#binary-analysis News & Analysis

4 articles tagged with #binary-analysis. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

4 articles

AIBearisharXiv – CS AI · Jun 17/10

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Automatically Attacking Software Reverse Engineering AI Agents

Researchers demonstrate a novel adversarial attack using genetic algorithm-based prompt injection that can deceive LLM-powered reverse engineering tools like GhidraMCP into misinterpreting binary executables. This vulnerability exploits how large language models process decompiled code through surreptitious string variable assignments, potentially allowing malware to bypass automated detection systems that rely on AI-driven analysis.

AIBearisharXiv – CS AI · Jun 17/10

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Investigating Detection and Obfuscation of Prompt Injection Attacks Against Software Reverse Engineering AI Agents

Researchers have demonstrated that agentic AI systems used for software reverse engineering are vulnerable to prompt injection attacks embedded in executable binaries, and have developed both offensive obfuscation techniques and defensive detection methods. This research highlights critical security gaps in AI-powered code analysis tools that organizations are beginning to deploy in production environments.

AIBullisharXiv – CS AI · Jun 46/10

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MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments

MimeLens is a new BERT-based machine learning model designed to classify file types from binary fragments at any position within a file, without requiring file headers or complete files. It outperforms Google's Magika on standard benchmarks and uniquely handles use cases like packet inspection and forensic recovery where Magika fails.

🏢 Hugging Face

AINeutralarXiv – CS AI · Jun 26/10

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Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research

Researchers present Symbolicate-Enrich-Sample, a batch pipeline that uses LLM assistance to prioritize vulnerability research targets across millions of Windows functions. By combining symbol recovery, structural analysis, and language model reasoning, the system reduces 7.2 million functions to a manageable 22,000-function shortlist for security analysis.