Intro to LLM Security – OWASP Top 10 for Large Language Mode

What you'll learn
The AI Threat Landscape: Understand the Rise of LLMs and New Attack Surfaces that differ fundamentally from traditional web application security.
The Blueprint for Defense: Master the OWASP Top 10 for LLM Applications and learn to assess risks based on Prevalence, Exploitability, and Impact.
Secure Foundations: Integrate LLM security into the Secure Development Lifecycle (SDLC) with a practical Whiteboard Solution for risk analysis and mitigation
The #1 Risk: Deep dive into LLM01: Prompt Injection and distinguish between direct and indirect attacks.
Strategic Layering: Implement a robust Defense-in-Depth architecture tailored for LLMs.
Vector Database Security: Understand the emerging threats and best practices for LLM08: Vector and Embedding Weaknesses.
Protecting Your Secrets: Implement controls against LLM02: Sensitive Information Disclosure and prevent model over-sharing.
Requirements
No Pre Requirements
Description
"This course contains the use of artificial intelligence."Course OverviewThe integration of Large Language Models (LLMs) into enterprise applications has opened up a powerful new frontier—and a dangerous new attack surface.This comprehensive course is designed to equip developers, security professionals, and architects with the specialized knowledge and practical skills needed to build, deploy, and manage secure LLM applications.You won't just learn what the risks are; you'll learn how to proactively prevent them.We will dive deep into the OWASP Top 10 for LLM Applications, providing clear, actionable strategies for mitigating the most critical vulnerabilities at every stage of the development lifecycle.What You Will LearnModule 1: Introduction to LLM Security and the OWASP Top 10The AI Threat Landscape: Understand the Rise of LLMs and New Attack Surfaces that differ fundamentally from traditional web application security.The Blueprint for Defense: Master the OWASP Top 10 for LLM Applications and learn to assess risks based on Prevalence, Exploitability, and Impact.Secure Foundations: Integrate LLM security into the Secure Development Lifecycle (SDLC) with a practical Whiteboard Solution for risk analysis and mitigation.Module 2: The Critical Input and Output VulnerabilitiesThe #1 Risk: Deep dive into LLM01: Prompt Injection and distinguish between direct and indirect attacks.Defense Against Data Poisoning: Address LLM07: System Prompt Leakage and secure the core instructions of your model.Post-Processing Security: Learn best practices to prevent vulnerabilities like XSS through LLM05: Improper Output Handling.Module 3: Data, Model, and Supply Chain RisksProtecting Your Secrets: Implement controls against LLM02: Sensitive Information Disclosure and prevent model over-sharing.Integrity is Key: Explore the threats of LLM04: Data and Model Poisoning and how they compromise model reliability.Third-Party Trust: Secure your reliance on external components by mitigating LLM03: Supply Chain Vulnerabilities with a dedicated Whiteboard Solution.Module 4: Runtime, Control, and Operational IssuesControlling the Model's Power: Address LLM06: Excessive Agency using the Principle of Least Privilege and human-in-the-loop controls.Beyond the Code: Explore operational risks like LLM09: Misinformation and Overreliance and guard against financial attacks through LLM10: Unbounded Consumption.Vector Database Security: Understand the emerging threats and best practices for LLM08: Vector and Embedding Weaknesses.Module 5: Defense-in-Depth and Future TrendsStrategic Layering: Implement a robust Defense-in-Depth architecture tailored for LLMs.Active Testing: Master Best Practices for LLM Security Testing, including Red Teaming and Adversarial Testing.Staying Ahead: Establish protocols for Monitoring, Logging, and Incident Response and prepare for The Future of LLM Security and Emerging Threats.Who Should Attend?Software Developers building LLM-enabled features.Security Engineers responsible for application and AI security.DevOps/MLOps Engineers managing LLM deployment and infrastructure.Technical Product Managers overseeing AI product development.Enroll now to transform from simply using LLMs to building genuinely secure AI applications.
Who this course is for
Software Developers building LLM-enabled features.
Security Engineers responsible for application and AI security.
DevOps/MLOps Engineers managing LLM deployment and infrastructure
Technical Product Managers overseeing AI product development.
Homepage

https://www.udemy.com/course/intro-to-llm-security-owasp-top-10-for-large-language-mode/

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