DARWIN: Evolving Jailbreak Adversary and Guardrail for LLM Safety Evaluation and Protection
Most existing LLM safety evaluation and defense methods follow a static formulation: jailbreak vulnerabilities are evaluated with fixed attack methods, and guardrails are trained on fixed malicious prompt datasets. However, real-world adversaries continuously evolve their capabilities and expand the attack space. To address this challenge, we propose DARWIN, an evolutionary attack-defense framework that formulates jailbreaking as an open-ended evolution process and continuously updates guardrail
Record details
Published: 22 July 2026
Source: arXiv red teaming query
Category: Research
Topics: Safety & alignment · Military & security
Retrieved: 23 July 2026
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How to cite this record
ethics.ai (22 July 2026), “DARWIN: Evolving Jailbreak Adversary and Guardrail for LLM Safety Evaluation and Protection,” evidence record 12987, https://ethics.ai/record/12987 (originally published by arXiv red teaming query).
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