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AI CURATED HOT STORY · 10/15/2026

Archestra Releases OpenAPPA: Deterministic Security Engine Blocks Agent Data Leaks with Zero Attack Success Rate

1 reports archived1 independent sourcesupdated 10/15/2026, 17:45:57
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Archestra released OpenAPPA, an open-source security engine that enforces data access controls via deterministic rules outside the agent execution loop to prevent leaks from prompt injection and hallucinations. It achieved a 0% attack success rate in Bench-Corp and AgentThreatBench tests, outperforming Claude Auto-Mode (10%) and Microsoft FIDES (31%). The solution replaces probabilistic classifiers with formal algebra to address policy failures caused by approval fatigue in automated review models.

LATEST/Archestra released OpenAPPA, an open-source security engine that enforces data access controls via deterministic rules outside the agent execution loop to prevent leaks from prompt injection and hallucinations. It achieved a 0% attack success rate in Bench-Corp and AgentThreatBench tests, outperforming Claude Auto-Mode (10%) and Microsoft FIDES (31%). The solution replaces probabilistic classifiers with formal algebra to address policy failures caused by approval fatigue in automated review models.

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Total 1 reports · Latest first
  1. InfoQ 中文T2·78 pts
    • Uses deterministic rules instead of probabilistic models for enforcement, architecturally avoiding policy vulnerabilities caused by model hallucinations.
    • Achieved a 0% attack success rate in two authoritative agent security benchmarks, significantly outperforming mainstream commercial solutions.
    • Supports cross-tool call data flow tracking, specifically addressing automated review failures due to approval fatigue.