Build an AI Security Vulnerability Scanner
An intelligent security scanner that uses AI agents to discover, analyze, and report vulnerabilities across codebases and web applications, with automated red-teaming and guardrail enforcement.
AI Agent Orchestration
Core agent framework that coordinates scanning tasks, triages findings, and manages multi-step vulnerability analysis workflows
Graph-based agent architecture enables branching scan workflows — static analysis, dynamic testing, and dependency auditing can run as parallel subgraphs with conditional edges for triage
Role-based multi-agent setup lets you define specialized agents (recon agent, exploit validator, report writer) that collaborate on complex vulnerability assessments
Type-safe agent framework ensures structured vulnerability reports with validated severity scores, CVE references, and remediation steps
Web Reconnaissance & Crawling
Automated discovery of attack surfaces by crawling web applications, extracting endpoints, and mapping API schemas for vulnerability testing
LLM-friendly web crawler that extracts clean structured data from target applications — ideal for mapping endpoints, forms, and input vectors before scanning
AI-driven browser automation can interact with authenticated flows, SPAs, and dynamic content that static crawlers miss — critical for testing login bypasses and session handling
Converts entire web applications into structured data, enabling comprehensive sitemap generation and content extraction for thorough attack surface mapping
Code Analysis & Sandboxed Execution
Secure environment for analyzing source code, running exploit proof-of-concepts, and validating vulnerabilities without risk to production systems
Sandboxed execution environments let AI agents safely run exploit PoCs, dependency scanners, and static analysis tools in isolated containers — no risk of lateral damage
Packs entire repositories into LLM-digestible format so the AI agent can perform holistic code review — spot insecure patterns, hardcoded secrets, and injection vectors across the full codebase
AI Safety & Guardrails
Enforces responsible scanning boundaries — prevents the AI from generating actual exploits, limits scope to authorized targets, and validates that outputs follow responsible disclosure standards
Validates AI outputs to ensure scanner recommendations stay within authorized scope — blocks generation of weaponized exploits and enforces responsible disclosure formatting
Programmable safety rails ensure the scanning agent only targets authorized assets, refuses out-of-scope requests, and follows ethical security testing guidelines
Red-teams the scanner's own prompts to prevent prompt injection attacks against the security tool itself — ensures the AI agent cannot be manipulated by malicious target content
Observability & Reporting
Tracks every scanning decision, logs vulnerability findings with full provenance, and generates actionable security reports with severity rankings
Traces every agent step from reconnaissance through validation — provides full audit trail of how each vulnerability was discovered, essential for compliance and reproducibility
AI observability platform that helps evaluate scanner accuracy over time — track false positive rates, missed vulnerabilities, and agent reasoning quality across scan runs