bb-local-toolkit

To avoid theoretical bug bounty findings, structure your workflow through Recon, Learn, Hunt, Validate, and Report stages with explicit decision gates. Apply validation-first reporting checks like scope verification, reproducibility, and data-leak verification before writing any submission.

A to B bug chaining is a cluster hunting methodology that systematically pivots from an initial bug class into higher-value exploit chains. It uses A to B signal methodology to chain vulnerabilities like IDOR, SSRF, and OAuth/OIDC auth bypasses for greater real-world exploitable impact.

Validate OAuth and OIDC authorization bypass vulnerabilities by enforcing scope checks, verifying reproducibility, confirming data leaks, and framing the severity with CVSS 3.1. Run these validation checks and use provided PoC templates before writing the final report.

Yes, this bug bounty methodology covers LLM and agentic AI security testing scenarios. It includes practical tactics for prompt injection, indirect injection, data exfiltration, tool RCE, and ASI01 through ASI10 vulnerability classes alongside traditional web and API targets.

Yes, the bug bounty toolkit provides OSINT and fingerprinting guidance for source and tech reconnaissance. It includes language-specific greps for identifying dangerous sinks across JavaScript, Python, PHP, Go, Ruby, and Rust codebases during the initial recon phase.

You should kill a bug bounty finding early during the validation phase if it lacks real exploitable impact or fails the 7-Question Gate. The workflow enforces strict decision gates to prevent wasting time on theoretical or low-impact results before report writing.