Expired Course: OWASP Top 10 LLM 2025: AI Security Essentials

Master the latest OWASP list for AI, protect Large Language Models apps, and build secure, resilient systems

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OWASP Top 10 LLM 2025: AI Security Essentials
EXPIRED

What You'll Learn

  • Understand the fundamentals of Large Language Models (LLMs) and their security landscape
  • Explore the OWASP Top 10 for LLMs (2025) and why it matters for developers, architects, and security professionals
  • Identify common vulnerabilities unique to LLMs, such as prompt injection and data leakage
  • Learn practical techniques for defending against adversarial prompt manipulation
  • Recognize risks of unbounded resource consumption and denial-of-wallet attacks
  • Detect and mitigate model extraction and replication attempts
  • Understand embedding inversion attacks and their impact on data privacy
  • Explore cross-tenant risks in multi-user vector databases and retrieval-augmented generation (RAG)
  • Implement safe input validation, sanitization, and filtering strategies
  • Apply Role-Based Access Control (RBAC) and least-privilege design principles to LLM systems
  • Build robust monitoring, logging, and anomaly detection pipelines for AI workloads
  • Learn secure deployment practices for APIs and LLM-driven applications
  • Apply adversarial robustness training and continuous red-teaming practices
  • Explore strategies for preventing sensitive information disclosure from training data
  • Balance usability with security when designing LLM-enabled user interfaces
  • Learn about legal, ethical, and compliance considerations for AI security
  • Gain hands-on experience with real-world case studies and attack simulations
  • Develop a security mindset for building and auditing AI-powered systems
  • Learn best practices for MLOps governance and secure lifecycle management
  • Walk away with actionable checklists and frameworks to protect LLMs in production

Requirements

  • Familiarity with web application concepts (APIs, databases, authentication)
  • General awareness of cybersecurity principles (helpful but not required)
  • Curiosity about Artificial Intelligence, Machine Learning, or LLMs
  • No advanced math or deep AI background is needed - we focus on practical security
  • Willingness to experiment with AI tools, prompts, and security testing scenarios

Who This Course is For

  • Software developers who integrate LLMs into applications and want to avoid common pitfalls
  • Security engineers and penetration testers interested in the newest category of AI threats
  • AI/ML engineers who need to secure LLM-powered pipelines, APIs, and RAG systems
  • Solution architects designing enterprise systems that include AI components
  • Product managers and tech leads who want to understand risks before deploying LLMs in production
  • DevOps and MLOps professionals responsible for monitoring and governance of AI systems
  • Cybersecurity students and researchers exploring adversarial AI and AI ethics
  • Compliance and risk management professionals looking to align AI use with security standards
  • Business leaders and decision-makers seeking to make informed choices about adopting LLMs securely
  • Anyone curious about the OWASP Top 10 for LLMs (2025) and eager to learn practical defense strategies

Your Instructor

Andrii Piatakha

Founder and CEO in IT-Bulls, Founder of Learn-IT University

4.4 Instructor Rating

49,574 Reviews

1,179,427 Students

73 Courses

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