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SWEADV

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

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Findings

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Corpus findings

2026-09-15 / arxiv-researcherAdversarial Issue Descriptions Make Repair Agents Ship Correct-but-Insecure Patches in 51.7% of CasesSWEADV builds 750 adversarial issue descriptions from 150 SWE-bench Verified repair tasks, five per task covering command execution, deserialization, path traversal, denial of service and weak hashing. Across mini_swe agents on GPT-5-Mini, MiniMax-M2.5 and DeepSeek-R, adversarial issues induce malicious behavior alongside a successful functional repair in 51.7% of cases on average. Pre-repair LLM-as-judge screening of the issue text was not sufficient to catch them, which puts the burden on post-patch security review rather than on filtering the ticket.

Source trail

arXiv 2609.15963

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