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Oct 13 · Tuesday

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Attack surface / entry point：Code repositories and dependencies Attack surface / entry point：Training data System component：Memory System component：Reasoning chains System component：Vision Clear all

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AttacksarXiv 2610.12644Oct 9
Cancerous backdoor attack: progressive activation via invisible tokens and a stage controller.
Proposes the Cancerous backdoor, which progressively corrupts reasoning using invisible stage tokens.
arXiv
2610.12644
Published
Oct 9
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
Llama-3.1-8B-Instruct, Qwen2.5-7B-Instruct, Mistral-7B-Instruct-v0.3
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentReasoning chains
AbstractHidden tokens plus a stage controller make the backdoor progressively corrupt reasoning upon triggering, and the authors believe that looking only at the answer will miss it.
Cancerous Backdoor Attack changes LLM backdoors from one-time activation to multi-stage reasoning corruption that accumulates progressively with triggers.
Paper analysisRead analysis
DefensesarXiv 2610.09941Oct 7
OrthoPurify 用一步正交投影净化被后门污染的视觉语言模型
提出 OrthoPurify，用正交投影清除视觉语言模型适配器中的劫持方向
arXiv
2610.09941
Published
Oct 7
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
LLaVA-1.5-7B, Qwen3-VL-8B, LLaVA-1.5-13B and others5
- DefensesModel hardening
- AttacksPoisoning and backdoors
- ComponentFine-tuning and open weights
Abstract一次投影去掉劫持方向。
OrthoPurify 是部署前的 LVLM 后门净化方法，用一次正交投影去掉被劫持的权重更新方向。
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 2609.35659Sep 29
Tracekit: A tamper-proof intent-reasoning-action audit system for autonomous coding agents
提出 Tracekit，审计编码 Agent 的意图、推理与动作并检测账本篡改
arXiv
2609.35659
Published
Sep 29
Layer
Application layer
Setting
coding agent
Evaluated models
Claude Code (claude -p, version 2.1), 独立评审（同一 CLI，无工具）
- DefensesMonitoring and auditing
- AttacksPrompt injection
- RiskDangerous agent actions
- ComponentMonitors
AbstractTracekit 把意图、自述和动作写入可锚定的哈希链。
Tracekit 是无第三方依赖的编码智能体审计层：把人类请求、模型自述和已执行动作并排写入可外部锚定的哈希链，执行前用正则门，事后用规则和独立模型互查。
Paper analysisRead analysis
DefensesarXiv 2609.28239Sep 23
ODPure：通过集成破坏共识实现目标检测后门净化
提出 ODPure，在输入阶段用腐蚀重建与共识净化目标检测后门
arXiv
2609.28239
Published
Sep 23
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
YOLOv5, Faster R-CNN
- AttacksPoisoning and backdoors
- ComponentVision
Paper analysisRead analysis
AttacksarXiv 2609.07048Sep 7
FreqDoor：面向视觉语言模型的频域后门攻击
提出 FreqDoor，在频域混合振幅并对生成式 VLM 做训练时视觉后门
arXiv
2609.07048
Published
Sep 7
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
BLIP-2 (opt-2.7b), InstructBLIP (flan-t5-xl), LLaVA (interleave-qwen)
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentVision
AbstractFreqDoor 用频域振幅混合给三款 VLM 植入仅视觉的训练时后门。
FreqDoor 是针对生成式 VLM 的仅视觉、训练时后门：在频域混合触发源振幅、保留干净图像相位，使触发在空间上分散。
Paper analysisRead analysis
DefensesarXiv 2609.06346Sep 6
面向后门攻击下持续学习的鲁棒动态扩展：净化与选择性恢复
提出持续学习下的净化与选择性恢复框架，抵御逐任务训练投毒后门
arXiv
2609.06346
Published
Sep 6
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
ViT-B/16
- DefensesModel hardening
- AttacksPoisoning and backdoors
- ComponentVision
Abstract作者报告任务内净化与恢复可配合动态专家防御后门，但保证依赖分离条件。
这是一项面向持续图像分类的后门防御研究：模型只使用当前任务数据，同时需要保留过去知识并避免学习恶意监督。
Paper analysisRead analysis
DefensesarXiv 2609.03139Sep 3
TRIM：面向多种后门触发器的黑盒检测与净化方法
提出 TRIM，在黑盒推理时定位并净化图像后门区域
arXiv
2609.03139
Published
Sep 3
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
ResNet-50
- DefensesInference-time intervention
- AttacksPoisoning and backdoors
- ComponentVision
Paper analysisRead analysis
AttacksarXiv 2609.01222Sep 1
Researchers propose context privilege escalation attack, affecting 12 agent frameworks
提出针对 Agent Harness 的上下文特权提升攻击
arXiv
2609.01222
Published
Sep 1
Layer
Application layer
Setting
coding agent
Evaluated models
GPT-5.5, GPT-5.4 mini, Claude-Sonnet-4.6 and others7
- AttacksPrompt injection
- TechniqueDormant triggers
