Agent Egress Bench: A Test Corpus for AI Agent Egress Security Tools

This article introduces Agent Egress Bench, an open-source test corpus designed to evaluate security tools that monitor traffic between AI agents and external networks. Unlike existing benchmarks that test the LLM itself (e.g., for prompt injection resistance), this corpus tests the network security layer—proxies, firewalls, and MCP wrappers—that should block malicious traffic after a model has already failed or been tricked. The corpus contains 72 test cases across 8 categories, including URL and request body DLP, response injection, and MCP-specific attacks (input scanning, tool poisoning, and chain detection). Each case is a self-contained JSON file with an attack payload and expected verdict. The project includes a validation tool and a runner framework for integrating with any security solution. It is not a leaderboard; each tool publishes its own results. The corpus maps to the OWASP Top 10 for Agentic Applications and is available under an Apache 2.0 license. 

https://pipelab.org/blog/agent-egress-bench-benchmark-corpus

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