OWASP Top 10 Vulnerabilities for LLM Applications

As developers, data scientists, and security experts work with LLM technologies to design and build applications and plug-ins, it is essential to be mindful of potential security risks. The Open Web Application Security Project (OWASP) identifies several key vulnerabilities in LLM-based systems that need attention:

1. Prompt Injection

Prompt Injection involves manipulating LLMs through clever inputs, leading to unintended actions.

2. Insecure Output Handling

Insecure Output Handling arises when LLM outputs are accepted without proper scrutiny, exposing backend systems to serious threats.

3. Training Data Poisoning

Training Data Poisoning occurs when tampered LLM training data introduces vulnerabilities or biases.

4. Model Denial of Service

Model Denial of Service exploits LLMs’ resource-intensive nature, causing resource-heavy operations and service degradation.

5. Supply Chain Vulnerabilities

Supply Chain Vulnerabilities compromise the LLM application lifecycle by incorporating vulnerable components or services.

6. Sensitive Information Disclosure

Sensitive Information Disclosure occurs when LLMs inadvertently reveal confidential data in their responses.

7. Insecure Plugin Design

Insecure Plugin Design exposes LLM plugins to exploitation and potential code execution.

8. Excessive Agency

Excessive Agency leads to unintended consequences due to excessive LLM functionality.

9. Over-reliance

Over-reliance on LLMs without proper oversight may result in misinformation, miscommunication, legal issues, and security vulnerabilities.

10. Model Theft

Model Theft involves unauthorized access, copying, or exfiltration of proprietary LLM models, leading to economic losses and compromised competitiveness.

Being aware of these OWASP-identified vulnerabilities empowers developers, data scientists, and security experts to implement best practices and security measures, ensuring the robustness and security of LLM-based applications and plug-ins.

Stay tuned to learn more about the key LLM security vulnerabilities, and how to safeguard sensitive data and user interactions.

More Insights