Attack your own AI before someone else does.
Learn the attacker's playbook for AI, then use it to defend. Every course runs attacks on a practice company, then has you catch them and fix them, with numbers to show for it.
The ways AI gets attacked are already written down
Prompt injection is risk number one
Hidden instructions that trick an AI into ignoring its rules are first on the OWASP Top 10 for LLM Applications 2025.
Source: OWASP Top 10 for LLM Applications 2025AI that can act can be made to act
Giving an AI tools and permissions it should not use alone is on the same list, as Excessive Agency. Agents make this everyone's problem.
Source: OWASP Top 10 for LLM Applications 2025The supply chain is a way in
Models, packages and plugins you did not write are on the list too, as Supply Chain. One bad update reaches every app that uses it.
Source: OWASP Top 10 for LLM Applications 2025Four steps, from breaking your AI to running the program
Attack it
3 coursesFor testers and builders who need to see how their AI breaks before an attacker does.
- Prompt Injection & Jailbreak DefenceAttack a practice assistant, then add defences and count what still gets through.Intermediate
- Red, Blue & Purple: Ethical Hacking for Your OrganizationRun an authorised red, blue and purple test that finds your gaps and proves your detections work.Intermediate
- Red-Team Your AI AgentTest a practice claims agent that can act, add rules for each tool, and count attacks stopped and real work still done.Advanced
Catch it
2 coursesFor security teams who need to spot an attack while it happens.
Fix it
2 coursesFor the developers and product owners who build AI into your products.
Lead it
2 coursesFor security leaders, risk owners and the people who answer to the board.
The attacker's method, used for defence
No course hands you a working attack to use elsewhere. You learn what each attack is, watch it work on a practice target, and leave with the defence and the evidence.
See the attack work
Each course runs attacks against a made-up practice company, so you see what an attacker would do without touching a real system.
Catch it
You find the attack in the logs and the test results, and you write the check that would have caught it.
Fix it and prove it
You add the defence, run the attacks again and count what still gets through. That count is your evidence.
Find out how your AI breaks, on your terms
Tell us what AI you build or use. We will suggest the courses to start with.