Security for AI-generated code

Vigil scans your PRs for vulnerabilities that Snyk and Semgrep miss — prompt injection, hardcoded AI keys, and more.

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THE PROBLEM

AI codegen is everywhere. Security tooling hasn't caught up.

Snyk and Semgrep were built for code humans write. They miss the new class of vulnerabilities that LLMs introduce — prompt injection, insecure model context, and hardcoded AI credentials. Vigil was built from day one to catch them, with lower false positives through Claude-powered triage.

WHAT VIGIL CATCHES

The vulnerabilities AI code introduces

vigil · PR scan
CRITICAL

Prompt injection detection

Catches unsanitized user input flowing directly into LLM prompts — the #1 attack surface in AI-powered apps.

└─ api/chat.py:42
prompt = f"Answer: {user_input}"
fix → sanitize + bound prompt context
vigil · PR scan
HIGH

AI API key scanning

Finds hardcoded OpenAI, Anthropic, and Cohere keys committed to your repo before they reach production.

└─ config/settings.py:15
OPENAI_KEY = "sk-proj-..."
fix → use environment variables
vigil · PR scan
HIGH

Inline PR comments

Posts findings directly on the diff line — with fix suggestions, confidence scores, and zero noise.

└─ src/db/users.ts:89
db.query(`SELECT * WHERE id=${id}`)
fix → use parameterized queries
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