AI Could Generate 10,000 Malware Variants, Evading Detection in 88% of Case
Dec 23, 2024
Machine Learning / Threat Analysis
Cybersecurity researchers have found that it's possible to use large language models (LLMs) to generate new variants of malicious JavaScript code at scale in a manner that can better evade detection. "Although LLMs struggle to create malware from scratch, criminals can easily use them to rewrite or obfuscate existing malware, making it harder to detect," Palo Alto Networks Unit 42 researchers said in a new analysis. "Criminals can prompt LLMs to perform transformations that are much more natural-looking, which makes detecting this malware more challenging." With enough transformations over time, the approach could have the advantage of degrading the performance of malware classification systems, tricking them into believing that a piece of nefarious code is actually benign. While LLM providers have increasingly enforced security guardrails to prevent them from going off the rails and producing unintended output, bad actors have advertised tools like WormGPT...