Compliance Audit

核心功能为生成哈希链式不可篡改的审计日志，支持记录自主代理的技能执行、决策、数据访问、预算变更等操作；可查询日志、校验完整性、导出多格式文件、生成合规摘要。典型场景包括企业合规、事件响应、预算问责、信任验证及代理调试，通过Python脚本命令输入，输出结构化日志、查询结果等。

trypto1019

热度 90.16

最近更新 2026-05-17 12:06:56

分类：安全依赖：代码执行 / 读写文件应用场景：法律文档 / 报告撰写

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add arc-compliance-audit

Metadata

name: compliance-audit
description: Immutable audit trail for autonomous agent operations. Log skill executions, data access, decisions, and budget changes with tamper-evident hashes. Essential for enterprise governance, incident response, and trust verification.
user-invocable: true
metadata: {"openclaw":{"emoji":"📋","os":["darwin","linux"],"requires":{"bins":["python3"]}}}

Compliance Audit Trail

Immutable, tamper-evident audit logging for autonomous agents. Every action gets a hash-chained entry that can be verified for integrity.

Why This Exists

Autonomous agents make decisions, execute skills, access data, and spend money without human oversight. When something goes wrong, you need to know exactly what happened. Current agent frameworks have no standard audit trail — this fills that gap.

Commands

Log an action

python3 {baseDir}/scripts/audit.py log --action "skill_executed" --details '{"skill": "scanner", "target": "some-skill", "result": "clean"}'

Log a decision

python3 {baseDir}/scripts/audit.py log --action "decision" --details '{"choice": "deploy v2", "reason": "all tests passed", "alternatives_considered": ["rollback", "hotfix"]}'

Log data access

python3 {baseDir}/scripts/audit.py log --action "data_access" --details '{"resource": "api_key", "purpose": "moltbook_post", "accessor": "ghost_agent"}'

Log a budget change

python3 {baseDir}/scripts/audit.py log --action "budget_change" --details '{"amount": -10.00, "merchant": "namecheap", "reason": "domain purchase", "balance_after": 190.00}'

View recent entries

python3 {baseDir}/scripts/audit.py view --last 20

View entries by action type

python3 {baseDir}/scripts/audit.py view --action skill_executed

View entries in a time range

python3 {baseDir}/scripts/audit.py view --since "2026-02-15T00:00:00" --until "2026-02-16T00:00:00"

Verify audit trail integrity

python3 {baseDir}/scripts/audit.py verify

Export audit trail

python3 {baseDir}/scripts/audit.py export --format json > audit-export.json
python3 {baseDir}/scripts/audit.py export --format csv > audit-export.csv

Generate compliance summary

python3 {baseDir}/scripts/audit.py summary --period day

Entry Format

Each audit entry contains:

timestamp — ISO 8601, UTC
action — what happened (skill_executed, decision, data_access, budget_change, error, custom)
agent — which agent performed the action
details — structured JSON with action-specific data
hash — SHA-256 hash chaining previous entry's hash + current entry (tamper-evident)
sequence — monotonically increasing sequence number

Integrity Verification

The audit trail is hash-chained: each entry includes a SHA-256 hash of the previous entry's hash concatenated with the current entry's data. If any entry is modified or deleted, the chain breaks and verify will report the exact point of tampering.

Storage

Audit logs are stored in ~/.openclaw/audit/ as daily JSON files (audit-YYYY-MM-DD.json). This keeps individual files small while maintaining the full history.

Use Cases

Incident response: What happened in the 5 minutes before the error?
Budget accountability: Show every dollar spent and why
Trust verification: Prove your agent hasn't been compromised
Enterprise compliance: Meet audit requirements for autonomous systems
Debugging: Trace the decision chain that led to an unexpected outcome