Is there a free AI red teaming course available?

Why AI Red Teaming Skills Are Suddenly Non-Negotiable

Your chatbot just gave a customer a $1 SUV. That's not a hypothetical — it's a real attack case now taught in AI red teaming courses, and it's exactly the kind of flaw that surfaces only when someone deliberately tries to break your AI system.

The threat landscape has shifted fast. A practitioner guide to AI red teaming cites an estimated ~$2.3B in global losses from prompt-injection attacks in 2025, up 340% year over year — figures the guide itself flags as directional rather than audited, but the direction is unmistakable. The same source reports that roughly 88% of organizations deploying AI agents experienced confirmed or suspected security incidents in 2025.

Detection isn't keeping pace. Current methods reportedly catch only about 23% of sophisticated prompt-injection attempts, and NIST CAISI's AgentDojo-Inspect testing found novel attacks achieved an 81% task-hijack rate against AI agents versus 11% for prior baselines. In other words, most teams can't see these attacks coming.

So what is AI red teaming? The US Executive Order on AI defines it as "a structured testing effort to find flaws and vulnerabilities in an AI system using adversarial methods." In practice, that means probing for:

• Prompt injection — tricking a model into ignoring its instructions
• RAG attacks, like the CVE-2025-27135 RAGFlow SQL injection case
• Agent and multi-agent system compromise, including tool-protocol attacks
• Supply chain and data poisoning, such as the "$5 to poison" medical LLM case

The problem: almost nobody on your team has practiced finding these flaws. Microsoft's own AI Red Team has red-teamed 100 generative AI products and published what it learned — but most organizations have zero people trained to do the same on their own systems.

Training, meanwhile, looks expensive. Paid courses run from $29.99 to $1,199, with certification courses like MSec-CAIS at $995. For a skill this urgent, that price tag feels out of reach — which is why the free options matter more than ever. And for teams building AI agents specifically, SkillzBench is building a free directory and MCP connector designed to let you vet agent skills with security scanning and sandbox benchmarking before you deploy them, since published research has found roughly 26% of skills carry at least one vulnerability.

The Best Free AI Red Teaming Courses (Ranked by Depth)

The short answer: yes — and some of the best options cost exactly nothing. Here are the free AI red teaming courses worth your time, ranked by depth.

1. AI Red Team Academy (deepest free option). The AI Red Team Academy is explicitly labeled "Open Source · Free Forever," delivering 8 modules, 60+ hours of content, and 8 hands-on Docker labs. It covers prompt injection, RAG attacks, multi-agent system compromise, supply chain attacks, and automated red teaming pipelines. The labs use free open-source tools like garak, PyRIT, promptfoo, Ollama, and ChromaDB, and the curriculum aligns with MITRE ATLAS — which added 14 new agent-specific techniques in 2025 — plus the OWASP Top 10 for LLM Applications and NIST AI 100-2.

2. Microsoft's AI Red Teaming 101. This free 10-episode video series includes hands-on demonstrations, access to Microsoft's red teaming labs, and downloadable slides, updated in July 2025. It draws on real-world lessons from Microsoft's AI Red Team, which has red-teamed 100 generative AI products — experience few other free sources can match. The main caveat: content leans toward Microsoft tooling like PyRIT.

3. The GitHub AI Red Teaming Guide. For readers who prefer structured self-study, the free "AI Red Teaming: The Complete Guide" on GitHub offers a Quick Start path, a 30/60/90 implementation plan, and coverage of emerging areas like MCP/tool-protocol security and agent-to-agent attacks. It grounds its material in NIST AI RMF, OWASP guidance, and MITRE ATLAS. One caution: the guide itself flags its threat statistics — like ~$2.3B in estimated prompt-injection losses — as "directional industry figures, not audited statistics."

