Releasing shortly

Autonomous
vulnerability discovery.

AutoVuln is a long-running cyber-reasoning system for real codebases. It maps attack surfaces, follows dangerous data flows, challenges its own findings, and produces the evidence needed to act.

Join early access Multi-model reasoning
Evidence-led validation

Evidence pipeline / active

01map.attack_surface()ready

02trace.source_to_sink()ready

03challenge.hypothesis()ready

04validate.exploitability()ready

05verify.patch()ready

output → finding + evidence + validation
confidence is earned, not assumed

Open-model intelligence

Diverse reasoning paths reduce dependence on any single model.

DeepSeek V4 Pro

GLM 5.3

Kimi K3

01 / Why AutoVuln

Powered by open models. Verified by evidence.

AutoVuln is being built around explicit hypotheses, code-level evidence, and critical review. Model diversity gives you freedom of choice without locking you into a single model.

Map the real attack surface

Inspect language-aware sources, sinks, trust boundaries, and reachable code paths before prioritising leads.

Challenge every hypothesis

Use adversarial review and multiple reasoning perspectives to test assumptions and reduce fragile conclusions.

Return decision-ready evidence

Every finding is tied to the exact code and marked by how far it has been verified. A convincing AI explanation is never treated as proof.

Early-access request* Required

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Source repository / optional

Public repository: paste its URL. Private repository: submit the URL only. We will arrange access through a read-only GitHub App. Never paste a password, token, SSH key, or other credential.

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Autonomousvulnerability discovery.

Powered by open models. Verified by evidence.

Map the real attack surface

Challenge every hypothesis

Return decision-ready evidence

Be first to put AutoVuln to work.

Autonomous
vulnerability discovery.