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Agent Skill · 效率

agentshield(agentshield 效率)

agentshield 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中需要复核安全边界、认证流程或敏感配置时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

agentshield 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 6,127。

总安装 9,789周安装 396GitHub Stars 公开资料未说明下载 3,073核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
2.0.2

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agentshield(agentshield 效率)
来源仓库:https://github.com/markbriers/agentshield
安装命令:
openclaw skills install agentshield
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install agentshield

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

agentshield 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中复核安全边界。使用 Sigma 规则和 LLM 支持的分类进行实时安全监控。通过 clawhub 安装,结合来源仓库和 README 文档核验具体用法。安装前需确认权限范围、维护状态及是否涉及联网、命令执行或文件读写。

适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install agentshield;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agentshield 怎么安装?

在终端执行 openclaw skills install agentshield。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agentshield 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agentshield 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

agentshield 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

agentshield 用的人多吗?

公开数据是累计安装 9,789 次,近一周安装 396 次,下载 3,073 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agentshield 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
agentshield

agentshield 效率 · 本页

9,789—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
agentshield
description
AI Agent Detection & Response — real-time security monitoring with Sigma rules and LLM-powered triage
homepage
https://github.com/agentshield-ai/agentshield
user-invocable
true
metadata
{"openclaw":{"requires":{"anyBins":["go","curl"]},"os":["darwin","linux"]}}

AgentShield

AI Agent Detection & Response (AADR) — real-time security monitoring with Sigma rules and LLM-powered triage.

What is AgentShield?

AgentShield is a Go security engine that monitors AI agent tool calls in real-time. It evaluates each call against Sigma security rules and optionally routes suspicious events through LLM triage for context-aware verdicts. It runs as a single binary with no external runtime dependencies.

Architecture

Single Go binary (agentshield) containing:

  • HTTP server (Chi router, 127.0.0.1:8433 by default)
  • Sigma rule engine (forked sigmalite in pkg/sigma/)
  • SQLite alert/feedback store
  • LLM triage (OpenAI or Anthropic provider, optional)
  • Bearer token authentication (constant-time comparison)
  • Per-IP rate limiting (~100 req/min, burst 10)

One systemd user service: agentshield-engine.service (Linux) or one launchd agent: ai.agentshield.engine (macOS).

Installation

Quick Install

./install.sh

The installer:

  1. Detects platform (linux/darwin) and architecture (amd64/arm64)
  2. Downloads binary from GitHub releases (falls back to go install)
  3. Creates ~/.agentshield/ directory (rules, config, database)
  4. Clones sigma-ai rules from agentshield-ai/sigma-ai
  5. Generates a 64-character auth token
  6. Writes ~/.agentshield/config.yaml
  7. Creates a systemd user service (Linux) or launchd agent (macOS)
  8. Patches OpenClaw plugin configuration via openclaw config patch
  9. Starts the service and runs a health check

Manual Installation

# Build from source
go build ./cmd/agentshield/

# Create directory structure
mkdir -p ~/.agentshield/rules

# Clone rules
git clone --depth 1 https://github.com/agentshield-ai/sigma-ai.git ~/.agentshield/rules

# Generate auth token
openssl rand -hex 32

# Create config.yaml (see Configuration section)
# Start the engine
~/.agentshield/agentshield-engine serve --config ~/.agentshield/config.yaml

Configuration

Config file: ~/.agentshield/config.yaml

server:
  addr: "127.0.0.1"
  port: 8433

auth:
  token: "your-64-char-token-here"

rules:
  dir: "~/.agentshield/rules"
  hot_reload: true

store:
  sqlite_path: "~/.agentshield/agentshield.db"
  retention_days: 90
  cleanup_interval_hours: 24

evaluation_mode: "enforce"   # enforce | audit | shadow

log_level: "info"

# triage:
#   enabled: true
#   provider: "openai"        # openai | anthropic
#   model: "gpt-4o-mini"
#   api_key: "sk-..."
#   max_tokens: 500
#   timeout_sec: 10
#   health_check_mode: "full"  # full | connectivity

Environment Variable Overrides

VariableOverrides
AGENTSHIELD_PORTserver.port
AGENTSHIELD_ADDRserver.addr
AGENTSHIELD_AUTH_TOKENauth.token
AGENTSHIELD_RULES_DIRrules.dir
AGENTSHIELD_DB_PATHstore.sqlite_path
AGENTSHIELD_MODEevaluation_mode
AGENTSHIELD_LOG_LEVELlog_level
AGENTSHIELD_TRIAGE_API_KEYtriage.api_key

Authentication

A 32+ character token is mandatory. Without it, the server refuses to start. The installer generates a 64-character hex token automatically.

# Generate manually
openssl rand -hex 32

# Or via Python
python3 -c "import secrets; print(secrets.token_hex(32))"

Evaluation Modes

  • enforce: Blocks tool calls matching rules. Use in production.
  • audit: Logs alerts without blocking. Default for testing.
  • shadow: Silent monitoring. No user-visible alerts.

