English

Geometric Configurations of Perturbed Jailbreak Prompts

Cryptography and Security 2026-07-22 v1 Artificial Intelligence

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 "\.C\.C" in the 1$ Llama model, display a significant association with a compliant-labeled answer.

Keywords

Cite

@article{arxiv.2607.20581,
  title  = {Geometric Configurations of Perturbed Jailbreak Prompts},
  author = {Lynn Delcon and Andres Algaba and Vincent Ginis},
  journal= {arXiv preprint arXiv:2607.20581},
  year   = {2026}
}

Comments

21 pages, 9 figures, 7 tables, 2nd Workshop on Safe AI (SafeAI)