VulnVerify Skills

VulnVerify Skills helps AI agents verify findings in website and web application vulnerability reports from penetration testing and bug hunting. Reports may come from agentic AI workflows, manual testing, or a combination of both. VulnVerify provides a verification pass to determine whether each reported finding is supported by evidence, is a false positive, or needs more information, and to prepare minimal proofs of concept in authorized systems.

It supports OpenCode, OpenAI Codex, and Claude Code through their native skill mechanisms, including their existing VS Code integrations. The project version is recorded in VERSION.

The project adapts selected Trail of Bits skills with source-optional evidence handling and three explicit verdicts. It is a set of agent instructions, not a scanner or an automatic guarantee of correctness. Review tested compatibility and limitations before relying on an assessment.

What VulnVerify adds

VulnVerify combines the adapted Trail of Bits methodology with a portable report-to-verification workflow:

• Direct browser verification through Playwright MCP. When browser testing is relevant and authorized, the agent can navigate the permitted application, interact with its actual forms and pages, deliver the reported trigger, and compare the observed result with suitable controls. Screenshots, page snapshots, and relevant console/network output can support the verdict.
• A connected evidence workflow. Report intake, seven-brocard triage, standard/deep technical analysis, PoC reproduction, and six-gate review carry the same claim and evidence through to the final decision.
• Report-driven verification. Start with existing pentest or bug-hunting findings in PDF, JSON, or Markdown, subject to the host’s reading capabilities. Correlate supplied requests, responses, screenshots, source excerpts, configuration, and runtime evidence to assess the exact claimed behavior.
• Three explicit outcomes. Confirmed, False Positive, and Inconclusive keep missing evidence or an unavailable environment from becoming an unsupported dismissal. The assessment separates reported behavior, actual observations, and unverified internal causes.
• One methodology across three clients. The same canonical skill files serve OpenCode, Codex, and Claude Code, with client-specific setup kept in the integration layer.

For example, a report may claim that an input executes JavaScript in a web page. With an available Playwright MCP connection and explicit target/action scope, the agent can submit the reported input through the real form, observe its effect, and compare benign input or another appropriate control. The verdict must explain whether that exact delivery path and claimed security impact were established. Browser execution remains conditional on access, setup, and