- ComponentMemory
Paper analysisRead analysis
DefensesarXiv 2608.24354Aug 25
RACER：面向多模态大模型后门的区域感知一致性修复框架
提出 RACER，用区域感知一致性对抗微调去除多模态大模型后门
arXiv
2608.24354
Published
Aug 25
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
LLaVA-1.5-7B, Qwen2-VL-7B, Qwen2.5-VL-7B
- DefensesModel hardening
- AttacksPoisoning and backdoors
- ComponentVision
Paper analysisRead analysis
AttacksarXiv 2608.09867Aug 11
Researchers steal proprietary LLM inference chains via cross-model compatibility of encrypted inference blocks
利用加密思维块的跨模型重放，诱导弱模型逐字转写专有推理链
arXiv
2608.09867
Published
Aug 11
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
Claude Opus 4.8, Claude Sonnet 4.6, Claude Haiku 4.5 and others13
- AttacksExtraction and theft
- TechniqueReasoning-chain manipulation
- ComponentReasoning chains
Abstract论文揭示了客户端加密思维块跨模型互换漏洞，提出了低成本提取方法并给出防御方案。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2607.14611Jul 16
论文评测 Claude Code 与 Codex 记忆文件中的提示注入风险
评测编码 Agent 记忆文件中提示注入的跨会话影响
arXiv
2607.14611
Published
Jul 16
Layer
Application layer
Setting
coding agent
Evaluated models
Claude Haiku 4.5, Claude Opus 4.7, GPT-5.2 and others4
- AttacksPoisoning and backdoors
- ComponentMemory
Abstract已植入记忆文件的载荷可以跨会话影响 Claude Code 与 Codex，攻击成功与载荷是否留下是两种不同的失败。
Bad Memory 在沙箱合成工作区里评测文件型持久记忆上的提示注入，比较载荷能否改变当前会话，以及能否在后续会话中留下或叠加。
Paper analysisRead analysis
AttacksarXiv 2606.14517Jun 12
Researchers disclose a reasoning-amplified denial-of-service attack against LLM agent guardrails
提出针对 Agent 护栏的推理扩展拒绝服务攻击
arXiv
2606.14517
Published
Jun 12
Layer
Application layer
Setting
AI Agent
Attacker
Black-box
Evaluated models
TS-Guard-8B, Qwen3.5-9B, DeepSeek-V3.2 and others11
- AttacksDenial of service
- TechniqueReasoning-chain manipulation
- ComponentGuardrails and judges
Paper analysisRead analysis
AttacksarXiv 2605.30040May 28
研究揭示 LLM 按 token 计费可被服务商系统性虚报
构造可通过计费审计的 token 虚报，使服务商系统性超收
arXiv
2605.30040
Published
May 28
Layer
Infrastructure layer
Setting
Models and APIs
Evaluated models
PALACE domain-adapted auditor
- AttacksDetection evasion
- TechniqueDefense-targeted
- ComponentMonitors
Abstract不诚实提供方可在三种 token 审计上虚报并通过检查，作者认为需改用提供方不控制的证据。
不透明 LLM 的按 token 计费里，现有审计核验的是提供方可控的证据，不诚实提供方可以虚报并通过检查。。
Paper analysisRead analysis
AttacksarXiv 2605.15338May 15
Hidden in Memory: Latent Memory Poisoning of LLM Agents
提出潜伏记忆投毒，诱导 Agent 把外部文档写成持久伪造记忆
arXiv
2605.15338
Published
May 15
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-5.4, GPT-5.5, Claude Sonnet 4.6 and others12
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentMemory
Abstract持久记忆成为跨会话攻击面：通用载荷可写入伪造记忆，并在相关后续任务中影响行为。
sleeper memory poisoning 研究带持久记忆的 LLM 助手：外部文档能否让助手存下一则伪造的用户记忆，并在原文档消失后的新会话里被取回、用来改变回复或动作。
Paper analysisRead analysis
AttacksarXiv 2602.06409Feb 6
VENOMREC: Cross-modal Interactive Poisoning for Targeted Promotion in Multimodal LLM Recommendation Systems
提出 VenomRec 跨模态交互投毒，定向推广多模态推荐物品
arXiv
2602.06409
Published
Feb 6
Layer
Training and data layer
Setting
LLM applications
Evaluated models
VIP5 (T5-small), VIP5 (T5-base), DiffMM
- AttacksPoisoning and backdoors
- TechniqueCross-modal payloads
- ComponentVision
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2511.18921Nov 24, 2025
BackdoorVLM：面向视觉语言模型后门攻击与防御的基准
提出 BackdoorVLM 基准，评测视觉语言模型微调中的后门攻击与防御
arXiv
2511.18921
Published
Nov 24, 2025
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
LLaVA-1.5-7B, Qwen2.5-VL-7B
- AttacksPoisoning and backdoors
- ComponentFine-tuning and open weights
AbstractBackdoorVLM 统一评测 VLM 后门与防御：含文本触发在低投毒率下更易激活，现有防御跨类型不稳定。
BackdoorVLM 是作者提出的 VLM 后门攻击与防御评测基准，作者称它是首个此类综合基准。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2510.14207Oct 16, 2025
论文提出多轮在线骚扰 Agent 基准
提出多轮在线骚扰 Agent 基准，评测记忆、规划与微调越狱
arXiv
2510.14207
Published
Oct 16, 2025
Layer
Application layer
Setting
Multi-agent systems
Evaluated models
LLaMA-3.1-8B-Instruct, Qwen3-30B-A3B-Instruct, DeepSeekMoE-16B and others4
- AttacksJailbreaks
- ComponentFine-tuning and open weights
Paper analysisRead analysis

