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DefensesarXiv 2610.13733Oct 9
KVeil: First-Place Solution for the ECCV 2026 LifeGenIP Unlearnable Video Challenge
Propose KVeil, which adds perturbations to face videos to prevent unauthorized customization from reproducing identity
arXiv
2610.13733
Published
Oct 9
Layer
Prompt layer
Setting
Models and APIs
Attacker
White-box, Black-box
Evaluated models
Wan2.2-TI2V-5B, HunyuanVideo-1.5, Kling 3.0 and others4
- AttacksMalicious use
- ComponentImage generation
AbstractKVeil adapts LETHE's reference-reading disruption to the challenge's two stages, ranking first on the leaderboard in both Final columns.
Paper analysisRead analysis
AttacksarXiv 2610.09973Oct 7
从期望危害到似然：LLM 智能体越狱的概率重构
提出 OPUR 攻击，用似然梯度优化对抗后缀越狱 LLM 智能体
arXiv
2610.09973
Published
Oct 7
Layer
Application layer
Setting
AI Agent
Attacker
White-box
Evaluated models
Llama-3.1-8B-Instruct, Ministral-8B-Instruct-2410
- AttacksJailbreaks
- TechniqueGradient and representation optimization
Paper analysisRead analysis
DefensesarXiv 2610.07532Oct 6
LADE：用暗知识中的模型无关潜在安全信号防御 LLM 越狱
提出 LADE，用首 token 暗知识在生成前过滤越狱查询
arXiv
2610.07532
Published
Oct 6
Layer
Prompt layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
Llama-2-7B-Chat, Llama-3-8B-Instruct, Qwen2-7B-Instruct and others13
- DefensesDetection and filtering
- AttacksJailbreaks
Abstract作者用 LADE 在生成前过滤有害查询，并称八个模型中六个的 Held-out 平均最好。
LADE 是一种只读首 token 输出概率的防御，用来在生成前挡下可能引出有害回复的查询。
Paper analysisRead analysis
AttacksarXiv 2610.06670Oct 6
研究者提出 Reward Stealing Attack，从对齐模型行为反推安全奖励实施攻击
提出 ReSA，从对齐模型行为恢复安全奖励并在解码时反转
arXiv
2610.06670
Published
Oct 6
Layer
Model layer
Setting
Models and APIs
Attacker
White-box, Gray-box
Evaluated models
Llama3.1-8B-Instruct, Gemma-7B-Instruct, Qwen2.5-7B-Instruct and others9
- AttacksJailbreaks
- TechniqueDefense-targeted
AbstractReSA 用最大熵 IRL 从对齐模型行为恢复代理安全奖励，并在解码时反转以诱导有害输出。
ReSA 是一种对抗攻击：从对齐模型的可观察行为恢复代理安全奖励，再在解码时把该奖励反过来用。。
Paper analysisRead analysis
AttacksarXiv 2610.05894Oct 5
研究者提出闭环偏见注入攻击
提出闭环激活引导，在扩散语言模型去噪过程中注入定向偏见
arXiv
2610.05894
Published
Oct 5
Layer
Model layer
Setting
Models and APIs
Attacker
Gray-box
Evaluated models
LLaDA-8B-Instruct, Dream-v0-Instruct-7B, LLaDA-MoE-7B-A1B-Instruct
- AttacksModel tampering
- TechniqueGradient and representation optimization
Abstract通过去噪中间概率反馈动态调节残差流转向，证明扩散语言模型在推理服务栈中存在闭环偏见注入脆弱性。
Paper analysisRead analysis
AttacksarXiv 2610.05601Oct 5
Tracer 框架可从遗忘后的扩散模型中识别被擦除概念
提出 TRACER，从权重差识别扩散模型被擦除概念
arXiv
2610.05601
Published
Oct 5
Layer
Model layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
Stable Diffusion v1.5, Stable Diffusion 3, FLUX.1 and others5
- AttacksExtraction and theft
- ComponentImage generation
AbstractTRACER 用权重足迹识别未披露擦除概念并估计个数，作者称数秒内完成且准确率高于对照。
TRACER 针对的是遗忘扩散模型上的目标识别：提供者从公开基座 W 用已发表方法擦掉未知集合 S⋆，只发布 W′。攻击者还有假定包含这些概念的词表，但不知擦了谁、擦了几个、用了什么算法。
Paper analysisRead analysis
DefensesarXiv 2610.05401Oct 5
AVCE：面向扩散模型可验证概念擦除的审计感知遗忘框架
提出审计感知遗忘框架 AVCE，从文本与视觉通路擦除扩散模型概念
arXiv
