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SoK: AI-Augmented Binary Reversing

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arXiv:2606. 17398v1 Announce Type: new Abstract: Binary reversing is fundamental to software understanding, vulnerability discovery, malware investigation, and firmware auditing.

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Authors: Yujeong Kwon, Yiyue Zhang, Shakhzod Yuldoshkhujaev, Kexin Pei, Dokyung Song, Hyungjoon Koo
Released: 2026-06-17 (22d ago)
Topic: Related to current project
Relation to my work: Read next because SoK: AI-Augmented Binary Reversing overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "Only continuous soft prefixes hit both EM axes at once on Qwen-2.5-7B-Instruct: discrete prompt searches split between the alignment objective and the distributional objective, and both discretizations of the soft prefix collapse (MODERATE confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)". Matching terms: under, soft, eval, line, rate, language, model. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2606.17398

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