CLI Commands

# Start the server
agentshield serve --config ~/.agentshield/config.yaml [--daemon] [--verbose]

# Check server status (queries /api/v1/health)
agentshield status [--verbose]

# List recent alerts
agentshield alerts [-l LIMIT] [-s SEVERITY] [--since RFC3339] [-r RULE]

# List loaded rules
agentshield rules list

# Reload rules (sends SIGHUP to running server)
agentshield rules reload

# Analyze rule performance using feedback data
agentshield refine [rule-name] [--apply] [--threshold FP_RATE]

# Show version
agentshield version

Service Management

Linux (systemd user service):

systemctl --user status agentshield-engine
systemctl --user start agentshield-engine
systemctl --user stop agentshield-engine
systemctl --user restart agentshield-engine
journalctl --user -u agentshield-engine -f

macOS (launchd):

launchctl load ~/Library/LaunchAgents/ai.agentshield.engine.plist
launchctl unload ~/Library/LaunchAgents/ai.agentshield.engine.plist
tail -f ~/.agentshield/engine.log

API Endpoints

All endpoints are under /api/v1/. Authentication via Authorization: Bearer <token> header.

EndpointMethodDescription
/api/v1/evaluatePOSTEvaluate a tool call against rules + triage
/api/v1/healthGETHealth check (minimal info, works unauthenticated)
/api/v1/alertsGETQuery stored alerts (paginated, filterable)
/api/v1/feedbackPOSTSubmit alert feedback (false_positive, true_positive, improvement)
/api/v1/feedback?rule=<name>GETQuery feedback + FP rate for a rule

Server Limits

  • Max request body: 1 MB
  • Max field value: 10 KB
  • Max fields per request: 100
  • Rate limit: ~100 req/min per IP, burst 10
  • Request timeout: 30 seconds

LLM Triage

Optional. When enabled, the engine sends suspicious events to an LLM for context-aware analysis.

Supported providers: openai, anthropic.

triage:
  enabled: true
  provider: "openai"
  model: "gpt-4o-mini"
  api_key: "sk-..."
  max_tokens: 500
  timeout_sec: 10
  health_check_mode: "full"   # "full" runs a model call; "connectivity" just checks /v1/models

Triage returns a verdict (block, allow, investigate), confidence (0-1), and reasoning. In the OpenClaw plugin, a high-confidence allow (>0.8) from triage overrides rule-based alerts.

Sigma Rules

Rules are stored in ~/.agentshield/rules/. The engine loads all .yml/.yaml files from this directory.

Rule Format

Standard Sigma format adapted for agent tool monitoring:

title: Suspicious File Access
id: file-access-monitor
description: Monitor for access to sensitive system files
logsource:
  category: agent-tool
detection:
  selection:
    tool: file_operation
    path|contains:
      - '/etc/passwd'
      - '/etc/shadow'
      - '.ssh/'
  condition: selection
level: medium

Managing Rules

  • Hot reload is enabled by default (rules.hot_reload: true)
  • Manual reload: agentshield rules reload (sends SIGHUP)
  • List loaded rules: agentshield rules list
  • Rules repository: agentshield-ai/sigma-ai

OpenClaw Integration

The plugin registers as agentshield in OpenClaw's plugin system. The installer patches OpenClaw config automatically:

{
  "plugins": {
    "entries": {
      "agentshield": {
        "enabled": true,
        "config": {
          "enabled": true,
          "endpoint": "http://127.0.0.1:8433/api/v1/evaluate",
          "auth_token": "<generated-token>",
          "timeout_ms": 200,
          "timeout_policy": "block"
        }
      }
    }
  }
}

Plugin hooks registered:

  • before_tool_call (priority -100): Synchronous evaluation with timeout
  • after_tool_call: Fire-and-forget audit report
  • session_start, session_end, before_agent_start, agent_end: Lifecycle events

See the plugin README for full plugin documentation.

Troubleshooting

Engine Won't Start

# Check logs
journalctl --user -u agentshield-engine -n 50

# Run with verbose output
agentshield serve --config ~/.agentshield/config.yaml --verbose

# Test health endpoint
curl -s -H "Authorization: Bearer YOUR_TOKEN" http://127.0.0.1:8433/api/v1/health

Common Issues

  • Auth token too short: Must be 32+ characters. Regenerate with openssl rand -hex 32.
  • Port conflict: Check netstat -an | grep 8433. Change server.port in config.
  • Rules not loading: Verify rules.dir path exists and contains .yml files.
  • Triage timeouts: Increase triage.timeout_sec or switch to health_check_mode: "connectivity".

Testing the Engine Directly

curl -X POST http://127.0.0.1:8433/api/v1/evaluate \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "event_id": "test-001",
    "tool_name": "exec",
    "command": "ls -la",
    "params": {"command": "ls -la"},
    "fields": {"tool": "exec", "command": "ls -la"}
  }'

File Locations

FilePath
Binary~/.agentshield/agentshield-engine
Config~/.agentshield/config.yaml
Rules~/.agentshield/rules/
Database~/.agentshield/agentshield.db
Systemd service~/.config/systemd/user/agentshield-engine.service
Launchd plist~/Library/LaunchAgents/ai.agentshield.engine.plist

Uninstallation

cd plugins/openclaw/skill
./uninstall.sh

This stops the service, removes ~/.agentshield/, reverts OpenClaw plugin config, and cleans up PATH references.

License

Apache 2.0

平台分布

OpenClaw

77.62%
按下载量换算2,385

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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