🔥 Next batch starts 5 Oct — enroll by 30 Sep 2026 for early-bird pricing  |  10,000+ Students Trained Globally

AI Security & LLM Exploitation

AI Security & LLM Exploitation

AI shipped to production.
Its attack surface came too.

A 41-module offensive AI security course — prompt injection, autonomous agent exploitation, RAG and vector database risks, MCP protocol attacks and AI-powered pentesting automation, every topic paired with hands-on labs.

41 Modules OWASP LLM Top 10 MCP Security Real AI Lab Environments
ai-pentest / llm-session
$ probe system prompt
[+] hidden instructions extracted
$ inject indirect payload via document
[+] agent executed unintended tool call
$ enumerate mcp tools
[+] tool shadowing possible
[✓] finding documented
41Training Modules
5Core Skill Highlights
40 hrsLive, in Real AI Environments
Hands-OnPractice Approach
10,000+ professionals trainedTraining security professionals globally since 2015.
Industry-recognised instructorsCertified professionals acknowledged by Facebook, Google, Microsoft and 20+ global companies.
Placement support includedResume reviews, mock interviews and direct referrals to 100+ partner organizations.
Course positioning

New capability. Entirely new vulnerability class.

AI is already embedded in enterprise applications and developer workflows — and it brought prompt injection, data poisoning, insecure agent tool use and protocol-level attacks with it.

Learning AI security in theory

✕ Prompt injection sounds simple until you face a real guardrail.
✕ Agent and tool-use abuse is hard to picture without a live agent.
✕ MCP is new — almost no training material covers it.
✕ No safe environment to test model and data poisoning.

Ignite's hands-on approach

✓ 41 modules covering the full AI & LLM attack surface.
✓ Hands-on prompt injection, agent exploitation & MCP attacks.
✓ OWASP Top 10 for LLMs with real-world lab scenarios.
✓ AI-powered pentesting automation with Burp Suite integration.
“You’re not just memorizing stuff—you’re actually learning how to use it.”— Guido Solares, verbatim Google review
Your learning outcomes

The full AI stack, attacked end to end

Six focus areas that carry through all 41 modules of the course.

LLM Foundations

Tokens, transformers, inference flow and the OWASP Top 10 for LLMs.

Prompt Injection

Direct, indirect and multi-layer prompt manipulation plus defenses.

Agents & RAG

Autonomous agent abuse, vector database and embedding vulnerabilities.

Data & Model Attacks

Training data poisoning, model inversion and supply chain risk.

MCP Security

Traffic analysis, tool hijacking, token theft and control bypass.

AI-Powered Pentesting

Burp Suite integration, automation and local LLM deployment.

Learning journey

One skill builds the next

The 41 modules are sequenced from LLM fundamentals through to advanced exploitation.

01FoundationsLLM internals
02Prompt InjectionAttack & defense
03Agents & RAGTool abuse
04Data AttacksPoisoning & leakage
05MCPProtocol exploitation
06AutomationAI-powered testing
41 training modules

Full curriculum, module by module

Click a module to see what it covers.

Understand how LLMs work internally including tokens, transformers, and inference flow. Build a strong base for AI security concepts.

Explore the major risks identified in LLM applications and how they impact enterprise systems.

Hands-on setup of a working lab to safely test AI vulnerabilities and attacks.

Learn how attackers manipulate prompts and how to design defenses against them.

Understand hidden and multi-layer prompt injection methods used in real-world attacks.

Analyze how AI agents can be abused to perform unintended actions.

Identify how AI generates incorrect outputs and the business risks involved.

Learn how data leaks occur and how to prevent exposure of confidential information.

Understand risks from third-party models, APIs, and integrations.

Explore how training data can be manipulated to compromise AI behavior.

Learn how improper handling of AI outputs can lead to vulnerabilities.

Understand how attackers extract hidden system instructions.

Learn risks in embeddings and vector search systems.

Compare Retrieval-Augmented Generation with traditional LLM models.

Design scalable and secure AI chatbot systems.

Understand how attackers extract sensitive data from AI systems.

Implement validation strategies for secure AI inputs.

Explore injection risks in UI layers interacting with AI.

Understand command-level attacks triggered via AI.

Learn how hidden metadata can leak sensitive information.

Understand how attackers alter AI memory behavior.

Introduction to MCP and its role in AI ecosystems.

Practical setup for testing MCP-related vulnerabilities.

Breakdown of MCP architecture and modules.

