LATIDIA · Ciberseguridad

APEX: Protección activa en los límites de ejecución para agentes LLM

arXiv:2610.06966v1 Announce Type: new Abstract: Indirect prompt injection (IPI) oculta instrucciones contradictorias en el contenido que los agentes del modelo de lenguaje grande (LLM) leen en tiempo de ejecución. A medida que los agentes componen capacidades heterogéneas

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arXiv:2610.06966v1 Announce Type: new Abstract: Indirect prompt injection (IPI) hides adversarial instructions in content that large language model (LLM) agents read at runtime. As agents compose heterogeneous capability units, including Tools, MCP servers, and Skills, the carriers of injection multiply, and defenses built to recognize attack patterns fall behind them. We instead shift defense from covering attack patterns to one stable point: whatever the carrier and however the injection propagates, harm materializes only at the \emph{execution boundary}, where the agent turns internal state into an external action or released output. Safety there turns on two conditions, both settled by the trusted task rather than by the run: whether the proposed