The Defender's Advantage Podcast Using LLMs to Analyze Windows Binaries
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Oct 4, 2024 Vicente Diaz, a Threat Intelligence Strategist at VirusTotal, dives into the fascinating world of using large language models (LLMs) for malware analysis. He discusses how Gemini can analyze Windows binaries, enhancing security operations. The conversation touches on the balance of static and dynamic analysis, the challenges of de-obfuscation, and how LLMs can provide critical attribution signals. Diaz also highlights the potential of LLMs to reduce analyst workload, speed triage processes, and assist in comparing malware variants.
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LLMs Turn Code Into Readable Explanations
- LLMs can generate detailed, human-readable descriptions from code, not just create code from descriptions.
- Vicente Diaz found they work well for scripts and can explain intent and red flags quickly.
Augment LLMs With Contextual Signals
- Combine LLM code analysis with aggregated signals and contextual data for better decisions.
- Use function calls to query supplemental info (e.g., VirusTotal APIs) instead of overloading prompts.
Provide Dynamic Results To Improve Static Analysis
- Use static analysis as the base but include dynamic analysis outputs as prompt context for cross-checks.
- Let the model compare static and dynamic findings to flag evasion or missing behaviors.