AI SAST
Traditional SAST tools drown you in false positives. Nurbak's AI static application security testing reasons across your codebase and surfaces the bugs that are actually exploitable. Free scan to start.
Create account and connect GitHubWe never store your code. We only write when you ask for a fix PR.
Instead of flagging every pattern, the agent validates exploitability and ranks the real risks, so triage stops being a chore.
Catches vulnerabilities that span multiple files and the business logic a rules engine can't follow.
Scan on connect or on every pull request, export to Jira, without changing your workflow.
Runs on our own model on ephemeral infra; your code never goes to OpenAI or Anthropic and isn't stored.
Create your account and connect GitHub.
We run our Whitehat model on ephemeral infra.
The agent analyzes code and correlates multi-file findings.
You get exploitability-ranked results with the fix.
Wire it into CI/CD and your Jira on paid plans.
AI SAST is static application security testing driven by an AI agent that reasons about code instead of only matching patterns, which cuts false positives and finds cross-file, business-logic bugs.
A traditional SAST tool matches rules and produces noisy alerts. An AI SAST validates exploitability, correlates findings across files and prioritizes the risks that matter.
Yes. Scan a public GitHub repository for free and see the score and summary. Full reports and CI/CD integration are on paid plans.
No. Nurbak runs its own model on ephemeral infrastructure; your code is deleted after the scan and never reaches OpenAI or Anthropic.
SAST reads your source code, DAST attacks your running app. Each one catches bugs the other cannot see. Here is a practical comparison with IAST and SCA, real examples of what each finds and misses, and a recommended stack for startups and regulated companies.
See how much less noise reasoning-based static analysis produces.
Scan my repo