2610.05401
Published
Oct 5
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box, Black-box
Evaluated models
Stable Diffusion XL (SDXL), Stable Diffusion v1.5 (SD v1.5), Flux 1.0
- DefensesModel hardening
- AttacksJailbreaks
- ComponentImage generation
AbstractAVCE 在审计锚点上改两条注意力通路。
AVCE 是面向扩散模型的概念擦除方法，要让擦除经得起绕过文本条件的潜空间审计，而不只是挡住对抗提示词。
Paper analysisRead analysis
DefensesarXiv 2610.04470Oct 3
SENTINEL：通过意图感知的输入-输出匹配防御 LLM 越狱
提出生成时防御 SENTINEL，匹配输入输出以抽出越狱意图并停写
arXiv
2610.04470
Published
Oct 3
Layer
Model layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
Llama2-7B, Llama3-8B, Mistral-7B-v0.2 and others6
- DefensesInference-time intervention
- AttacksJailbreaks
Paper analysisRead analysis
DefensesarXiv 2610.04467Oct 3
无需目标答案的潜在空间安全对齐：无监督对抗训练提升 LLM 越狱鲁棒性
提出 Target-free LAT，用无目标多方向潜干预做对抗安全对齐以抵御越狱
arXiv
2610.04467
Published
Oct 3
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box, Black-box
Evaluated models
Qwen2.5-7B-Instruct, Llama-3-8B-Instruct, Mistral-7B-Instruct-v0.2
- DefensesModel hardening
- AttacksJailbreaks
AbstractTarget-free LAT 用无目标多方向潜干预扩大行为覆盖，作者称能提高越狱鲁棒性并保住效用。
Target-free LAT 是一种不监督有害输出的潜空间对抗对齐。它要处理的问题是：现有 LAT 每步大多只造一种有害行为，对不上真实越狱里的直接遵从、角色扮演、编码和多语言等模式。
Paper analysisRead analysis
AttacksarXiv 2610.03166Oct 2
LiBRA：通过双向隐空间优化实现检测感知的图像水印去除
提出 LiBRA，在潜空间双向优化以规避图像水印双侧检测
arXiv
2610.03166
Published
Oct 2
Layer
Model layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
Stable Signature, YU1, HiDDeN and others4
- AttacksDetection evasion
- TechniqueDefense-targeted
AbstractLiBRA 用双向潜空间优化规避双侧水印检测，并提高相对反转基线的保真。
Paper analysisRead analysis
DefensesarXiv 2610.02853Oct 2
研究提出基于收缩约束状态空间模型的有界可达性与越狱检测方法
提出收缩约束 SSM 安全头，认证嵌入扰动并检测越狱
arXiv
2610.02853
Published
Oct 2
Layer
Prompt layer
Setting
Models and APIs
Attacker
White-box, Black-box
Evaluated models
ToySSMClassifier, S4 safety head
- DefensesDetection and filtering
- AttacksJailbreaks
- ComponentGuardrails and judges
Abstract收缩给出玩具 LTI 的有界认证。
给 SSM 安全头一个收缩条件，并在越狱检测上使用收缩正则的 S4 头。。
Paper analysisRead analysis
AttacksarXiv 2610.03124Oct 2
研究提出 Untag 攻击框架，使开源大模型触发标签滥用检测机制失效
提出 UNTAG，绕过开源权重模型的 trigger-tag 滥用检测
arXiv
2610.03124
Published
Oct 2
Layer
Model layer
Setting
Models and APIs
Attacker
Black-box, White-box
Evaluated models
Llama2 (7B), Llama3 (8B), Qwen2.5 (7B)
- AttacksDetection evasion
- TechniqueDefense-targeted
- ComponentFine-tuning and open weights
Abstract作者用 UNTAG 评估 trigger-tag，认为其不能充当开放权重滥用检测的主要边界。
UNTAG 是针对开放权重 LLM 上条件滥用检测 trigger-tag 的统一攻击评估：信号可以在解码期注入，也可以写进权重，但攻击者若能改输出或改已发布权重，检测可以失效。
Paper analysisRead analysis
AttacksarXiv 2610.01365Oct 1
ReGap：无需真实隐私数据即可通过微调重新提取模型隐私关联
提出 ReGap，用自生成伪监督微调恢复模型中的隐私关联
arXiv
2610.01365
Published
Oct 1
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box, Gray-box
Evaluated models
GPT-2 Small, GPT-2 Medium, GPT-2 Large and others6
- AttacksExtraction and theft
- ComponentFine-tuning and open weights
Abstract提出无真实私有监督的恢复攻击 ReGap，实验显示微调可通过自生成数据唤醒模型潜在隐私关联，突显后适应隐私风险。
Paper analysisRead analysis
