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 2609.34519
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
- OtherarXiv 2609.12413
SoK 综述：智能体 AI 时代的越狱攻击、防御与实践考量
系统梳理智能体执行链路中的越狱攻击与防御并比较推理时防御
- arXiv
- 2609.12413
- Published
- Layer
- Application layer
- Setting
- AI Agent
- Evaluated models
- Qwen3.5-4B, Llama-3.1-8B-Instruct
- AttacksJailbreaks
- ComponentMemory
AbstractSoK 将越狱重放到智能体流水线，并用两种模型检验回复层防御的边际与代价。
Mia 等人把越狱安全从单轮回复扩展到智能体的规划、记忆、工具和智能体间通信，并问既有结论在更强原生对齐下是否还成立。
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
- 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
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