AgentHound is an open-source red team framework designed to test the security of modern AI agent infrastructure. It automates the full offensive lifecycle including reconnaissance, credential looting, prompt and model manipulation, and configuration attacks across MCP servers, A2A agents, inference platforms, vector stores, and related tools. Results are visualized as attack paths in a Neo4j graph, helping security teams understand and remediate risks in agentic systems.
In the Developer Tools space, AgentHound takes a focused approach. Manually testing and mapping attack paths across complex AI agent infrastructure stacks. It is built as an open-source project for red teamers. The project is open source (Apache-2.0). It ships for the command line, and it can be self-hosted.
It is developed by Adithyan AK, and it first shipped in 2026. The project is developed in the open on GitHub with 125 stars and 247 commits in the last 90 days. Key capabilities include Attack Path Mapping, Neo4j Graph Output, and Credential Looting. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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