DefensesarXiv 2609.37054
ACTR：对齐推理与回答以提升推理大语言模型的多语言安全
提出 ACTR，只更新安全思考神经元以对齐推理与回答的安全类别
- arXiv
- 2609.37054
- Published
- Setting
- Models and APIs
- Evaluated models
- Qwen3-8B, Gemma4-12B-it
- DefensesModel hardening
- AttacksJailbreaks
- ComponentReasoning chains
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- DefensesarXiv 2609.36562
ThinkingGuard：通过逐步风险归因解码多模态大语言模型中的隐式危害
构建 TriggerBench 并训练 ThinkingGuard，检测图文隐式风险
- arXiv
- 2609.36562
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Evaluated models
- ThinkingGuard（Qwen3-VL-8B-Instruct）
- DefensesDetection and filtering
- AttacksJailbreaks
- ComponentGuardrails and judges
AbstractTriggerBench 隔离触发条件，ThinkingGuard 用分步归因在隐式风险检测上取得作者报告的较高平均分。
这篇工作研究多模态隐式风险检测：图文各自良性，风险只在关键元素与触发元素交互时出现。
- DefensesarXiv 2609.34519
EOPSA：高效在策略自蒸馏安全对齐方法
提出 EOPSA，用 TRR 截断与安全类过滤做在策略自蒸馏安全对齐
- arXiv
- 2609.34519
- Published
- Setting
- Models and APIs
- Evaluated models
- Qwen3-1.7B, Qwen3-4B, Qwen3-14B and others5
- DefensesModel hardening
- AttacksJailbreaks
- ComponentReasoning chains
- AttacksarXiv 2609.29775
输出前缀攻击瞄准推理模型
提出推理通道预填与输出前缀组合攻击以越狱推理模型
- arXiv
- 2609.29775
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- Black-box
- Evaluated models
- Gemini 3 Flash Preview, DeepSeek V4 Flash, Claude Haiku 4.5
- AttacksJailbreaks
- TechniqueReasoning-chain manipulation
- ComponentReasoning chains
大型推理模型的效率与安全困境：量化与剪枝如何影响越狱鲁棒性
分析量化、剪枝与 KV 缓存压缩对推理模型越狱鲁棒性的影响
- arXiv
- 2609.23587
- Published
- Layer
- Model layer
- Setting
- Models and APIs
- Evaluated models
- QwQ-32B, DeepSeek-R1-Distill-Qwen-32B, DeepSeek-R1-Distill-Llama-8B
- AttacksJailbreaks
- ComponentReasoning chains
Abstract效率压缩常使 LRM 越狱 HR 下降，作者将其归因于推理退化而非对齐增强。
作者分析量化、剪枝和 KV 缓存压缩如何同时改变 LRM 的显存、推理和越狱脆弱性。。
- AttacksarXiv 2609.09553
研究：任意密文攻击前沿大模型无需微调即可越狱
提出任意字母置换密码越狱，无需微调即可诱导有害输出
- arXiv
- 2609.09553
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- Black-box
- Evaluated models
- Claude Sonnet 4, Claude Sonnet 4.5, Gemini 3 Flash (preview) and others7
- AttacksJailbreaks
- TechniqueEncoding and obfuscation
- ComponentGuardrails and judges
Abstract前沿大模型无需微调即可通过提示词学会字母置换密码，进而绕过分类器与对齐，作者呼吁关注能力提升带来的安全风险。
- Risky behaviorarXiv 2609.08186
论文揭示大推理模型的对齐崩溃并提出 Reasoning Trap 越狱范式
揭示推理加深引发的对齐坍塌，用 Reasoning Trap 放大越狱
- arXiv
- 2609.08186
- Published
- Layer
- Model layer
- Setting
- Models and APIs
- Evaluated models
- Qwen3-8B, Qwen3-14B, Llama2-7B and others8
- AttacksJailbreaks
- RiskMisalignment and value divergence
- TechniqueReasoning-chain manipulation
- ComponentReasoning chains
Abstract更深推理提升题目准确率，同时提高扰动下的相对损失。
作者研究扩展推理是否以对齐稳健性为代价，提出 ALR、RT 与 RRA。。
- AttacksarXiv 2604.02652
Generalization limitations of reinforcement-learning alignment
Proposes composite jailbreaks, stacking contrast structure, authoritative persona, and self-evaluation to saturate the instruction hierarchy
- arXiv
- 2604.02652
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Evaluated models
- OpenAI gpt-oss-20b
- AttacksJailbreaks
- TechniqueRole-play and persuasion
- ComponentReasoning chains
- AttacksarXiv 2603.10091
多流扰动攻击：通过并发任务干扰突破思考型 LLM 的安全对齐
提出多流扰动攻击，交织有害与良性任务绕过思考型 LLM 安全对齐
- arXiv
- 2603.10091
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Evaluated models
- Qwen3 1.7B, Qwen3 4B, Qwen3 8B and others11
- AttacksJailbreaks
- TechniqueEncoding and obfuscation
- ComponentReasoning chains
Abstract多流扰动用任务交织测试 thinking 模式，作者称它同时冲击内容安全与推理稳定性。
多流扰动攻击把有害任务与良性任务织进同一提示词，测试 thinking 模式的内容安全与推理稳定性。作者认为，交织多任务会拉长思考，使安全检测面对被打散的有害意图，并可能把推理用于合理化，或陷入崩溃与重复。方法不访问梯度。
- AttacksarXiv 2603.09246
研究者提出 Reasoning-Oriented Programming，通过链式语义片段越狱大型视觉语言模型
提出 VROP，把有害意图拆成良性视觉 gadget 越狱视觉语言模型
- arXiv
- 2603.09246
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- Black-box
- Evaluated models
- GPT-4o, Claude 3.7 Sonnet, GLM-4V-Plus and others7
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentVision
AbstractVROP 以良性视觉 gadget 与控制流提示词做组合越狱。
VROP是 black-box 多模态越狱框架：不在输入中放显式恶意触发，而把有害目标拆成语义正交的良性视觉 gadget，再用控制流提示词把合成留到后期推理。
- DefensesarXiv 2602.11096
Safety Recovery of Reasoning Models Only Needs a Few Early Steps of Guidance
提出推理时防御 SafeThink，监视思维链并在低于阈值时注入转向前缀
- arXiv
- 2602.11096
- Published
- Layer
- Model layer
- Setting
- Models and APIs
- Evaluated models
- R1-Onevision-7B, OpenVLThinker-7B, VLAA-Thinker-7B and others6
- DefensesInference-time intervention
- AttacksJailbreaks
- ComponentReasoning chains
- AttacksarXiv 2512.05853
VRSA：通过视觉推理序列攻击越狱多模态大模型
提出视觉推理序列攻击 VRSA，以图像序列越狱多模态大模型
- arXiv
- 2512.05853
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Attacker
- Black-box
- Evaluated models
- DeepSeek-VL2-tiny, InternVL-3.5-8B, LLaVA-1.6-Mistral-7B and others8
- AttacksJailbreaks
- TechniqueCross-modal payloads
- ComponentVision
- AttacksarXiv 2510.11570
研究显示简单攻击可绕过 gpt-oss 等推理模型的安全护栏
提出四种阶段转换攻击，绕过推理模型的安全推理护栏
- arXiv
- 2510.11570
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Evaluated models
- gpt-oss-20b, gpt-oss-120b, Qwen3-4B-Thinking-2507 and others10
- AttacksJailbreaks
- TechniqueReasoning-chain manipulation
- ComponentReasoning chains
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