Malware authors are creating payloads, such as the macOS.Gaslight sample linked to North Korean threat actors, that contain specific code commands designed to cause LLM-assisted security analysis tools to abort or refuse analysis, thereby evading detection. This is part of a growing trend of threats specifically engineered to subvert AI-powered security defenses, as previously documented by other security firms. Security professionals are advised that AI-supported protection is not infallible and should expect more samples exploiting this vector as LLM-assisted analysis becomes routine.
Enterprises that have turned to AI in order to boost their security defenses may have to reconsider their approach. Malware containing code that commands LLM-assisted products to abort their analysis or refuse to implement it is already circulating, according to a post from security company SentinelLabs. SentinelLabs thinks it knows who’s responsible for the malware, which attacks MacOS systems. “Apple’s XProtect detects the sample under the rule MACOS_BONZAI_COBUCH, and SentinelLabs associates the BONZAI signature family with North Korean threat activity,” the company wrote. It’s calling the malware macOS.Gaslight. This is not the first example of malware specifically targeting AI-generated analysis. As SentinelLabs noted, Checkpoint first documented such an approach exactly a year ago. And Socket followed suit with a report of a payload that also used code to evade detection by AI models. This new generation of threats was mentioned in the OPSWAT report, The State of File Security and cybersecurity experts are warning that AI-supported protection is not always the answer. SentinelLabs would certainly agree with that view. “As LLM-assisted analysis becomes routine, defenders should expect more samples built to exploit it,” it wrote.