AI Detection and Response

The evolution of detection and response — and why autonomy became inevitable.

• The Detection and Response LineageAV → EDR → XDR → MDR → AIDR: each generation exists because the last one failed somewhere.Free
• The Economics of Machine SpeedDwell time, breakout time, and why minutes became the unit that matters.
• Anatomy of an AIDR SystemDetection models, confidence thresholds, pre-authorized actions, and the guardrails that make autonomy survivable.

What changes when AI agents do triage, investigation, and hunting alongside analysts.

• Automated Triage and AI-Assisted InvestigationClearing the funnel so humans can do human work.
• Human-in-the-Loop and Automation BiasDividing labor between speed and judgment — and the trap of trusting the confident machine.
• Governing Autonomous ResponseEarned autonomy, action scoping, audit trails, and who signs off.

The same models now arm the attacker — phishing at scale, deepfakes, and AI-accelerated intrusion.

• AI-Powered Social EngineeringWhen every phish is fluent and the voice on the phone is your CEO.
• AI-Accelerated IntrusionFaster recon, adaptive malware, and the democratization of attacker skill.
• Defending Against Automated AdversariesWhat still works when the attacker is also a machine.

AI is now an asset class of its own — and it has a brand-new attack surface.

• Prompt Injection and the LLM Attack SurfaceWhen the data is the exploit.
• Poisoning, Theft, and Model IntegrityAttacks on what the model learned and what the model is worth.
• Governing AI RiskFrameworks, lifecycle thinking, and folding AI into the security program you already run.