Large Language Models (LLMs) and AI applications are revolutionizing industries, from customer service to healthcare and beyond. These systems are intelligent, adaptive, and powerful — but they’re also highly vulnerable. As their adoption grows, so do the risks, making it imperative to secure these technologies from emerging threats.

To address these challenges, the OWASP LLM Top 10 provides a comprehensive framework to identify and mitigate the most critical security risks in LLMs and AI applications. This series explores these vulnerabilities, one by one, to help developers, security professionals, and organizations build robust, secure AI systems.

What Is the OWASP LLM Top 10?

The OWASP LLM Top 10 outlines the most pressing risks specific to LLMs and AI-powered applications. Inspired by the classic OWASP Web Application Security Top 10, this list focuses on the unique vulnerabilities introduced by AI’s evolving capabilities.

Here’s the official OWASP LLM Top 10:

1. Prompt Injection
2. Sensitive Information Disclosure
3. Supply Chain Risks
4. Data and Model Poisoning
5. Improper Output Handling
6. Excessive Agency
7. System Prompt Leakage
8. Vector and Embedding Weaknesses
9. Misinformation Risks
10. Unbounded Consumption

Each of these vulnerabilities introduces unique challenges, ranging from manipulating AI prompts to exploiting weaknesses in model training and deployment.

Why Is LLM Security Important?

AI systems are becoming critical components of modern infrastructure. But with their increasing influence comes increased risk. Without proper safeguards, these systems can:

• Leak sensitive information, such as private user data or trade secrets.
• Be exploited to spread misinformation or harm users.
• Be manipulated through poisoned data or malicious prompts.

For example:

• Imagine a chatbot revealing sensitive customer information because of poorly secured prompt handling.
• Or a recommendation system being fed malicious data, leading to biased or harmful outputs.

These aren’t hypothetical scenarios — they’re real risks that require immediate attention.

What This Series Will Cover

In this series, we’ll dive deep into the OWASP LLM Top 10 vulnerabilities, explaining each risk, how attackers exploit them, and, most importantly, how to mitigate them. Here’s a roadmap of what to expect:

1. Prompt Injection: Learn how attackers manipulate LLMs with malicious inputs and how to defend against these attacks.
2. Sensitive Information Disclosure: Explore how AI systems inadvertently reveal private or sensitive data.
3. Supply Chain Risks: Understand the dangers of using compromised third-party models or components.
4. Data and Model Poisoning: Discover how malicious actors corrupt training data or models to skew outputs.
5. Improper Output Handling: Mitigate the risks of harmful or misleading outputs generated by LLMs.
6. Excessive Agency: Address the dangers of granting LLMs too much autonomy over sensitive processes.
7. System Prompt Leakage: Protect internal system instructions from being exposed through clever user queries.
8. Vector and Embedding Weaknesses: Secure vector spaces and embeddings against attacks that exploit their structure.
9. Misinformation Risks: Combat the spread of false or harmful information generated by AI.
10. Unbounded Consumption: Prevent resource exhaustion caused by unregulated interactions with LLMs.

Who Should Follow This Series?

This series is designed for:

• AI Developers: Learn how to secure LLMs and AI applications.
• Cybersecurity Professionals: Understand new threats in the age of AI.
• Tech Enthusiasts: Stay informed about the evolving security landscape of AI systems.

Whether you’re building AI applications or exploring the world of LLMs, this series will equip you with the knowledge and tools to navigate and mitigate these risks.

Call to Action

AI security is not optional — it’s essential. The vulnerabilities in LLMs and AI applications are unique, complex, and rapidly evolving. By understanding and addressing the OWASP LLM Top 10, we can ensure these powerful tools remain secure, ethical, and beneficial.

Join me tomorrow as we dive into Prompt Injection, the first and most critical vulnerability in the OWASP LLM Top 10. We’ll explore how attackers manipulate AI prompts and how to protect your systems from exploitation.

Stay informed, stay secure, and let’s master LLM and AI app security together.