AI in Memory Forensics: Extracting Evidence from Live RAM

When attackers operate in-memory—fileless malware, rootkits, credential theft—traditional forensics often fails. AI-driven memory forensics helps investigators uncover volatile evidence hidden deep inside RAM.

• Detection of Fileless Malware
  AI identifies suspicious processes, injected code, and abnormal memory regions that indicate fileless or in-memory attacks.

• Process & Thread Analysis
  Machine learning examines process hierarchies, thread behavior, and API call patterns to spot malicious activity that blends in with normal OS operations.

• Automatic Artifact Extraction
  AI recovers encryption keys, chat fragments, login tokens, clipboard data, and volatile artifacts before they disappear.

• Rootkit & Stealth Technique Exposure
  AI detects hidden processes, kernel manipulations, and hooks that attackers use to stay invisible.

• Timeline Reconstruction
  By analyzing memory dumps, AI rebuilds sequences of events—commands executed, sessions opened, credentials accessed—to understand the attack flow.

🔹 Bottom Line: AI strengthens memory forensics by exposing stealthy threats, analyzing complex RAM data, and uncovering evidence traditional tools often miss.