Geometric Configurations of Perturbed Jailbreak Prompts
Abstract
Perturbation techniques that turn unsuccessful jailbreak prompts into successful ones are continuously evolving, constituting a major security threat to LLM safety.
In this paper, we investigate the internal representations of such string-level perturbed jailbreak inputs in the small weight models of the Qwen-2.5-1.5B/-3B/-7B-Instruct and Llama-3.2-1B/-3B/-3.1-8B-Instruct families.
We select two representation spaces: the last-layer-last-token embedding space and the top-50 next-token probability space.
The former space separates prompts based on their spelling and format, while the latter space is effectively one-dimensional but appears more complex to cluster.
Within our refusal-dominated answer set we find no behavioral hyperplane in either space.
Only the next token "Sure" in the 1.5B Qwen model, and both tokens "," and "ĊĊ" in the 1$ Llama model, display a significant association with a compliant-labeled answer.
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