hayulalab/ssrf-discovery-at-scale-paper

SSRF Discovery at Scale: A Multi-Program Study Using Automated Reconnaissance and — Hayula Research

Hayula AI Lab

Abstract

We present a large-scale automated study of Server-Side Request Forgery (SSRF) vulnerabilities across 23 major bug bounty programs using a structured pipeline combining reconnaissance automation, multi-endpoint probing, response classification, and LLM-enriched analysis via the Saif cybersecurity AI system. Over a two-week period, we probed 23 programs using three standardized SSRF test endpoints — /proxy?url=, /fetch?url=, and /redirect?url= — and classified responses on a five-tier severity sc

Files

File	Description
paper.md	Full paper (Markdown)
README.md	This model card

Citation

@techreport{hayulalab2026ssrfdiscoveryatscale,
    title={SSRF Discovery at Scale: A Multi-Program Study Using Automated Reconnaissance and — Hayula Research},
    author={Hayula AI Lab},
    year={2026},
    url={https://huggingface.co/hayulalab/ssrf-discovery-at-scale-paper}
}

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hayulalab — Open Source AI Research