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Oct 12 · Monday

Agent safety · Papers

Found 11 papers

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Model risks

Reward hacking3 Dangerous agent actions11

Defense type

Monitoring and auditing9

Impact

Unauthorized actions6 Oversight failure3

System type

AI Agent11

Layer

Application layer11

System component

Memory5 Guardrails and judges5 Monitors11 Permissions and sandboxing23

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Model risks：Dangerous agent actions System component：Monitors Topic: Agent safety Clear all

DefensesarXiv 2610.12463Oct 9
Paper reviews OpenAI, Anthropic, and Google agent safety incidents and proposes the PASAC framework
Proposes PASAC and a five-layer boundary guarantee stack, turning agent evaluation overstepping into verifiable whole-system guarantees.
arXiv
2610.12463
Published
Oct 9
Layer
Application layer
Setting
AI Agent
- DefensesPermissions and approval
- RiskDangerous agent actions
- ComponentPermissions and sandboxing
Paper analysisRead analysis
DefensesarXiv 2610.12445Oct 9
FAR.AI paper: white-box probes surpass Opus 5.5 text monitoring on SHADE-Arena with 98.8% AUC
Using FIBS to train white-box probes to monitor agent sabotage behavior and undisclosed deception
arXiv
2610.12445
Published
Oct 9
Layer
Application layer
Setting
AI Agent
Evaluated models
Qwen3.5-397B-A17B, Qwen3.5-122B-A10B, Qwen3.5-27B and others10
- DefensesMonitoring and auditing
- RiskDeception and scheming
- ComponentMonitors
Paper analysisRead analysis
DefensesarXiv 2610.07256Oct 6
两阶段智能体轨迹审计框架：用门控规则加 LLM 审计降低监控成本
提出两阶段门控审计框架，在执行前阻断有害智能体动作
arXiv
2610.07256
Published
Oct 6
Layer
Application layer
Setting
AI Agent
Evaluated models
Claude Sonnet 5.5, Claude Haiku 4.5
- DefensesMonitoring and auditing
- RiskDangerous agent actions
- ComponentMonitors
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.06454Oct 5
AgentPrivArena：面向 LLM Agent 工作流的隐私风险评测框架
提出 AgentPrivArena 与运行时审计，评测 Agent 轨迹级隐私泄露
arXiv
2610.06454
Published
Oct 5
Layer
Application layer
Setting
AI Agent
Evaluated models
GPT-5.4, DeepSeek-V4-Pro, Kimi-K2.6 and others6
- DefensesMonitoring and auditing
- RiskDangerous agent actions
- ComponentMonitors
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.06406Oct 5
AgentMonBench：面向长时程智能体行为监控的软件工程基准
提出 AgentMonBench 评测长时程编程智能体监控并检验 EBG
arXiv
2610.06406
Published
Oct 5
Layer
Application layer
Setting
coding agent
Evaluated models
GPT-5.6 Luna, GPT-5.6 Terra, GPT-5.6 Sol and others8
- DefensesMonitoring and auditing
- RiskDangerous agent actions
- ComponentMonitors
AbstractAgentMonBench 评测后果性决策监控，EBG 组织证据。
长时程软件工程任务里，用户要判断智能体哪些选择值得核验。作者用 AgentMonBench 评测监控器，并用免训练的 EBG 组织带源证据。
Paper analysisRead analysis
DefensesarXiv 2609.35659Sep 29
Tracekit：面向自主编码 Agent 的防篡改意图-推理-动作审计系统
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
Analysis and theoryarXiv 2609.32390Sep 26
基于 2026 年 Hugging Face 事件的奖励作弊与 Agent 围堵失效蒙特卡洛研究
用五阶段蒙特卡洛分析奖励作弊如何导致 Agent 围堵失效
arXiv
2609.32390
Published
Sep 26
Layer
Application layer
Setting
AI Agent
- RiskReward hacking
- ComponentPermissions and sandboxing
Abstract分层控制的模拟事件率低于弱控制以及单独隔离或单独监控。
这项研究用蒙特卡洛把奖励黑客接到外部安全事件上，比较的是控制组合，不是 Hugging Face 事件的再现概率。
Paper analysisRead analysis
DefensesarXiv 2609.22724Sep 19
MATE：面向移动 Agent 的策略感知安全审计方法
提出移动 Agent 轨迹审计器 MATE，判断轨迹是否违反可编辑安全策略
arXiv
2609.22724
Published
Sep 19
Layer
Application layer
Setting
Browser and computer use
Attacker
Black-box
Evaluated models
MATE-0.5B, MATE-1.5B, MATE-3B
- DefensesMonitoring and auditing
- AttacksMalicious use
- RiskDangerous agent actions
- ComponentMonitors
AbstractMATE 用合成轨迹微调轻量审计器，在可编辑策略下判断移动智能体轨迹是否违规并给出解释。
MATE 是面向移动 GUI 智能体的轻量策略条件轨迹审计器，在给定自然语言安全策略时判断轨迹是否违规并解释原因。
Paper analysisRead analysis
DefensesarXiv 2609.15134Sep 14
HazardAuditor：面向计算机使用 Agent 的执行级安全护栏框架
提出 HazardAuditor，用可执行轨迹训练计算机使用 Agent 的运行时守卫
arXiv
2609.15134
Published
Sep 14
Layer
Application layer
Setting
Browser and computer use
Evaluated models
HazardAuditor, HazardAuditor-SFT
- DefensesMonitoring and auditing
- RiskDangerous agent actions
- ComponentMonitors
Paper analysisRead analysis
OtherarXiv 2609.06140Sep 5
论文提出反集群准则：以协调事件为单元遏制智能体协同入侵
提出以协调情节为单位遏制智能体协同入侵的准则
arXiv
2609.06140
Published
Sep 5
Layer
Application layer
Setting
Multi-agent systems
- RiskDangerous agent actions
- ComponentMonitors
Abstract立场是跨执行保留关系并约束共享状态。
Paper analysisRead analysis
DefensesarXiv 2607.19913Jul 22
Janus：面向长时程智能体安全的前瞻性潜在风险预测框架
提出 Janus 前瞻守卫，在长程智能体执行有害动作前拦截潜在风险
arXiv
2607.19913
Published
Jul 22
Layer
Application layer
Setting
AI Agent
Evaluated models
Vanguard
- DefensesMonitoring and auditing
- AttacksPrompt injection
- RiskDangerous agent actions
- ComponentMonitors
Paper analysisRead analysis

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