# investigation
16 articlestagged with “investigation”
Attack Attribution Techniques
Techniques for attributing AI attacks to specific actors including behavioral analysis, infrastructure tracking, and technique fingerprinting.
Attribution of AI Attacks
Techniques for attributing AI attacks to threat actors based on attack patterns and indicators.
Cross-System Attack Correlation
Correlating attack indicators across multiple AI systems and traditional IT infrastructure to identify coordinated campaigns and lateral movement.
Data Breach Investigation for AI Systems
Investigating data breaches involving AI systems including training data exposure, model memorization exploitation, and embedding inversion attacks.
Evidence Analysis Techniques for AI Incidents
Advanced techniques for analyzing evidence from AI security incidents including log correlation, model behavior analysis, and artifact examination.
Forensic Tooling for AI Systems
Overview of forensic tools and techniques specifically designed for AI system investigation including model analyzers, log parsers, and behavior profilers.
AI Forensics & Incident Response
Overview of forensic investigation and incident response for AI systems: why traditional IR falls short, the AI incident lifecycle, and the unique challenges of non-deterministic systems.
Prompt Log Forensics
Forensic investigation of prompt and completion logs: reconstructing attack chains, identifying injection sources, correlating prompts with outcomes, and building attack timelines.
Tool Call Forensics
Forensic investigation of agent tool calls: detecting unauthorized tool usage, analyzing parameter manipulation evidence, identifying exfiltration traces, and reconstructing agent action chains.
Model Behavior Forensics (Ai Forensics Ir)
Overview of model forensics: determining if a model has been tampered with, behavioral analysis methodology, and the relationship between model artifacts and observable behavior.
Prompt Injection Forensics
Forensic investigation techniques for prompt injection incidents including log analysis and payload reconstruction.
September 2026: Incident Response Challenge
Investigate simulated AI security incidents from logs, artifacts, and system traces. Reconstruct attack timelines, identify root causes, and write incident reports.
Lab: AI Incident Investigation
Investigate logs and artifacts from a compromised AI system to reconstruct the attack chain, identify the vulnerability exploited, and determine the scope of the breach.
CTF: AI Forensics Investigation
Analyze logs, model outputs, and system artifacts to reconstruct an AI security incident. Develop forensic analysis skills for AI-specific attack patterns, data exfiltration traces, and adversarial prompt detection.
Simulation: AI Supply Chain Attack Investigation
Investigate and respond to a supply chain compromise affecting an AI system's model weights, training data pipeline, and third-party dependencies.
Incident Response Playbook for AI Security Breaches
Walkthrough for building an incident response playbook tailored to AI security breaches, covering detection triggers, triage procedures, containment strategies, investigation workflows, remediation validation, and post-incident review processes.