The Automated AI Attacks Playbook: How to Prepare for the Coming Wave

Every AppSec program ends the quarter with a list of things it decided not to fix. That list was defensible for twenty years, because reaching it cost an attacker more than it returned.

Autonomous attackers changed the price, and they are already probing continuously at machine speed. This playbook covers what automation repriced, why the findings you deprioritized are the raw material for the attacks that matter, and what a program has to do about it now.

You'll learn how to:

• Measure the one number that tells you whether your program is gaining or losing (new findings entering against findings closed) and why finding faster than you fix is a throughput problem rather than a detection problem

• See why every serious exploit chain is assembled from findings that individually scored low enough to accept, and why no severity model can rank a combination

• Run the four moves, Discover, Remediate, Validate, Prevent, as one continuous loop instead of four separate initiatives, with a question to put to any vendor at each step

• Follow a 90-day plan in 30-day stages, each with a deliverable: your ratio, your merge rate, and two numbers you can defend to a board