New Archestra’s OpenAPPA Saturates Two Major Security Benchmarks with a 0% Attack Success Rate
infoq.com Oct 4, 2026

New Archestra’s OpenAPPA Saturates Two Major Security Benchmarks with a 0% Attack Success Rate

AI-summarised brief · reviewed before publication

New Archestra has launched OpenAPPA, an open‑source security engine that operates outside an AI agent’s prompt and execution loop to prevent data exfiltration from prompt injection and model hallucination. The system defines data sources, audiences, trust levels and authorities, then enforces deterministic security rules. In benchmark testing, OpenAPPA achieved a 0 % attack success rate on the Bench‑Corp suite of 20 multi‑step enterprise workflows and on the AgentThreatBench, outperforming Claude Code’s auto mode (10 % success) and Microsoft FIDES (31 %). The developers argue that stochastic, classifier‑based approaches suffer from approval fatigue and cannot reliably track data across tool calls, leading to breaches even at high accuracy levels. OpenAPPA’s deterministic model aims to eliminate these gaps while preserving agent utility.

💡 Why It Matters

  • · By demonstrating flawless defense in leading security benchmarks, OpenAPPA proves that deterministic policy enforcement can reliably safeguard AI agents without the false‑positive overload that hampers current probabilistic solutions.