Google Open-Sources Mantis: A Modular Skills Toolkit That Lets Coding Agents Find, Reproduce and Patch Vulnerabilities
Google open-sourced Mantis, an Apache-2.0 modular skills toolkit that lets AI coding agents find, reproduce, and patch vulnerabilities with sandboxed verification.
Google released Mantis on GitHub under Apache 2.0 as a stack-agnostic set of slash-command skills that chain through the full vulnerability lifecycle: mining version history, building threat models, filtering findings, reproducing bugs in gVisor or network-disabled VMs, assembling exploit chains, patching, and scoring residual risk from 1 to 10. It runs with Gemini CLI, Antigravity CLI, the Google ADK, or comparable agent frameworks, and a supervisor skill (/mantis-meta-agent) can drive the whole loop. Google says the design targets the sub-7 percent true-positive rate of naive AI code scanning, and that its hierarchical summary tree cuts token overhead by over 85 percent. The toolkit is deployable for local and internal evaluation but not yet recommended for production.
- Modular slash-command skills chain discovery, dedupe, sandboxed reproduction, patching, and 1-10 risk scoring.
- Differentiator is grounding: sandboxed reproduction and patch re-attack rather than model confidence alone.
- Hierarchical summary tree reportedly cuts token overhead by over 85 percent.
- Targets sub-7 percent true-positive rates of naive AI code scanning, per Google.
- Apache 2.0, usable locally with Gemini CLI or ADK; not production-ready yet.
From the original article
2 min read at marktechpost.com
Google has open-sourced Mantis, a stack-agnostic toolkit of security review skills for AI coding agents. It runs the full vulnerability lifecycle: sweep the code, filter false positives, reproduce the bug in a sandbox, patch it, re-attack the patch, then score the risk. Apache 2.
By Michal Sutter · marktechpost.com
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