September 2026 Summaries

A cybersecurity professional recounts responding to a ransomware incident in which nearly all virtual machine disks were encrypted and backups were unavailable or compromised, but an unexpectedly captured memory dump from one hypervisor enabled recovery efforts. Using a frontier AI model alongside cryptographic and forensic knowledge, the responder reverse-engineered the encryptor, identified that it only partially encrypted large files, extracted an in-memory session key, and built a decryptor that restored the disks affected by that specific encryption run, while untouched disk regions allowed further file recovery elsewhere. The incident was traced to an unpatched internet-facing service after attackers had remained in the network for over three weeks, though recovery was incomplete because separate encryption runs used independent keys not present in the available dump. The account argues that AI’s value depends on expert verification rather than acting as a universal multiplier, and advocates pairing AI-assisted detection with narrowly authorized automated response actions, such as memory capture, host isolation, and indicator blocking; it presents Stream.Security’s StreamForce, CloudTwin, and StreamMate AI products as tools intended to provide these capabilities.