Historically, enterprise organizations have not sufficiently monitored their employees' activities within internal business applications. They were essentially (and blindly) trusting their employees.

A UC Berkeley computer scientist is developing mathematical algorithms based on semantics to help detect malicious code in computer viruses. According to an article about the research in Lab Notes, ...

Burlington, Mass. " March 5, 2009 " Veracode Inc., the leading provider of on-demand application security testing solutions, today announced that it has expanded its coverage for detecting backdoors ...

CodeHunter, the Zero Trust for Code security company, today announced it has been named a winner in the Next Gen Behavioral Malware Analysis category of the 2026 Global InfoSec Awards, presented by ...

Threat intelligence-sharing platform VirusTotal has unveiled new research showing how AI can be used by cyber defenders to enhance malware analysis. Through the research, VirusTotal found that AI is ...

Fake Alibaba Labs AI SDKs hosted on PyPI included PyTorch models with infostealer code inside. With support for detecting malicious code inside ML models lacking, expect the technique to spread.

CodeHunter today announced Zero Trust for Code, an emerging new cybersecurity category that determines whether software ...

Generative AI – specifically ChatGPT – should not be considered a reliable resource for detecting vulnerabilities in developed code without crucial expert human oversight. However, machine learning ...

A malicious Python package on PyPI uses Unicode as an obfuscation technique to evade detection while stealing and exfiltrating developers' account credentials and other sensitive data from compromised ...