Artificial intelligence opens up new opportunities for businesses, but at the same time, it creates fundamentally new security risks. Prompt Injection, Jailbreak attacks, bypassing security mechanisms, and manipulation of large language models (LLM) are among today's most critical threats to modern AI applications.
This practical course is dedicated to AI Red Teaming — a cybersecurity discipline focused on identifying, modeling, and mitigating vulnerabilities in artificial intelligence systems. You will learn to think like an attacker to build truly secure AI systems.
During the training, you will gain practical experience conducting attacks on language models, study modern methods of exploiting vulnerabilities, learn to analyze the behavior of AI systems, and develop effective protection mechanisms. All lab work is based on real scenarios, as close as possible to the operating conditions of corporate AI applications.
Who the Course is For
The course will be beneficial for:
- information security specialists;
- AI/ML engineers and LLM application developers;
- software developers using generative AI;
- AI solution architects;
- DevSecOps and AppSec engineers;
- artificial intelligence security researchers;
- anyone responsible for the safe implementation of AI in a corporate environment.
What You Will Learn
Understanding Vulnerabilities in Modern AI Systems
You will understand why large language models become targets of attacks, how Prompt Injection, Jailbreak, Adversarial Attacks, and other techniques for bypassing security mechanisms work. You will study the architectural features of AI applications and understand why traditional approaches to information security are not always effective when dealing with generative AI.
Practice AI Red Teaming
You will master the methodology of conducting AI Red Team Assessment, learn to identify vulnerabilities, simulate real attacks, and analyze the response of language models to various types of malicious impacts. You will complete practical tasks for finding and exploiting weaknesses in AI systems in a safe lab environment.
Analyzing the Behavior of Language Models
You will learn to explore the internal logic of LLM operations, analyze model responses, identify the causes of vulnerabilities, and assess the potential consequences of successful attacks. You will gain skills in conducting a systematic analysis of the security of AI applications.
Building Robust AI Application Protections
You will study modern methods for protecting generative AI: input data filtering, request validation, context limitation, access control mechanisms, model behavior monitoring, RAG system protection, and multi-level strategies for preventing Prompt Injection and Jailbreak attacks.
Testing the Effectiveness of Protective Mechanisms
You will learn to test the implemented protective measures under conditions as close as possible to real attacks. You will master the construction of repeatable security assessment processes for AI systems and learn to identify potential issues even before the product is deployed in a production environment.
Practical Projects
Within the course, you will complete a series of practical projects on the security audit of AI applications, conduct a full cycle of AI Red Team Assessment, eliminate identified vulnerabilities, and assess the effectiveness of the implemented protection measures. The acquired skills will help apply the best practices of AI Security in the development and operation of modern intelligent systems.
Learning Outcomes
Upon completing the course, you will be able to:
- understand modern security threats to generative AI;
- conduct AI Red Team Assessment for LLM and AI applications;
- identify Prompt Injection, Jailbreak, and other types of attacks;
- analyze the architecture of AI systems from a security perspective;
- develop and implement effective protection mechanisms;
- conduct security testing of AI applications before deployment;
- apply the best global practices of AI Security in the development and maintenance of intelligent systems.
By the end of the course, you will have practical skills in finding, exploiting, and overcoming vulnerabilities in modern AI systems, allowing you to create more reliable, secure, and resilient solutions based on artificial intelligence.
