Agentic AI Red Teaming: Hands-On Security Testing
This course contains the use of artificial intelligence.AI agents do more than answer questions. They plan, call tools, store memories, coordinate with other...
What You'll Learn
- Map AI agent attack surfaces across planning loops, prompts, tool execution, external data, long-term memory, and multi-agent orchestration.
- Test prompt injection, goal hijacking, instruction override, multi-turn attacks, and gradual goal drift without touching real customer systems.
- Evaluate tool-call exploitation, unsafe tool chaining, excessive permissions, weak authorization, and untrusted tool responses.
- Investigate memory poisoning, persistent state attacks, context manipulation, and retrieval-based threats in RAG workflows.
- Examine agent-to-agent communication, cross-agent manipulation, false consensus, compromised workers, and multi-agent coordination failures.
- Assess Model Context Protocol (MCP) security, tool metadata integrity, and unsafe integration boundaries.
- Design adversarial test cases, automated security regression testing, execution traces, and AI security scorecards.
- Measure cascading failures, propagation depth, blast radius, unsafe action rates, and the difference between single-turn failure and system-wide compromise.
- Apply least privilege, policy enforcement, approval gates, memory validation, monitoring, and defense-in-depth, then retest to verify improvements.
About This Free Course
This course contains the use of artificial intelligence.
AI agents do more than answer questions. They plan, call tools, store memories, coordinate with other agents, and take action. Every capability creates a new security boundary. This hands-on course, Agentic AI Red Teaming: Hands-On Security Testing, teaches you to evaluate those boundaries and uncover failures before they reach production.
You'll learn agentic AI security, AI red teaming, LLM security testing, and adversarial AI evaluation through a realistic enterprise case study: BrightDesk, a fictional multi-agent customer support platform. Instead of relying on slides alone, you'll work with an isolated AI agent testing sandbox, synthetic records, mock APIs, local tools, and repeatable tests. See how an apparently harmless instruction can redirect a plan, trigger an inappropriate tool call, or contaminate later decisions.
What You'll Learn
Map AI agent attack surfaces across planning loops, prompts, tool execution, external data, long-term memory, and multi-agent orchestration.
Test prompt injection, goal hijacking, instruction override, multi-turn attacks, and gradual goal drift without touching real customer systems.
Evaluate tool-call exploitation, unsafe tool chaining, excessive permissions, weak authorization, and untrusted tool responses.
Investigate memory poisoning, persistent state attacks, context manipulation, and retrieval-based threats in RAG workflows.
Examine agent-to-agent communication, cross-agent manipulation, false consensus, compromised workers, and multi-agent coordination failures.
Assess Model Context Protocol (MCP) security, tool metadata integrity, and unsafe integration boundaries.
Design adversarial test cases, automated security regression testing, execution traces, and AI security scorecards.
Measure cascading failures, propagation depth, blast radius, unsafe action rates, and the difference between single-turn failure and system-wide compromise.
Apply least privilege, policy enforcement, approval gates, memory validation, monitoring, and defense-in-depth, then retest to verify improvements.
Build Practical Red-Team Skills
Using Python, Ollama, LangGraph, FastAPI, and pytest, you'll develop an agent testing environment and run controlled scenarios against BrightDesk. Explore AI threat modeling, risk prioritization, evidence collection, trace analysis, and security reporting. You'll also encounter concepts from the OWASP Top 10 for Agentic Applications, MITRE ATLAS, and AI governance, connecting technical findings to real enterprise risk decisions.
You'll practice distinguishing a model's incorrect answer from an agent's unauthorized action, and you'll learn why execution logs, reproducible scenarios, and clear pass/fail criteria matter when testing complex, stateful AI workflows in enterprise environments.
Your capstone is an end-to-end agentic AI penetration testing exercise in an authorized simulation. Create a threat model, execute structured adversarial evaluations, document vulnerabilities, introduce safeguards, and compare security results before and after remediation. You'll leave with reusable test templates, a security evaluation framework, and a portfolio-ready assessment report.
Who Should Enroll?
This course is designed for AI engineers, LLM developers, application security engineers, red teamers, penetration testers, AI architects, security researchers, and teams building autonomous AI agents or enterprise generative AI solutions. Basic Python skills and familiarity with LLMs or APIs will help; prior professional red-team experience isn't required.
If you're moving from traditional cybersecurity to agentic AI risk management, or building production agents that must be trustworthy, this course gives you a structured, hands-on way to test what happens when an AI system does more than talk.
Who Should Take This Course
"Agentic AI Red Teaming: Hands-On Security Testing" is aimed at people who want a practical, structured introduction to it & software without paying full price for it. It's a solid fit if you're starting out in it & software and want a guided course rather than piecing tutorials together yourself, if you've tried free YouTube content on the topic and want something more organized, or if you already work in a related area and want a refresher you can finish at your own pace. Since enrollment happens on Udemy itself, you keep full access to view the lectures, download any provided resources, and revisit the material later — this isn't a stripped-down or time-limited version of the course.
Why This Course Is Worth Taking
Our take: this listing earns a spot on DeelCart because the coupon we verified actually brings the price to $0, not just a token discount, and the course carries a 4.5/5 rating on Udemy. That combination — real reviews plus a working 100% OFF code — is what we look for before publishing a it & software course. It won't replace hands-on experience or a full degree program, but as a low-risk way to test whether it & software is worth pursuing further, or to pick up one specific skill, the free price tag makes it an easy yes while the coupon lasts.
Pros & Cons
👍 Pros
- 100% free to enroll via this coupon (normally $34.99)
- Lifetime access on Udemy once enrolled, even after the coupon expires
- Rated 4.5/5 by past students on Udemy
- Self-paced — no fixed schedule or live sessions to attend
👎 Cons
- Coupon is time-limited and can expire before you enroll
- No live instructor support — questions go through Udemy's Q&A, not us
- Certificate is a Udemy completion certificate, not an accredited qualification
Grab this course free before the coupon expires.
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Frequently Asked Questions
Is "Agentic AI Red Teaming: Hands-On Security Testing" really free?
Yes — we verified a 100% OFF Udemy coupon for this it & software course before publishing it. Enroll directly on Udemy using the button on this page; no credit card is needed while the coupon is active.
How long will this coupon last?
Udemy coupons typically last 1–3 days or expire after roughly 1,000 enrollments, whichever comes first. If the price on Udemy no longer shows $0 when you click through, the coupon has expired since we last checked it.
Do I keep access after the coupon expires?
Yes. Once you enroll while the coupon is live, "Agentic AI Red Teaming: Hands-On Security Testing" is yours to keep on Udemy — including any future updates the instructor makes — even after the coupon runs out.
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