AgentSkillsCN

agent-security-governance

为自主智能体构筑全方位的安全防护层。通过制定系统指令作为“宪法”，实施多阶段过滤机制，以及持续开展红队演练，全面提升智能体的安全性。

SKILL.md
--- frontmatter
name: agent-security-governance
description: comprehensive security layers for autonomous agents. Use this to implement system instructions as constitutions, multi-stage filtering, and continuous red-teaming.

Agent Security & Governance

Goal

Build trust and safety into the agentic lifecycle by implementing multi-layered defenses that manage risks unique to autonomous systems, such as rogue actions and data leakage.

Core Risks of Autonomy

Autonomous agents make independent decisions, which introduces distinct security vulnerabilities:

  • •Prompt Injection: Malicious users tricking agents into bypassing restrictions or performing unintended actions.
  • •Data Leakage: Inadvertent exposure of sensitive or confidential information through agent responses or tool outputs.
  • •Memory Poisoning: Corruption of future interactions by storing false or malicious information in the agent's long-term state.

The Three Layers of Defense

1. Policy Definition (The Constitution)

  • •System Instructions (SIs): Engineer clear policies for desired and undesired behavior directly into the agent's core instructions.
  • •Scope Definition: Explicitly define the boundaries of what the agent can and cannot do.

2. Enforcement Layer (Guardrails)

  • •Input Filtering: Use classifiers to analyze user prompts and block malicious intents before they reach the reasoning model.
  • •Output Filtering: Run agent responses through safety filters to check for PII, toxic language, or policy violations before delivery.
  • •HITL Escalation: Program the system to pause and require human approval for high-risk or ambiguous actions, such as financial transactions or data deletion.

3. Continuous Assurance (Testing)

  • •Dedicated RAI Testing: Use simulation agents and dedicated datasets to test for specific risks like bias (Parity evaluations) or harmful viewpoints (NPOV).
  • •Proactive Red Teaming: Actively attempt to break the system through creative manual testing and AI-driven adversarial simulations.
  • •Continuous Re-evaluation: Trigger a full safety evaluation pipeline for every change made to the model or its instruction set.

Secure Response Playbook

When a threat is detected in production, follow this sequence:

  1. •Contain: Immediately stop the harm using "circuit breakers" or feature flags.
  2. •Triage: Route suspicious requests to a human review queue to investigate impact.
  3. •Resolve: Develop a permanent logic patch and deploy it through the automated CI/CD pipeline.