Capture and analyze MCP communication.

Understand exploitation techniques targeting MCP tools.

Compare attack strategies on different resource types.

Identify risks of internal data leaks.

Explore command injection specific to MCP.

Understand misuse of MCP resources.

Learn how attackers override tools in MCP.

Techniques to evade MCP defenses.

Understand session compromise methods.

Learn how AI can be used to execute malicious code.

Identify access control flaws in AI applications.

Deploy and manage local LLMs securely.

Understand steps to create custom AI models.

Use AI within security testing workflows.

Automate security testing using AI tools.

Enhance developer productivity using AI assistants.

Apply all learned techniques to identify and exploit chatbot vulnerabilities.

Prerequisites

You’re ready if you have the basics

Missing one? Book a free demo — we’ll help you pick the right starting point.

Web Application Security Basics (HTTP, APIs)
Python or Any Scripting Language
No AI/ML Background Required — Covered From Scratch
Inside the lab

Practice the workflow, not just the prompt

A glimpse of the AI attack-chain approach used throughout the course.

$ upload doc with hidden instruction
[i] agent ingests document via RAG pipeline
[+] indirect prompt injection triggered
$ observe tool invocation
[+] agent called internal API unprompted

[+] sensitive record returned to attacker
[✓] impact proven, mitigation documented
"The goal is not to jailbreak a chatbot. The goal is to know what the model can reach."Practice-first learning principle
✓ AI security is the fastest-growing attack surface
✓ Covers offensive techniques and enterprise-grade defensive controls
✓ Includes cutting-edge MCP security content
✓ Taught by practitioners actively researching AI and LLM vulnerabilities
Fees & duration

What it costs, and how long it takes

No hidden charges. Ask us about instalments or group rates if you need them.

Early bird · closes 30 Sep 2026 1 days left
Expert level
Course fee ₹56,500 ₹47,000 or $530 USD $635 You save ₹9,500
Duration 40 hours of live, instructor-led training
  • Live instructor-led classes
  • Hands-on lab access
  • Projects and practical exercises
  • Interview preparation
  • Certificate on completion

Outside India or after hours? Fill the enrollment form instead — we reply by email.

Regular fee ₹56,500 applies once the 5 Oct batch opens.

Not ready to decide? Sit in on a free demo class first — nothing to pay until you’re sure.

What students say

Don't take our word for it

Unedited reviews our students left on Google.

Google
The AI Security training I took from Ignite Technology exceeded my expectations. The instructor, Priti, not only explained the concepts theoretically but also clearly demonstrated how we should think and approach them in real-world scenarios. From a security perspective, the discussion around risks, attack surfaces, and defense strategies of AI systems was truly eye-opening.
D Davut Eren AI Security training · Local Guide · Google Review
Google
I recently completed the AI Pentesting training with Ignite Technologies, and it was a great learning experience. The training was well-structured, practical, and focused on real-world concepts. A special thanks to Priti Madam for explaining complex topics in a simple and easy-to-understand way. The hands-on approach and practical examples made the sessions very valuable.
S Shikha yadav AI Pentesting training · Google Review
Google
Ignite technologies a known for its research and innovation especially in the field of offensive security. It not only provides great trainings but also educate Infosec community sharing great resources through articles and research papers.
S Subhash Paudel Google Review
Google
I recently completed training at Ignite Technologies, and I couldn't be more impressed with the experience. Raj Sir and his team are incredibly knowledgeable ad passionate about latest Pentesting techniques, which makes complex topics easy …
N nauman kirmani Google Review
Google
Great place to learn with awesome content and articles to be in sync with the cyber world.
S Shivanshu Singh Google Review
Google
Top notch instructors with real world experience. Highly recommend.
S sergio dote Google Review
FAQ

Before you start

Do I need an AI or machine learning background?+
No. The course begins with LLM fundamentals before progressing to offensive techniques — basic web application security knowledge and some scripting is enough.
Does it cover MCP (Model Context Protocol) security?+
Yes, extensively — MCP fundamentals, lab setup, traffic analysis, tool hijacking, token theft and control bypass each have dedicated modules.
Are the labs real or simulated?+
Hands-on labs run in real AI environments, not simulations, so the techniques transfer directly to live systems.
Does it cover defense as well as attack?+
Yes. The curriculum covers both offensive techniques and enterprise-grade defensive controls, including input validation and AI security controls.

Still deciding?

Sit in on a live class before you commit. It’s free, and there’s no obligation.

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