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Attack type

Attack technique

Defense type

Impact

System type

Attack surface / entry point

Layer

System component

Cancerous backdoor attack: progressive activation via invisible tokens and a stage controller.

OrthoPurify 用一步正交投影净化被后门污染的视觉语言模型

Purdue 提出 Pact：将欺骗作为行为遗忘

Tracekit: A tamper-proof intent-reasoning-action audit system for autonomous coding agents

ODPure：通过集成破坏共识实现目标检测后门净化

FreqDoor：面向视觉语言模型的频域后门攻击

面向后门攻击下持续学习的鲁棒动态扩展：净化与选择性恢复

TRIM：面向多种后门触发器的黑盒检测与净化方法

Researchers propose context privilege escalation attack, affecting 12 agent frameworks

RACER：面向多模态大模型后门的区域感知一致性修复框架

Researchers steal proprietary LLM inference chains via cross-model compatibility of encrypted inference blocks

论文评测 Claude Code 与 Codex 记忆文件中的提示注入风险

Researchers disclose a reasoning-amplified denial-of-service attack against LLM agent guardrails

研究揭示 LLM 按 token 计费可被服务商系统性虚报

Hidden in Memory: Latent Memory Poisoning of LLM Agents

VENOMREC: Cross-modal Interactive Poisoning for Targeted Promotion in Multimodal LLM Recommendation Systems

BackdoorVLM：面向视觉语言模型后门攻击与防御的基准

论文提出多轮在线骚扰 Agent 基准