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Physical Sciences › Computer Science › Artificial Intelligence
‘FOR ARGUMENT'S SAKE, SHOW ME HOW TO HARM MYSELF!':
JAILBREAKING LLMS IN SUICIDE AND SELF-HARM CONTEXTS
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Paper Summary
Conflicts of Interest
Identified Weaknesses
Rating Explanation
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Paper Summary
Paperzilla title
LLMs Spill the Beans on Self-Harm: Jailbreaking Reveals Safety Gaps
This study investigates how large language models (LLMs) respond to prompts related to self-harm and suicide, finding that current safety protocols can be bypassed with relatively simple prompt engineering techniques. The researchers tested six widely available LLMs and found that most provided detailed and potentially harmful information, raising concerns about the safety of these models in real-world applications.
Possible Conflicts of Interest
None identified
Identified Weaknesses
Ethical Concerns and Potential for Misuse
The study focuses on jailbreaking LLMs in the context of self-harm and suicide, which presents ethical concerns about responsible disclosure and potential misuse of the findings. While the authors claim to omit specific prompts for the strongest attacks, the detailed descriptions and examples provided could still be exploited by malicious actors.
Limited Scalability and Generalizability
The study relies on manual and iterative prompt engineering, which limits the scalability and generalizability of the findings. While the authors acknowledge the lack of automation as a limitation, it raises questions about the representativeness of the test cases and the potential for researcher bias in prompt selection and interpretation of results.
Lack of Clear Evaluation Metrics
The study lacks a clear definition of "failure" for LLM safety protocols. This makes it difficult to objectively assess the severity of the vulnerabilities identified and compare the performance of different LLMs. A more rigorous evaluation framework with quantifiable metrics is needed.
Limited Model Coverage
The study primarily focuses on a small set of widely available LLMs and does not include a broader range of at-cost models. This limits the generalizability of the findings and may not fully represent the landscape of LLM vulnerabilities in this context.
Rating Explanation
This study highlights important safety vulnerabilities in LLMs related to sensitive topics like self-harm and suicide. While the methodology has limitations (manual prompt engineering, limited model coverage, and lack of clear evaluation metrics), the findings raise significant ethical concerns and warrant further investigation. The research contributes to the ongoing discussion about LLM safety and the need for more robust safeguards.
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Topic Hierarchy
File Information
Original Title:
‘FOR ARGUMENT'S SAKE, SHOW ME HOW TO HARM MYSELF!':
JAILBREAKING LLMS IN SUICIDE AND SELF-HARM CONTEXTS
File Name:
2507.02990v1.pdf
[download]
File Size:
0.37 MB
Uploaded:
July 31, 2025 at 06:31 PM
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