prompt
FreeHybrid AI-agent vulnerability scanner prompt for large codebases
FreeFree tier
About prompt
A specialized prompt designed for configuring an AI agent to act as an architect and operator of a hybrid vulnerability scanning system. It combines fast, wide-coverage regex matchers (SCAN phase) with deep, expensive AI-agent analysis (PROCESS phase) and an adversarial false-positive reduction pass (REVALIDATE phase). The prompt details a three-phase pipeline optimized for large monorepos and mixed-tech codebases, aiming to surface vulnerabilities that traditional SAST tools miss while controlling inference costs.
Key Features
Three-phase scanning pipeline: SCAN (regex), PROCESS (AI agent), REVALIDATE (adversarial)
Tech-gated regex matchers activated by sentinel files or lockfiles
Structured JSON output per file with line ranges and match context
AI-agent analysis with exploitability, trust-boundary, and data-flow evaluation
Second AI pass for false-positive reduction with explicit skepticism prompt
Parallelizable and resumable runs for large codebases
Targeted detection based on codebase trust model and tech stack
Pros & Cons
Pros
- Combines speed of regex with depth of AI for wide coverage and deep analysis
- Explicit cost-quality trade-off design keeps AI costs under control
- Revalidation pass reduces false positives significantly
- Tech-gated matchers avoid irrelevant scan patterns
- Structured output easy to integrate into CI/CD pipelines
Cons
- Requires AI agent SDK (e.g., Claude or Codex) and associated API costs
- Relies on careful configuration and custom matchers for optimal results
- Accepts that some false negatives are preferable to false positives, potentially missing true vulnerabilities
- Not a standalone tool; depends on the prompt being used with a capable AI agent
Best For
Scanning monorepos and large codebases with mixed technology stacksFinding vulnerabilities that traditional SAST tools miss in production pipelinesCost-sensitive vulnerability hunting where AI inference spend must yield measurable security valueSecurity audit workflows requiring low false-positive rates through revalidation gates
FAQ
What is the overall architecture of the scanner described in the prompt?
The prompt defines a three-phase pipeline: SCAN (fast deterministic regex sweep), PROCESS (deep AI-agent analysis with context), and REVALIDATE (adversarial false-positive reduction).
How does the prompt control AI inference costs?
By keeping the SCAN phase cheap (no LLM calls), batching context for AI analysis, and only using AI for candidates flagged by regex. The REVALIDATE pass is limited to HIGH and CRITICAL findings.
What types of vulnerabilities does the prompt target?
Common CWE shapes such as SQL injection, SSRF, path traversal, and unsafe deserialization, but detection is tech-gated and adapted to the codebase's trust model and stack.