Private AI for smart contract security teams

Audit intelligence that works inside your security practice.

VulnautAI builds isolated AI systems for Web3 auditors: trained on vetted vulnerability knowledge, adapted to your methodology, and deployed where your client data stays under your control.

Context enriched Paths ranked Findings verified Report ready
Private
Client-isolated models
EVM
Audit-focused reasoning
Security audit dashboard showing code review panes, vulnerability traces, and benchmark cards
Finding triage ranked by exploit path confidence

The tool in practice

Review ranked findings, pipeline stages, and evidence in one audit workspace.

VulnautAI presents confirmed findings, inconclusive cases, rejected candidates, diagrams, deep dives, and PoC test work in a reviewer-friendly interface built for security teams.

VulnautAI security audit interface showing pipeline stages, confirmed findings, and export controls

Built for auditors, not generic chat

From vulnerability signal to review-ready evidence.

The platform is designed around how security firms actually work: private client context, repeatable methodology, explainable finding evidence, and measurable model performance.

01

Private model rooms

Dedicated environments for each firm keep methodology, audit reports, and client material isolated throughout tuning, evaluation, and deployment.

02

Evidence-first findings

Outputs are structured around exploit path, affected code, impact, assumptions, and remediation notes so auditors can review instead of rewrite.

03

Benchmark ledger

Model releases are compared against public EVM audit tasks and peer systems so performance claims stay tied to visible measurements.

A practical deployment path

Ship a private audit assistant without changing your review culture.

VulnautAI can start as a contained evaluation, then expand into internal tooling once your team trusts the output quality and governance model.

  1. 1

    Baseline evaluation

    Run representative contracts and historical findings through the foundation model to establish precision, recall, and reviewer effort.

  2. 2

    Confidential adaptation

    Fine-tune or retrieve against your approved reports, templates, and methodology docs in a dedicated environment.

  3. 3

    Controlled rollout

    Deploy through API, internal UI, IDE workflow, or private cloud with access controls, logging, and review gates.

Latest public comparison

Vulnaut leads the listed EVMBench audit comparison at 83%.

See the full comparison, release notes, and supporting benchmark links on the new benchmarks page.

Vulnaut 83.0%
Nethermind AuditAgent 67.0%
Guardix 64.2%
Claude Opus 4.6 45.6%
Open benchmark report

Security posture

Designed for confidential audit work.

Security firms carry client source code, embargoed findings, and proprietary review methods. VulnautAI treats that context as the product boundary.

Data separation

Client material is scoped to dedicated projects and kept out of shared training flows unless explicitly approved.

Deployment control

Support for private cloud or firm-controlled environments keeps access, logs, and retention aligned with internal policy.

Reviewer accountability

Findings stay traceable to code paths, assumptions, and model outputs so senior auditors can approve with context.

Get started

Evaluate VulnautAI against the contracts your team actually audits.

Send a confidential inquiry or book a short demo to discuss private deployment, benchmark methodology, and integration options.