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UID:pretalx-hf2026-GNEP7R@cfp.hackfest.ca
DTSTART;TZID=EST:20261030T193000
DTEND;TZID=EST:20261030T202000
DESCRIPTION:Modern IoT firmware is a largely unexplored attack surface\, an
 d manual analysis doesn't scale. In this talk\, we present a pipeline that
  combines core computer science fundamentals with large language models to
  automate vulnerability discovery in firmware binaries.\n\nIn this talk\, 
 we describe how we built a pipeline that combines computer science fundame
 ntals with LLMs to find bugs in firmware. We use LLMs as an operator for d
 etecting vulnerability patterns\, a kind of "vuln smell"\, and walk throug
 h how we built the pipeline using control flow graphs\, Ghidra internals t
 o extract pseudo-C code\, and build taint analyzes pipeline\, and how craf
 ting the right prompts with the right context lets even Gemini Flash detec
 t bugs or at least give meaningful hints\, and of course our pitfalls\, an
 d why LLMs better than fuzzing in case of firmware and MORE.\n\nAttendees 
 will leave with a practical understanding of how to build LLM-assisted bin
 ary analysis pipelines and how prompt engineering decisions directly impac
 t bug-finding accuracy.
DTSTAMP:20261014T080405Z
LOCATION:Track 2 (306A)
SUMMARY:Hacking IoT Firmwares with LLMs - Ravshan Rikhsiev
URL:https://cfp.hackfest.ca/hf2026/talk/GNEP7R/
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