ForgeDAN: An Evolutionary Framework for Jailbreaking Aligned Large Language Models

arXiv:2511.13548 · cs.CR, cs.AI, cs.CL · Submitted 2025-11-17 · Read on arXiv

cs.CR, cs.AI, cs.CL

Submitted: 2025-11-17

Updated: 2025-11-17

Terminology

• Alignment — 19× in this paper · explained in 1 episode
• Core — 15× in this paper · explained in 2 episodes
• Robustness — 13× in this paper · explained in 5 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Semantic Similarity — 8× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Attack Success Rate — 5× in this paper
• Transferability — 5× in this paper · explained in 4 episodes
• Verification — 5× in this paper · explained in 2 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Adaptability — 4× in this paper · explained in 1 episode
• Embeddings — 4× in this paper · explained in 2 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Large Language Models (LLMs) — 4× in this paper · explained in 6 episodes
• Adversarial Attacks — 3× in this paper · explained in 1 episode
• Attack Success Rate (ASR) — 3× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Iterative Refinement — 3× in this paper · explained in 3 episodes
• Empirical Methods in Natural Language Processing — 2× in this paper
• International Conference on Learning Representations — 2× in this paper
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Perplexity — 2× in this paper · explained in 3 episodes
• Prompt Engineering — 2× in this paper · explained in 4 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Adversarial Prompting — 1× in this paper · explained in 1 episode
• Adversarial Training — 1× in this paper · explained in 1 episode
• Adversarial scenarios — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Lexical Diversity — 1× in this paper · explained in 2 episodes
• Prompt Automatic Iterative Refinement — 1× in this paper
• Supervised Fine-Tuning — 1× in this paper
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study
• Don't Say No: Jailbreaking LLM by Suppressing Refusal
• Automated Progressive Red Teaming
• Safety Assessment of Chinese Large Language Models

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