AI Security Platforms Expand From Vulnerability Discovery to Malware Analysis

Security researchers and AI vendors reported rapid progress in applying frontier models to offensive and defensive cybersecurity work, including the discovery of CVE-2025-37899, a remote zero-day in the Linux kernel’s SMB implementation. A published account described using an advanced model to help identify the flaw, while OpenAI's Daybreak and Anthropic's Project Glasswing highlighted broader efforts to build AI systems for cyber operations, vulnerability research, and security workflows.

SentinelLABS added evidence that these systems are moving beyond isolated tasks into sustained investigations, describing an eight-stage benchmark based on reverse engineering fast16, a 2005 Windows sabotage toolkit tied to interference with high-precision solvers used in nuclear-weapons modeling. In that evaluation, GPT-5.6 Sol was reported as the only publicly available model tested that completed the full long-horizon malware-analysis workflow, while other models showed useful point-in-time reasoning but failed to maintain consistency as new evidence forced earlier conclusions to be revised.