BurpSqueezer compresses Burp Suite traffic dumps for LLM-ready AI analysis

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A developer has released BurpSqueezer, an open-source tool that compresses large Burp Suite HTTP traffic captures into compact Markdown reports optimized for AI processing. The tool reduced a 26.7 MB traffic dump to just 35 KB — a 745-fold compression — making it feasible to feed real penetration testing data into large language models that enforce file size limits. BurpSqueezer filters out irrelevant traffic such as CDN requests and maps relationships between API endpoints to preserve meaningful structure. The tool is designed for large, complex HTTP datasets and does not perform any active testing or send requests itself — it only processes already-captured, authorized traffic. The project is available on GitHub and its creator is seeking feedback from web security and API penetration testers.

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