DefensesarXiv 2610.02418Oct 1
Whiteout：用混淆样本阻止 LLM 泄露个人敏感信息
提出 Whiteout，用伪装样本微调覆盖个人敏感信息关联
arXiv
2610.02418
Published
Oct 1
Layer
Training and data layer
Setting
Models and APIs
Attacker
Black-box, White-box
Evaluated models
Llama 3.2, Phi-3-mini, Gemma 3 and others7
- DefensesModel hardening
- AttacksExtraction and theft
Paper analysisRead analysis
DefensesarXiv 2609.39866Sep 30
研究者提出梯度封堵实现 LLM 发布前的预防性遗忘
提出 GSU 在发布前封堵敏感门梯度，抵抗下游微调获取禁止能力
arXiv
2609.39866
Published
Sep 30
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
Llama-3.2-1B, Llama-3.2-3B, Llama-3.1-8B and others7
- DefensesModel hardening
- AttacksModel tampering
- ComponentFine-tuning and open weights
AbstractGSU 在发布前封堵 SiLU 门的获取梯度，并在 TOFU 与 WMDP 上降低下游微调得分。
Gradient-Sealed Unlearning（GSU）是一种发布前的 preemptive unlearning：不删除模型里已经有的能力，而是让指定禁止域能力更难被发布后的微调获取。
Paper analysisRead analysis
AttacksarXiv 2609.39607Sep 30
Pretext 攻击绕过 NVIDIA SkillSpector 等 Agent 技能扫描器
提出 PRETEXT 攻击，迭代改写技能文本绕过技能扫描器并让 Agent 执行木马
arXiv
2609.39607
Published
Sep 30
Layer
Application layer
Setting
AI Agent
Attacker
White-box
Evaluated models
glm (z-ai/glm-5.1), qwen3t (qwen/qwen3-235b-a22b-thinking-2507), gpt-oss (openai/gpt-oss-120b)
- AttacksDetection evasion
- TechniqueAutomated search
- ComponentMCP and skills
Abstract论文提出了针对多阶段技能检测器的白盒攻击，揭示了单纯依赖大模型自适应检测的局限。
PRETEXT 是一项针对基于“静态规则加语义大模型”的智能体技能安全检测框架的白盒攻击与协同进化评估研究。
Paper analysisRead analysis
DefensesarXiv 2609.38909Sep 30
Purdue 提出 Pact：将欺骗作为行为遗忘
提出 PACT，遗忘推理模型在压力下的欺骗行为并保留上下文理解
arXiv
2609.38909
Published
Sep 30
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
DeepSeek-R1-Distill-Qwen-32B, QwQ-32B
- DefensesModel hardening
- AttacksModel tampering
- RiskDeception and scheming
- ComponentFine-tuning and open weights
Abstract论文将大模型欺骗形式化为上下文条件行为，提出 PACT 框架在消除欺骗的同时保留了上下文遵循能力。
Paper analysisRead analysis
DefensesarXiv 2610.00320Sep 29
研究显示少样本微调可绕过安全层局部冻结与修复防御
检验层冻结与奇异方向截断能否挡住少样本有害微调
arXiv
2610.00320
Published
Sep 29
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
Llama-3.1-8B-Instruct, Llama-3.1-Tulu-3-8B-DPO, OLMo-2-1124-7B-Instruct and others10
- DefensesModel hardening
- AttacksModel tampering
- ComponentFine-tuning and open weights
Abstract定位与恢复可以复现，但知情攻击能把损伤移出冻结带，并打败跨检查点的截断修复。
这篇工作检验：把拒答定位到某些层或更新方向之后，能不能在攻击者知情时还守住拒答。。
Paper analysisRead analysis
AttacksarXiv 2609.33445Sep 27
CSR：跨架构统一攻击概念擦除
提出跨架构攻击 CSR，用概念分数参数重学习恢复文生图被擦除概念
arXiv
2609.33445
Published
Sep 27
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
FLUX.1-dev, Stable Diffusion-v1.4
- AttacksModel tampering
- ComponentImage generation
Paper analysisRead analysis
AttacksarXiv 2609.33136Sep 27
Leaky Students：针对 on-policy distillation 的成员推断攻击
提出 Leaky，用新鲜轨迹的 token 对数概率差推断 OPD 训练记录成员身份
arXiv
2609.33136
Published
Sep 27
Layer
Model layer
Setting
Models and APIs
Attacker
Gray-box, Black-box
Evaluated models
Qwen3-1.7B, Qwen3-4B, Qwen3.5-2B and others5
- AttacksExtraction and theft
Paper analysisRead analysis

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