With the recent release of the OWASP top 10 for LLM applications, the spotlight is on the security challenges that come with integrating these powerful tools into applications.
Prompt Injection vulnerabilities are of particular concern, and they underscore the complexity of maintaining a robust security posture with LLMs.
Whether you're new to the field or an experienced professional, asking the right questions is crucial for secure deployment:
🎯 Direct Prompt Injection
- How are system prompts protected from unauthorized overwriting or revelation?
- What mechanisms are in place to detect and prevent unauthorized commands?
🎯 Indirect Prompt Injection
- How do we handle external input to the LLM, and how can it be manipulated by an attacker?
- What controls are in place to sanitize or segregate untrusted content and limit their influence on user prompts?
- Are there mechanisms to visually highlight potentially untrustworthy responses to the user?
🎯 Extensible Functionality & Plugins
- How do we manage plugins or other extensible functionalities with the LLM?
- What privilege controls are in place for the LLM's access to backend systems and extensible functionalities?
- Are user approval mechanisms implemented for privileged operations?
🎯 Mitigation, Monitoring, & Awareness
- What measures have been taken to establish trust boundaries between the LLM, external sources, and extensible functionalities?
- How are we monitoring the behavior of the LLM to detect suspicious activities or signs of an attack?
- Have we conducted regular security testing, including penetration testing and code review, to identify and remediate prompt injection vulnerabilities?
Based on OWASP Top 10 for Large Language Model Applications.
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