论文《Defense-as-Skill》提出运行期防护技能 SkillSonar,在智能体执行过程中检查敏感操作,并决定放行、收窄、重规划或先询问用户。在 GLM-5 上,它把熟悉攻击类型的攻击成功率从 48.2% 降至 10.4%,未见风险类型从 60.6% 降至 11.5%。作者指出仅安装该安全技能效果明显更弱,必须显式提示智能体在行动前查询它,同时仍需保留权限与沙箱等硬防护。
A malicious agent skill can look safe when installed and turn dangerous only during a real task, so this paper argues that agents need runtime safety checks, not just pre-install scanning.
The problem is timing: a bad skill can wait until the agent has access to useful files, tools, credentials, or external services before pushing it beyond what the user actually asked for.
The paper proposes SkillSonar, a safety skill that checks sensitive actions while the agent is working and decides whether to allow them, narrow them, replan, or ask the user first.
On GLM-5, it cut attack success from 48.2% to 10.4% on familiar attack types and from 60.6% to 11.5% on unseen risk families.
A crucial result: simply installing the safety skill was much weaker.
The agent had to be explicitly told to consult it before acting.
overall, the paper says scan skills before installation, check their actions during execution, and still keep hard protections like permissions and sandboxing underneath.
– arxiv. org/abs/2609.01487
Title: "Defense-as-Skill: Evolving Runtime Guard Skill for Skill-Augmented Agents"
来源:@rohanpaul_ai · x.com