Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Kroll identified a cross-platform malware framework, dubbed GARUDA C2, that uses public code-hosting platforms like GitHub for staging, redundancy and command distribution across Windows, macOS and Linux. Analysis links the campaign to an India-based operator supported by Hindi-language development artifacts, build logs, infrastructure indicators and evidence suggesting use of a locally hosted large language model (LLM) to accelerate malware development.

The next phase of Threat Exposure Management by Gayathri Kunapuli.

Enterprise security is confronting an identity problem that has outgrown the tools designed to contain it. For years, the operating model was straightforward, to authenticate users at the gate, grant access and monitor known risks. However, today AI is increasingly interwoven with business practices, making that model no longer fit for purpose.

How Agentic AI Is Outpacing the Compliance Frameworks Built to Contain It.

What recent AI security developments should change and what they should not—for security leaders and vulnerability management teams The question is no longer whether AI will affect vulnerability discovery. It is whether exposure management programs can keep up with a faster clock.

A combination of accelerating risk complexity and increasing attack times is creating a perfect storm for organizations. Responding effectively to this fast-evolving threat landscape demands more advanced capabilities.