AI Security Monitoring and Incident Response Course (Self-Paced)
IDCYSE8014SP

Self-paced online training with expert support

An AI system can be compromised without anyone touching the server it runs on. This course teaches federal staff what to watch for, how to tell a real AI incident from a performance blip, and what to do in the first hour when one happens.

$799 8 clock hours Live Support Start anytime

This course includes

  • 8 hours of project-based training from experts
  • Answers from real instructors
  • Retake for free within 1 year
  • Verified digital certificate of completion
  • Learn at an accredited institution

This is the self-paced version. For live instruction, enroll in AI Security Monitoring and Incident Response Course.

A focused, practitioner-level course on the two things traditional IT monitoring and incident response do not cover well for AI systems: knowing what a compromise looks like, and knowing what to do about it. The framing that makes it work is that an AI system inherits every traditional attack surface and then adds new ones tied to data, models and inference behavior — an attacker can manipulate what a model learns from, or what it sees at run time, without ever reaching the infrastructure. Monitoring therefore has to move from "is the system running" to "is the system behaving the way it is supposed to, on data it is supposed to see, for the purposes it was approved for."

The practical core is a signals table that maps observed patterns to likely causes, paired with the first-hour triage sequence. A sustained spike in near-identical unusual inputs reads as adversarial probing; a slow accuracy decline reads as drift; an unexplained query spike from one credential reads as an extraction attempt. From there the course turns to judgment — separating anomalies from incidents, preserving the evidence responders routinely lose (model version in use, surrounding prompt and response logs, training data lineage, guardrail configuration in effect), and classifying severity by impact rather than technical complexity. Its sharpest teaching point: an incorrect benefits determination caused by a data integrity failure is a high-severity incident even though nothing technically broke. The final module applies the four-phase incident response lifecycle with containment actions specific to AI, including model rollback to a validated version, disabling automated decision-making in favor of human review, quarantining a compromised training data source, and closing a confirmed prompt injection vector. It sits deliberately downstream of AI Security & Governance for Government Course (Self-Paced), which covers the governance landscape this course does not repeat.

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Since 1921, Graduate School USA has partnered with over 125 federal agencies and trained more than one million federal employees. Led by instructors with deep, real-world knowledge of federal regulations, policies, and practices, our private group programs are practical, mission-driven, and tailored to your agency’s objectives. We offer expertise across key federal domains—including human resources, financial management, acquisition and contracting, leadership, and more—to deliver training where and how your team needs it.

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