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network-forensics网络取证

Agent Skill

network-forensics 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

总安装

396

周安装

17

GitHub Stars

4

下载量

139
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:network-forensics(网络取证)
来源仓库:https://github.com/alphaonedev/openclaw-graph
仓库路径:skills/network-forensics
安装命令:
npx skills add https://github.com/alphaonedev/openclaw-graph --skill network-forensics
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/alphaonedev/openclaw-graph --skill network-forensics

简介

network-forensics 用于分析网络流量模式、识别异常行为并检测入侵、恶意通信或未授权访问。

  • 适用于安全事件调查、合规审计或高网络活动环境中的威胁监控与缓解。
  • 支持数据包捕获、日志分析和实时数据处理,聚焦于异常流量和攻击特征识别。
  • 安装前应评估是否需要网络抓包权限,并确保运行环境具备相应监控能力。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

network-forensics

Purpose

This skill enables the AI to investigate network traffic patterns, identify anomalies, and mitigate threats by analyzing packet captures, logs, and real-time data. It focuses on detecting intrusions, malware communications, and unauthorized access.

When to Use

Use this skill during security incidents, routine monitoring, or compliance audits. Apply it when network logs show unusual traffic spikes, unknown IP connections, or potential DDoS attacks. Ideal for blue-team operations in environments with high network activity, such as corporate networks or cloud infrastructures.

Key Capabilities

  • Parse PCAP files to extract metadata like source/destination IPs, ports, and protocols.
  • Detect anomalies using rulesets, e.g., identifying SYN floods or unusual port scans.
  • Generate reports in JSON or CSV format for threat intelligence.
  • Integrate with tools like tcpdump for live capture or Zeek for advanced protocol analysis.
  • Support real-time monitoring via API hooks to flag threats immediately.

Usage Patterns

To use this skill, first authenticate with an API key via environment variable (e.g., $NETWORK_FORENSICS_API_KEY). Invoke it programmatically in Python scripts or via CLI for analysis tasks. For file-based analysis, provide a PCAP file; for live monitoring, specify a network interface. Always wrap calls in error-handling blocks to manage failures. Chain with other blue-team skills for automated workflows, like feeding results to an intrusion detection system.

Common Commands/API

Use the following CLI commands or API endpoints for core operations:

  • CLI: Analyze a PCAP file: openclaw network-forensics analyze --file path/to/capture.pcap --output report.json
  • CLI: Monitor live traffic: openclaw network-forensics monitor --interface eth0 --duration 300 --alert-level high
  • API Endpoint: POST to /api/network/analyze with JSON body: {"file": "base64_encoded_pcap", "rules": ["syn_flood", "port_scan"]}. Set header: Authorization: Bearer $NETWORK_FORENSICS_API_KEY
  • API Endpoint: GET from /api/network/status to check ongoing sessions: Response includes active alerts in JSON format.
  • Code Snippet (Python): import requests api_key = os.environ.get('NETWORK_FORENSICS_API_KEY') response = requests.post('https://api.openclaw.com/api/network/analyze', headers={'Authorization': f'Bearer {api_key}'}, json={'file': 'capture.pcap'}) print(response.json()['threats'])
  • Config Format: Use YAML for rulesets, e.g.: rules: - name: syn_flood threshold: 1000 packets/sec - name: port_scan ports: [80, 443, 22]

Integration Notes

Integrate this skill with other tools by exporting results to SIEM systems like Splunk or ELK Stack. For authentication, always use $NETWORK_FORENSICS_API_KEY in environment variables. In code, handle dependencies like installing scapy for PCAP processing: pip install scapy. To combine with other OpenClaw skills, use the SDK: e.g., call network-forensics output as input to intrusion-detection. Ensure network interfaces are configured for capture, e.g., via sudo setcap cap_net_raw+ep /path/to/openclaw binary. Test integrations in a sandbox environment to avoid production disruptions.

Error Handling

Always check for common errors like invalid PCAP files, network timeouts, or authentication failures. In CLI, errors return exit codes (e.g., 1 for file not found). In API calls, parse HTTP status codes: 401 for unauthorized (check $NETWORK_FORENSICS_API_KEY), 400 for bad requests. Use try-except in code snippets:

try:
    response = requests.post('https://api.openclaw.com/api/network/analyze', ...)
    response.raise_for_status()
except requests.exceptions.HTTPError as err:
    print(f"Error: {err} - Verify API key and input format")
except Exception as e:
    print(f"Unexpected error: {e} - Retry with debug flag")

Log errors with timestamps and retry transient issues up to 3 times. For CLI, add --debug flag to output detailed traces.

Concrete Usage Examples

  1. Analyze a captured PCAP file for threats: Suppose you have a file suspicious.pcap from a potential breach. Run: openclaw network-forensics analyze --file suspicious.pcap --rules syn_flood. This outputs a JSON report with detected threats. In code: Use the API to process it and alert if threats > 5, then integrate with email notification.
  2. Monitor live traffic for intrusions: On a server with interface eth0, execute: openclaw network-forensics monitor --interface eth0 --duration 600 --alert-level medium. This captures packets for 10 minutes and flags anomalies like port scans. Script it in a loop for continuous monitoring, e.g., in a cron job, and pipe results to a database for long-term analysis.

Graph Relationships

  • Related to: "intrusion-detection" (shares threat detection logic)
  • Depends on: "log-analysis" (for correlating network logs)
  • Complements: "endpoint-security" (for holistic blue-team defense)
  • Clusters with: "blue-team" skills like "vulnerability-scanning"

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.89%
按下载量换算50

Claude

31.03%
按下载量换算43

Cursor

17.98%
按下载量换算25

Gemini CLI

10.5%
按下载量换算15

安全审计

Gen Agent Trust Hub

未通过

Socket

未通过

Snyk

可疑

权限和风险

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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