Maven – AI Red Teaming & AI Security Masterclass
Released 8/2026
By Sander Schulhoff – Ran the 1st AI Red Teaming CTF w/ OpenAI
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 14 Lessons ( 11h 42m ) | Size: 2.6 GB
Your AI Systems Are Vulnerable… Learn how to Secure Them!
The #1 AI Red Teaming Course. Taught by HackAPrompt, creators of the 1st AI Red Teaming Competition
Prompt injection attacks are the #1 security vulnerability in AI systems. HackAPrompt’s research helped OpenAI increase their model’s resistance to prompt injections by up to 46%. Our recent research with OpenAI, Anthropic, and Google DeepMind found humans outperform automated AI Red Teaming.
That’s why companies need trained AI Red Teamers, and why we built this course.
Using HackAPrompt, you’ll gain hands-on experience identifying prompt injections, jailbreaks, and adversarial attacks – learning to break AI systems and secure them.
Plus, access recorded hacking sessions with top AI Red Teamers who share their favorite techniques, including
Pliny the Prompter – World’s most renowned AI jailbreaker
Johann Rehberger – Built Microsoft Azure Red Teams
Richard Lundeen – Microsoft AI Red Team Lead
Valen T. – 1st in Anthropic’s Red Teaming competition
& more!
The training prepares you for our AIRTP+ certification exam, which has certified 100’s from Microsoft, Google, Capital One, IBM, ServiceNow, and Walmart.
What you’ll learn
Learn how to uncover AI vulnerabilities, run real attacks, and apply defenses that secure systems in production.
Understand How AI Systems Fail
Learn how prompt injections, jailbreaks, and adversarial inputs actually succeed
Study real model behavior to identify weak points in prompts, context, and integrations
Recognize where traditional security assumptions break down in AI applications
Build Core Red Teaming Skills
Run hands-on attacks in a controlled environment to expose real vulnerabilities
Trace how manipulations happen by analyzing system outputs and behavior
Use red teaming workflows to validate risks and stress-test AI features
Design Practical and Effective AI Defenses
Apply validation, filtering, and safety controls that strengthen system behavior
Test defenses under realistic conditions to confirm they prevent exploitation
Build repeatable evaluation routines that surface failures early
Secure AI Systems Through Real-World Projects
Investigate live systems for vulnerabilities and test exploitation paths
Repair insecure flows and measure the impact of your fixes
Complete projects that prepare you for the AIRTP+ exam through practical, exam-aligned work
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