PRO · AI REPAIR

From finding to verified PR — in 10 seconds.

Claude reads the vulnerable code, drafts a patch, runs your tests in a sandbox, re-scans for safety, and opens a GitHub PR. You review and merge.

Try AI Repair →Read the docs →
10s
average resolution
95%
AI fix success rate
25
languages supported
0
data retained

Five stages, fully automated

  1. 1
    Context
    Vulnerable code slice + similar CVE patches retrieved from RAG.
  2. 2
    Generate
    Claude generates a fix with a step-by-step reasoning trace.
  3. 3
    Sandbox
    Docker (--network none --read-only --cap-drop ALL) runs your tests.
  4. 4
    Re-scan
    Confirms the patch doesn't introduce new vulnerabilities.
  5. 5
    PR
    Confidence score (0–100) plus a fully-formed GitHub Pull Request.

Built for production

Sandboxed by default

Generated patches never touch your infra. Tests run inside a network-isolated, read-only Docker container with all Linux capabilities dropped.

Confidence-scored

Every PR carries a 0–100 score combining test pass rate, re-scan safety, breaking-change risk, and CVE patch reference quality. Review what matters.

Reasoning trace, exposed

We show you why Claude made each change. The full step-by-step reasoning is attached to the PR — no black boxes.

Ready to ship clean code?

Connect your repo — we'll handle the rest.

Get started →