0sec Labs open-sourced an AI security harness that automates vulnerability investigations and code reviews, allowing developers to integrate their own LLMs for enhanced software security.
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Zurich-based 0sec Labs has released 0, an open-source AI security harness. It runs vulnerability investigations, code review, pentesting, reverse engineering and fix generation. Developers drive it from a local browser console, a headless CLI or an MCP server. The 0sec Labs open-source AI security harness is licensed MIT OR Apache-2.0 and ships as a research preview. TL;DR Wrapper: It is a software harness. Bring your own LLM from 14 listed providers. Runs on: Apple Silicon macOS, x64 or ARM64 Linux, or the ghcr.io/0sec-labs/0 container. No GPU needed. Model inference runs at your provider. Performance: Strong self-reported CTF scores, plus a public record of upstream Linux kernel fixes. Best: 93/95 (97.9%) on XBOW web CTFs, gpt-5.4 cohort, any-success grouping. Worst: Black-box-only XBOW union of 81/104 (77.9%). A 2026 cold run scored 45/104 (43.3%). Bottom line: Best: one harness spans web, source, packages, binaries and kernels. Worst: headline scores are self-reported and not pass@1. What is 0 from 0sec Labs? 0 is a control plane around LLMs and security tools. It is not a model. You plug in a provider, and 0 runs scoped workflows against authorized targets. The research team describes it as a self-evolving, multi-model harness. 0sec Labs is backed by Y Combinator. How does the 0 harness work? The architecture docs state one rule: reproduce before trusting. Agentic scans follow a conceptual pipeline: Plan, Discover, Attack: a research agent picks vulnerability classes, maps endpoints and tests hypotheses. Triage: filters remove weak findings and check evidence completeness. Verify: a separate session re-exercises each candidate, with 5 turns per finding. Report: outputs include HTML, PDF, SARIF, Markdown and JSON. Web pentesting is shell-first. The agent uses bash with curl, python3 and sqlmap, not a fixed HTTP tool set. Evidence carries a proof grade from candidate to impact-proven. Compiled targets go through 0verse, a separate in-repo eng
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