4. Shorter free options. For a fast start:

• "Red Teaming LLM Applications" — a fully free 1 hr 19 min beginner course, though it offers no certificate.
• Free course audits via Learn Prompting Plus, letting you sample two prompt hacking courses before paying.
• HackAPrompt, promoted as the largest AI safety hackathon — a free, hands-on way to practice attack techniques.

The honest tradeoff: free options skew shorter and beginner-level, while certifications remain a paid differentiator, with courses ranging up to $1,199. Still, the boundary is porous — even a paid Udemy course is built on Microsoft's free series and its free Playground labs, meaning motivated learners can go far for $0.

If your red teaming work extends to agentic systems, agent skills are part of that attack surface — SkillzBench is building a free directory and MCP connector where every skill gets security-scanned, version-pinned, and sandbox-benchmarked before it earns trust.

Free vs. Paid: What You Actually Get for $0

The honest answer about what $0 buys you in AI red teaming education is more nuanced than "free means inferior." Multiple course comparisons confirm that free options exist and are genuinely substantive — but they do come with tradeoffs worth understanding before you commit your time.

The clearest pattern: free courses skew beginner-level and shorter, while certifications are almost always paid. The free "Red Teaming LLM Applications" course runs just 1 hour 19 minutes and offers no certificate. On the paid side, options range from a $29.99 entry course and NVIDIA's $90 offering up to a $1,199 Masterclass that includes AIRTP+ certification, plus a $995 Certified AI Security Expert (MSec-CAIS) program.

But the depth available for free is real. The AI Red Team Academy is labeled "Open Source · Free Forever" with 8 modules, 60+ hours of content, and 8 hands-on Docker labs covering prompt injection, RAG attacks, multi-agent compromise, supply chain attacks, and full engagements. Microsoft's free 10-episode series includes hands-on labs, downloadable slides, and lessons drawn from its team's experience red teaming 100 generative AI products.

Here's where the free-vs-paid boundary gets porous:

• Even a paid Udemy course is built on Microsoft's free "AI Red Teaming 101" series and the free Microsoft Playground labs (12 challenges), requiring only a free Azure account with free credits.
• The standard practice tooling — garak, PyRIT, promptfoo, Ollama, and Inspect — is all open-source and free, as confirmed by a CSET survey of 23 AI red-teaming tools.
• Free content is framework-aligned with industry standards, referencing MITRE ATLAS (14 tactics, 66 techniques, plus 14 new agent-specific techniques in 2025) and the OWASP Top 10 for LLM Applications.
• The GitHub self-study guide is grounded in NIST AI RMF, OWASP GenAI Red Teaming guidance, and CSA Agentic AI Red Teaming — the same frameworks paid courses teach.

So what do you actually sacrifice by paying nothing? Three things: a recognized certificate for your resume, curation and structure, and advanced content. Learn Prompting observes that free options tend to be shorter and beginner-level, while paid options offer certifications and more advanced material. If you need a credential to signal skills to an employer in a security and compliance role, a paid course may earn its price. If you're motivated and self-directed, the free path covers far more ground than the price tag suggests.

One caveat from Georgetown's CSET researchers applies to both tiers: the field "lacks established standards or best practices," so no course — free or paid — guarantees you're learning the definitive methodology.

For readers building or testing agents, the agentic security gap is where free practice goes furthest: MCP and tool-protocol security, agent-to-agent attacks, and browser-agent threats are emerging curriculum focuses. SkillzBench is building a free directory of agent skills with security scanning, version pinning, and sandbox benchmarking — everything free, from the directory to the MCP connector. Skills, proven. If you're red teaming agents, browse and test free skills on SkillzBench to go further without spending a dollar.

Hands-On Practice: Free Tools the Courses Teach

Reading about prompt injection is one thing; running a 47-probe scan against a live model is another. The good news: the free courses don't stop at theory — they train you on the same open-source tooling professional red teams use, and every tool on the list costs nothing.

