpoint deserialization bug in Microsoft Agent Framework that allowed remote code execution via poisoned agent state; Microsoft paid a $10,000 bounty and fixed it. Details →

Capability Gates Are Not Authorization: Confused-Deputy Failures in LLM Agent Frameworks

A security research paper, 'Capability Gates Are Not Authorization,' audits LangChain/LangGraph, LlamaIndex, and the Stripe Agent Toolkit and finds that all three provide capability gating by default but none enforce a deterministic fail-closed per-call value authorization gate, enabling classic confused-deputy abuse where an attacker-influenced model emits an unauthorized side-effecting call (e.g., a payout). The authors introduce SCOPEGATE, a five-stage PDP/PEP control (scope, authorization, money ceiling, idempotency, default deny), and report an identical unauthorized payout executing under LangChain's default dispatch but denied by SCOPEGATE, with an available artifact (github.com/raceksd-source/scopegate-runtime). Details →
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