Code Scanning for AI Apps: SAST, Secrets, Data

Three engines

What gets caught before production

Each engine covers a failure mode AI code generation is measurably prone to. Together they cover the attack surface a human reviewer skims past at 2,000 generated lines per hour.

SAST. Semgrep

200+ rulesets against injection, auth bypass, unsafe deserialization, path traversal. Tuned for the frameworks AI tools generate: React, FastAPI, Express, Next.js.

Secret detection. GitLeaks

API keys, tokens, connection strings, private keys, in source, config, and history. AI tools love writing credentials into example files; GitLeaks catches them before your pentester does.

SCA. Trivy

CVE scanning across dependencies and containers. AI-generated package.json files routinely pin versions with known vulnerabilities, every import gets checked.

Blocking policies

Severity thresholds you set. Criticals block by default; accepted risks require an owner, a reason, and an expiry, all logged for audit.

Data scanners, the surface everyone skips

Quality, access, and lineage scanning: schema validity, freshness, PII egress without basis, data residency, ungoverned shares. AI risk concentrates in data, not just code.

Agent output, same pipeline

Code and changes produced by AI agents go through identical checks, no separate rules, no unscanned side door.

Built for vibe coding security, the risks of AI-generated code are systemic, so the scanning is systematic, no opt-outs, no unscanned side doors.
Zero-setup, scanning is part of the platform pipeline; there is no scanner to procure, integrate, or forget to run.
Evidence by default, every scan result feeds the compliance layer: vulnerability-management evidence for SOC 2 CC7.1 without extra work.

Every finding here feeds the same record as your compliance evidence, so fixing a vulnerability and proving it to an auditor is one motion. If your team builds with Lovable or Cursor, see how enterprise vibe coding keeps that speed safe.

The problem

Why AI-generated code needs its own security layer

This isn't a claim that AI code is bad. It's a claim that AI code is fast, and unreviewed speed is what security incidents are made of.

Volume outruns review

A developer with Cursor ships 10x the code. Your AppSec team didn't grow 10x. Manual review as the only gate stopped being realistic in 2025.

Confident mistakes

AI-generated code looks right. Hardcoded secrets in example configs, string-built SQL, permissive CORS, plausible code, exploitable patterns.

Invisible dependencies

AI tools import packages the developer never chose. Each one is a supply-chain decision nobody consciously made, until it's scanned.

FAQ

Code security questions

What is vibe coding security?

Vibe coding security is the practice of securing applications built with AI coding tools, scanning the generated code for vulnerabilities, detecting exposed secrets, checking dependencies for CVEs, and gating deployment on the results. It matters because AI tools generate plausible-looking code containing exploitable patterns at a speed manual review can't match.

Which scanners does Clarista use?

Semgrep for static analysis (SAST), Trivy for dependency and container analysis (SCA), and GitLeaks for secret detection. All three run on every build automatically, no configuration, procurement, or CI wiring required.

Can findings block a deployment?

Yes, that's the default. Critical findings stop the deploy until fixed or explicitly risk-accepted by a named owner with a reason and expiry date. Every decision is logged and exportable as audit evidence.

How is this different from running Snyk in CI?

Two ways. First, coverage: CI scanning depends on every repo being wired correctly, forever; Clarista scans everything on the platform with no opt-out. Second, the results feed compliance evidence automatically, the scan and the audit artifact are the same motion.

Does it work with code from Cursor, Claude Code, Lovable, or Bolt?

Yes. Import via Git and the same pipeline applies regardless of which AI tool wrote the code.

Security scanning built for AI-generated code