Course · 5 chapters
Adversarial AI
Ship LLM features that survive attack. Defend against prompt injection, context poisoning, and jailbreaks, then run an internal red-team program. 5 chapters, advanced, for engineers.
What you'll be able to do
- Defend LLM features against prompt injection
- Harden AI agents against data poisoning
- Automate jailbreak testing with DeepTeam
- Run proven attack algorithms like PAIR
- Turn attack discovery into cheap CI gates
- Run an internal AI red-team program
What's inside
- 1Adversarial AI: Start Here
Orientation across the four-chapter Adversarial AI skill path — defender → threat-surface → offense → program — covering everything from your first prompt-injection patch to running an internal red-team practice
- 2Prompt Injection Defense Foundations
Why prompt injection exists, how attackers exploit it, and the layered defense every LLM-powered feature needs before shipping
- 3Context Poisoning & Indirect Injection
Map and defend the agent-era attack surface — RAG poisoning, document-borne payloads, memory poisoning, and tool-output hijacking that direct-injection defenses don't reach
- 4Automated Jailbreak Tooling
Stand up automated offensive tooling for AI red-teaming — DeepTeam, PyRIT, Mindgard; attacker LRMs and BYO-attacker pattern; PAIR, TAP, GCG algorithms; and trajectory caching that turns expensive discovery into cheap CI gates
- 5AI Red Teaming & Adversarial Evaluation
Run a red-team program for production AI — taxonomy, the finding lifecycle, runtime monitoring, alignment regression, and the internal playbook
Frequently asked questions
- What will I learn in this adversarial AI course?
- You learn to defend and attack LLM-powered systems: patching prompt injection with defense-in-depth, blocking context poisoning and indirect injection across RAG and agents, running automated jailbreak tooling, and operating an internal AI red-team program. The path spans five chapters across the defender, threat-surface, offense, and program stages.
- Who is this AI security path for?
- It is built for engineers shipping production LLM features and the security teams that test them. The level is advanced, so it assumes you already work with LLM apps, agents, or RAG pipelines.
- Do I need coding experience or prior AI security knowledge?
- Yes. This is an advanced engineering path, so you should be comfortable building LLM features and reading code. It uses offensive tools like PyRIT, DeepTeam, and Mindgard, so familiarity with running Python tooling helps.
- How long does the Adversarial AI course take and is there a certificate?
- The path runs about 100 minutes across five chapters, including a short orientation chapter. You earn a completion certificate once you finish every chapter.
- Is this course free?
- No. Adversarial AI is a paid path included with AI Academy by Anthropos. It covers prompt injection defense, context poisoning, automated jailbreak tooling, and AI red teaming.
Earn a certificate
Complete all chapters to receive your certificate of completion.