Commoditized AI Vulnerability Scanning for Everyone

P6/10April 11, 2026

WhatA platform that runs cheap, small open-weight models against codebases to find security vulnerabilities at a fraction of the cost of frontier models.

SignalThe core finding is that small, cheap models (down to 3.6B parameters at $0.11/M tokens) can replicate much of the vulnerability detection that expensive frontier models achieve, suggesting the tooling and harness matter more than raw model capability.

Why NowOpen-weight models have crossed a capability threshold where they can perform meaningful security analysis, and the cost difference versus frontier models (100-1000x cheaper) makes continuous scanning economically viable for the first time.

MarketEvery software company with a codebase — from startups to enterprises. Security scanning TAM is $15B+ and growing 15% annually. Competes with Snyk, Semgrep, but the AI-native approach at commodity pricing is a gap.

MoatThe harness/scaffolding IP — how you chunk code, orchestrate multi-model analysis, and filter false positives — is the real defensibility, not the model itself. First mover who nails the pipeline builds a proprietary benchmark dataset of validated findings.

Small models also found the vulnerabilities that Mythos found View discussion ↗ · Article ↗ · 1,153 pts · April 11, 2026

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