Code Audit & Software Supply Chain Security
Problem Statement
Dynamic Application Security Testing (DAST) scanners flag potential web vulnerabilities (e.g., Cross-Site Scripting, SSRF) based solely on HTTP status codes, requiring security engineers to manually write proof-of-concept (PoC) exploit payloads to confirm exploitability.
Goal
Build an agent that receives potential DAST vulnerability leads, synthesizes benign PoC verification payloads, and confirms exploitability without damaging target systems.
Outcome Measurement
- Verification Speed: Proof-of-concept verification completed in under 5 seconds per finding.
- False Positive Elimination: 100% confirmation of exploitable vulnerabilities prior to alerting developers.
How the Code was Built
Generates safe, non-destructive validation payloads to verify parameter reflection or dynamic execution.
Executable Code
from pydantic import BaseModel, Fieldfrom langchain_openai import ChatOpenAIclass DASTVerification(BaseModel): target_url: str vulnerability_type: str poc_payload: str expected_response_indicator: str safety_notes: strdef generate_dast_poc(target_url: str, vuln_type: str, parameter: str) -> DASTVerification: llm = ChatOpenAI(model="gpt-4o", temperature=0) structured_llm = llm.with_structured_output(DASTVerification) prompt = f"Generate a non-destructive verification payload for {vuln_type} on URL '{target_url}' parameter '{parameter}'." return structured_llm.invoke(prompt)if __name__ == "__main__": res = generate_dast_poc("https://app.company.com/profile", "Reflected XSS", "username") print(f"Target: {res.target_url}") print(f"PoC Payload: {res.poc_payload}") print(f"Expected Response Indicator: {res.expected_response_indicator}")
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