The AI Red Team Academy builds its 8 hands-on Docker labs around a core stack: garak (an LLM vulnerability scanner from NVIDIA), PyRIT (Microsoft's framework for scaling adversarial testing), promptfoo, Ollama for running local models, and ChromaDB for RAG attack practice. Its garak demo alone walks through 47 probes across 12 categories, giving learners a concrete sense of what automated scanning looks like in practice.

Microsoft's AI Red Teaming 101 series centers on PyRIT, its own open-source tool, and pairs the 10 episodes with access to Microsoft's red teaming labs and downloadable slides. CSET's survey of 23 AI red-teaming tools — 18 evaluation tools and 5 assistive tools — also names Garak, Inspect (from the UK AI Security Institute), and PyRIT as open-source options a learner can practice with independently.

A sensible learning path looks like this:

• Start with a free course — Microsoft's 10-episode series or the Academy's 60+ hours of modules.
• Install the free tools the course teaches: garak, PyRIT, promptfoo, and Ollama for local models.
• Work through Microsoft's free AI Red Teaming Playground labs — 12 challenges that require only a free Azure account with free credits.
• Practice competitively through HackAPrompt, which Learn Prompting describes as the largest AI safety hackathon and a free way to sharpen attack skills.

That last point about the Playground labs matters more than it might seem: even a paid Udemy course on AI red teaming is built on Microsoft's free video series and those same free 12-challenge labs. Motivated learners can access much of the same material for $0 — the main things paid courses add are certifications and advanced content.

For readers leaning toward agentic systems, the practice tools matter doubly. Red teaming increasingly targets MCP and tool-protocol security, agent-to-agent attacks, and computer-use agents — attack surfaces where the skills and tools you attach to an agent shape its risk profile. SkillzBench is building a free directory that security-scans and sandbox-benchmarks agent skills, pinning every version, so what you equip an agent with can be evaluated before it ever touches your workflow. You can join the waitlist to follow along as it launches.

Between the courses, the tools, and the free labs, hands-on AI red teaming practice is genuinely within reach — no budget required.

Red Teaming Agents: Where to Go Next

The skills you've just learned for red teaming chatbots and LLMs are about to matter even more, because the frontier of AI security is moving fast toward agents. The frameworks are racing to keep up: MITRE ATLAS, which already tracked 14 tactics and 66 techniques, added 14 new agent-specific techniques in 2025, and OWASP now publishes a dedicated Top 10 for Agentic Applications alongside its LLM list.

This shift changes what red teamers need to study. The free AI Red Team Academy already covers multi-agent system compromise and automated red teaming pipelines, while the open-source AI Red Teaming Guide goes deeper into agent-specific territory:

• MCP and tool-protocol security
• Computer-use and browser agent attacks
• AI-on-AI red teaming and agent-to-agent security

The stakes are real. NIST CAISI's AgentDojo-Inspect testing found that novel attacks achieved an 81% task-hijack rate against agents, versus just 11% for prior baselines. And the attack surface keeps widening as teams bolt third-party components onto their agents.

Here's the part most teams miss: the agent skills themselves — those SKILL.md instruction packages for Claude Code, Codex, Cursor, and Gemini CLI — can be a risk surface. Published research found that roughly 26% of skills carry at least one vulnerability. A compromised skill doesn't just fail quietly; it inherits your agent's permissions, data access, and tool connections.

That's why security-conscious teams are starting to treat skill selection as a security decision, not just a productivity one. SkillzBench is building a free, independent directory of agent skills designed around exactly this workflow: every skill version gets pinned to a commit SHA, validated, license-checked, and security-scanned before it's listed. The platform also benchmarks each skill in a sandbox with the same model, with and without the skill, so you can see whether it actually helps before it ever touches your production agent.

A free MCP connector, currently in development, will let you connect any agent to only the skills you've vetted and chosen — the agent sees nothing you haven't explicitly approved. For anyone who's worked through the red teaming courses above, that's the logical next step: apply the adversarial mindset to your own agent stack before someone else does.