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AI Security for Product Teams
This 10-lesson course, packed with exclusive insights and practical tools, will guide you through securing AI applications, understanding key threats, navigating regulations, and making a business case for AI security.

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Overview

Explore AI security with the Lakera LLM Security Playbook. This guide is a valuable resource for everyone looking to understand the risks associated with AI technologies.

Ideal for professionals, security enthusiasts, or those curious about AI, the playbook offers insight into the challenges and solutions in AI security.

Highlights

  • Comprehensive Analysis of LLM Vulnerabilities: Detailed overview of critical security risks in LLM applications.
  • Gandalf - The AI Education Game: Introduction to Gandalf, an online game designed for learning about AI security.
  • Expansive Attack Database: Insights from a database of nearly 30 million LLM attack data points, updated regularly.
  • Lakera Guard - Security Solution: Information about Lakera Guard, developed to counteract common AI threats.‍
  • Practical Security Advice: Tips on data sanitization, PII detection, and keeping up-to-date with AI security developments.

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Are you building AI products? Learn the essentials of AI security with Lakera's "AI Security for Product Teams."

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This 10-lesson course, packed with exclusive insights and practical tools, will guide you through securing AI applications, understanding key threats, navigating regulations, and making a business case for AI security.

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What’s inside:

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Day 1: Introduction to AI Security for Product Teams – Learn why AI security is crucial for product teams and how it differs from traditional cybersecurity.

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Day 2: AI Security Threat Landscape Overview – Understand common AI threats, including prompt injections and data poisoning, and explore real-world breaches.

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Day 3: Prompt Injection Attacks Deep Dive – Discover the different types of prompt injection attacks with examples.

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Day 4: Regulatory Landscape for AI Products – Get a brief overview of AI-specific regulations like the EU AI Act and the US AI Bill of Rights.

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Day 5: Secure AI Product Development Lifecycle – Explore when and how to address security during AI product development and the importance of 'secure by design.

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Day 6: Addressing User Concerns and Privacy in GenAI – Learn how to tackle unique privacy concerns in GenAI and communicate security measures effectively to users.

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Day 7: AI Security Tools & How to Evaluate Them – An overview of key tools and how to integrate security testing into your QA processes.

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Day 8: Making a Business Case for AI Security – Learn to unlock enterprise sales and gain leadership buy-in by making a compelling business case for AI security.

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Day 9: How to Secure Your GenAI Application – Step-by-step guide on securing various types of GenAI applications, including a Lakera demo.

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Day 10: AI Security Resources for Product Teams – Discover essential resources and networks for staying updated on AI security.

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Note: Please ensure the name you enter in the registration form is accurate, as it will be used exactly as provided for your certificate. Double-check for any typos before submitting.