Researchers have developed an adversarial machine learning algorithm to improve detection of malicious JavaScript code by using large language models to rewrite it. Unlike off-the-shelf obfuscation tools, which create obvious changes that can be detected, the tool creates changes that look natural and are harder to detect. Retraining deep learning-based detectors on adversarially generated samples improved their performance by 10%. The researchers warn that while detecting malware becomes challenging as it evolves, using similar tactics to rewrite such code can aid in improving machine learning models.
Cisco SNMP Vulnerability Actively Exploited to Install Linux Rootkits
Cybersecurity researchers at Trend Micro have discovered an active attack campaign dubbed “Operation Zero Disco” that exploits a critical vulnerability in Cisco’s Simple Network Management
