Trust boundary review
Read the workflow, find untrusted inputs, and map the systems the agent touches.
Five-day AI agent security bootcamp
We train teams to scope deployed AI workflows, test agent failure modes, build controls, and prove readiness to a client security review board.
Course description
Companies now place AI agents inside real workflows, where they read records, draft replies, and write to other systems. This course teaches AI FDSE skills: model the threats, scope access, add controls, watch production behavior, and give reviewers the evidence they need.
Read the workflow, find untrusted inputs, and map the systems the agent touches.
Run direct and indirect injection, privilege escalation, and exfiltration tests.
Build least privilege maps, approval gates, output checks, and sandbox boundaries.
Use logs, evals, incident response, and compliance mapping to prove readiness.
Course schedule
Learner outcomes
A trust boundary map for the agent, its inputs, tools, data, and authority.
A least privilege service-account map with allowed fields, denied fields, and proof of denial.
A set of attack cases that runs beside accuracy evals and catches regressions.
A control package with logs, findings, eval results, and review-board talking points.
Who it is for
Best fit for learners with working AI knowledge, Python environment comfort, cybersecurity fundamentals, and enterprise context.
Bring one real workflow from your job that you would like to secure. Expect hands-on work between sessions as each deliverable builds on the last.
Instructor
Dean Bushmiller has taught cybersecurity since 1999 and has taught continuously online since 2007. He consults on cybersecurity, incident response, and penetration testing, and he now uses AI to build and secure learning platforms.
Bring FDSE training to your team