Independent Security Audit

Your code. Ten models.
One consensus.

Run the same source code against 10+ frontier LLMs simultaneously. Each produces an independent audit report. A scorer compiles a cross-model consensus analysis with a publishable scorecard.


How it works

1

Upload

Point the tool at your source directory. It concatenates, hashes, and builds a structured audit prompt with a security checklist tailored to your language and domain.

2

Audit

The prompt is sent to 10+ frontier models in parallel — Claude, Gemini, GPT, Grok, Llama, Qwen, DeepSeek, Kimi, Codestral, MiniMax. Each audits independently.

3

Score

Findings are cross-referenced. A consensus-weighted scoring system discounts single-model hallucinations and amplifies real issues flagged by multiple models.


Scoring methodology

Each finding's severity is cross-referenced with the number of models that independently identified it. The penalty table:

Severity 1 model 2–3 4–6 7+
Critical12244060
High6122030
Medium361015
Low1235
Info0000

Score = 100 − Σ(penalties). A single model flagging CRITICAL costs only 12 points. Seven models flagging it costs 60. Anti-hallucination by design.


Rating bands

A+ 95–100 Exemplary
A 85–94 Strong
B 70–84 Acceptable
C 50–69 Concerns
D 25–49 Significant issues
F 0–24 Not recommended

Auditing panel

Reports are produced by independent frontier models from vendors across three continents. No vendor grades itself.

Grok 4.3xAI
Claude Opus 4.7Anthropic
Gemini 3.1 ProGoogle
GPT-5.5 ProOpenAI
Llama 4 MaverickMeta
Qwen 3.6 PlusAlibaba
MiniMax M2.7MiniMax
Kimi K2.6Moonshot
Codestral 2508Mistral
DeepSeek V4DeepSeek