Coding agents struggle to infer least-privilege file permissions by omitting needed accesses while granting unused or sensitive ones, but Sufficiency-Tightness Decomposition improves sensitive-task success by up to 15.8% and reduces attacks.
Sok: Trust-authorization mismatch in llm agent interactions
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Error messages in the Model Context Protocol can be systematically mutated across seven dimensions to triple indirect prompt injection success rates, reaching up to 100% compliance on four frontier models.
A synthesis of 247 papers on LLM agent security identifies prompt injection and tool hijacking as dominant threats, notes weakly compositional defenses, and argues for trust boundaries and realistic evaluations.
The Redpanda Agentic Data Plane uses out-of-band metadata channels to enforce data scoping, action constraints, and tamper-proof auditing on autonomous AI agents.
citing papers explorer
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VATS: Exploiting Implicit Authority in Error-Path Injection via Systematic Mutation
Error messages in the Model Context Protocol can be systematically mutated across seven dimensions to triple indirect prompt injection success rates, reaching up to 100% compliance on four frontier models.
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The Importance of Out-of-Band Metadata for Safe Autonomous Agents: The Redpanda Agentic Data Plane
The Redpanda Agentic Data Plane uses out-of-band metadata channels to enforce data scoping, action constraints, and tamper-proof auditing on autonomous AI agents.