A meta-prompt and hierarchical detection framework automates LLM red-teaming, achieving 3.9 times higher vulnerability discovery rate than manual methods with 89% accuracy on GPT-OSS-20B.
" 18returntemplate Listing 2: Sandbagging attack generation template A.3 Inappropriate Tool Use Templates 1defgenerate_tool_misuse_template(tool_name, usage_context): 2template = f
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Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models
A meta-prompt and hierarchical detection framework automates LLM red-teaming, achieving 3.9 times higher vulnerability discovery rate than manual methods with 89% accuracy on GPT-OSS-20B.