OWASP LLM Top 10: PromptInjection Feedback


## **PromptInjection_Feedback.md**

### **Strengths**:
1. **Clear Structure**: The entry follows a well-organized structure with appropriate headings, making it easy to navigate. This is important for readers, especially when dealing with complex topics.
2. **Concise and Direct Explanation**: The description is clear and quickly conveys the core issue of prompt injection. The author does a good job of explaining the vulnerability without overloading the reader with technical jargon.
3. **Effective Use of Examples**: The section outlining examples and scenarios provides concrete, relatable instances where this vulnerability could occur, which makes it easier for readers to grasp the concept.

### **Areas for Improvement**:

1. **Overuse of Long Sentences**: There are a few long, complex sentences that can be broken down for better readability. For instance, in the first paragraph, the sentence “These inputs can affect the model even if they are imperceptible to humans, therefore prompt injections do not need to be human-visible/readable” could be split to improve clarity.
2. **Bullet Lists for Key Points**: The entry would benefit from more frequent use of bullet points, especially in the "Common Examples of Vulnerability" and "Prevention and Mitigation Strategies" sections. This would improve readability and make the information easier to scan.
3. **Tone Consistency**: The tone is mostly formal, but a few areas could be made more concise and professional. For instance, phrases like "therefore" and "even if" could be tightened up for a smoother tone.

### **Suggestions for Enhancement**:

1. **Rephrase for Clarity**:
   - Original: “These inputs can affect the model even if they are imperceptible to humans, therefore prompt injections do not need to be human-visible/readable, as long as the content is parsed by the LLM.”
   - Suggested: “Prompt injections can affect the model even when they are imperceptible to humans. The input does not need to be visible or readable, as long as the LLM parses the content.”
   
2. **Use Bullet Points for Vulnerability Examples**: 
   - In the “Common Examples of Vulnerability” section, instead of presenting examples in paragraph form, use a numbered list:
     1. **Example 1**: Malicious actors use input that misguides the model to execute unauthorized actions.
     2. **Example 2**: User inputs unstructured text that bypasses preset restrictions within the LLM’s prompts.

3. **Simplify Sentences for Better Flow**: In some sections, the sentences could be simplified:
   - Original: "This can cause the LLM to produce outputs that violate its intended use case or even allow for harmful activities."
   - Suggested: "As a result, the LLM may produce outputs that violate its intended use or facilitate harmful activities."

4. **More Consistent Formatting**:
   - Ensure each section has a consistent and clear format. For instance, the **Example Attack Scenarios** could be broken into clearly numbered examples for uniformity with the rest of the document.

5. **Use More Section Headings**: 
   - Consider adding a section called "Potential Impact" or "Risks" to highlight the severity of prompt injection vulnerabilities. This will emphasize the importance of addressing the issue.