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Agent Skill · 研究检索

shannon(shannon 测试)

shannon 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

shannon 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 3,647。

总安装 41,616周安装 1,655GitHub Stars 26下载 13,328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
unknown

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:shannon(shannon 测试)
来源仓库:https://github.com/unicodeveloper/shannon
仓库路径:skills/shannon
安装命令:
npx skills add https://github.com/unicodeveloper/shannon --skill shannon
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/unicodeveloper/shannon --skill shannon

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

自主人工智能渗透测试仪可分析源代码、识别漏洞并执行真实的漏洞利用以证明安全缺陷。

涵盖 OWASP Top 10 类别:注入、XSS、SSRF、破坏身份验证和破坏授权,在安全基准测试中利用成功率为 96.15% 测试前需要明确的书面授权;包括强制性安全检查,以防止生产系统意外成为目标 在带有集成安全工具(Nmap、Subfinder、WhatWeb、Schemathesis、headless Chromium)的 Docker 中运行,并支持通过 YAML 进行登录流程的身份验证配置 为每个发现生成包含可重复的概念验证漏洞的详细报告;每个报告的漏洞都包含一个有效的 PoC

来源仓库内路径:skills/shannon

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/unicodeveloper/shannon --skill shannon;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

shannon 怎么安装?

在终端执行 npx skills add https://github.com/unicodeveloper/shannon --skill shannon。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

shannon 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

shannon 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。

shannon 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

shannon 用的人多吗?

公开数据是累计安装 41,616 次,近一周安装 1,655 次,下载 13,328 次,GitHub 26 星。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。

shannon 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、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。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
shannon

shannon 测试 · 本页

41,61626接触敏感数据未明确有提醒

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

Shannon: Autonomous AI Pentester for Web Apps & APIs

Permissions overview: This skill orchestrates Shannon, a Docker-based pentesting tool that actively executes attacks against a target application. It clones/updates the Shannon repo locally, runs Docker containers, and reads pentest reports. Shannon performs real exploits — only run against apps you own or have explicit written authorization to test. Never run against production systems.

Shannon analyzes your source code, identifies attack vectors, and executes real exploits to prove vulnerabilities before they reach production. 96.15% exploit success rate on the XBOW security benchmark. Covers OWASP Top 10: Injection, XSS, SSRF, Broken Auth, Broken AuthZ, and more.


CRITICAL: Safety Checks (ALWAYS run first)

Before doing ANYTHING, you MUST confirm:

  1. Authorization: Ask the user — "Do you have explicit authorization to pentest this target?" If they say no or are unsure, STOP and explain they need written permission from the system owner.
  2. Environment: Confirm the target is a local, staging, or sandboxed environment — NEVER production.
  3. Scope: Clarify what they want tested (full pentest vs specific category).
⚠️  Shannon executes REAL ATTACKS with mutative effects.
├─ Only run on systems you OWN or have WRITTEN AUTHORIZATION to test
├─ Never target production environments
├─ Results require human review — LLM output may contain hallucinations
└─ You are responsible for complying with all applicable laws

Display this warning BEFORE every pentest run. If the user has already confirmed authorization in this session, a brief reminder suffices.


Parse User Intent

Extract from the user's input:

  1. TARGET_URL: The URL to pentest (e.g., http://localhost:3000, http://staging.example.com)
  2. REPO_NAME: The source code folder name (placed in ./repos/ inside Shannon)
  3. SCOPE: Full pentest (default) or specific categories (injection, xss, ssrf, auth, authz)
  4. WORKSPACE: Named workspace for resume capability (optional)
  5. CONFIG: Custom YAML config path (optional, for auth flows, focus/avoid rules)

Common invocation patterns:

  • /shannon http://localhost:3000 myapp → Full pentest of local app
  • /shannon --workspace=audit1 http://staging.example.com backend-api → Named workspace for resuming
  • /shannon --scope=xss,injection http://localhost:8080 frontend → Targeted categories
  • /shannon status → Check running pentests
  • /shannon results → Show latest report
  • /shannon stop → Stop running pentest

Display parsed intent:

🔐 Shannon Pentest
├─ Target: {TARGET_URL}
├─ Source: repos/{REPO_NAME}
├─ Scope: {SCOPE or "Full (all 5 OWASP categories)"}
├─ Workspace: {WORKSPACE or "auto-generated"}
└─ Config: {CONFIG or "default"}

Estimated runtime: 1–1.5 hours │ Estimated cost: ~$50 (Claude Sonnet)

Step 0: Ensure Shannon is Installed

Check if Shannon is cloned locally:

SHANNON_HOME="${SHANNON_HOME:-$HOME/shannon}"

if [ -d "$SHANNON_HOME" ] && [ -f "$SHANNON_HOME/shannon" ]; then
  echo "Shannon found at $SHANNON_HOME"
  cd "$SHANNON_HOME" && git pull --ff-only 2>/dev/null || true
else
  echo "Shannon not found. Cloning..."
  git clone https://github.com/KeygraphHQ/shannon.git "$SHANNON_HOME"
fi

# Verify Docker is available
if command -v docker &>/dev/null; then
  echo "Docker: $(docker --version)"
else
  echo "ERROR: Docker is required. Install Docker Desktop: https://docker.com/products/docker-desktop"
  exit 1
fi

If Shannon is not installed, clone it and inform the user. If Docker is missing, stop and tell them to install it.

SHANNON_HOME defaults to ~/shannon. Users can override with SHANNON_HOME env var.


Step 1: Prepare Source Code

Shannon needs the target's source code in $SHANNON_HOME/repos/{REPO_NAME}/.

Ask the user where their source code is:

# If user provides a local path
REPO_PATH="/path/to/their/source"
REPO_NAME="myapp"

# Create symlink or copy into Shannon's repos directory
mkdir -p "$SHANNON_HOME/repos"
if [ ! -d "$SHANNON_HOME/repos/$REPO_NAME" ]; then
  ln -s "$(realpath "$REPO_PATH")" "$SHANNON_HOME/repos/$REPO_NAME"
  echo "Linked $REPO_PATH → repos/$REPO_NAME"
fi

If the user provides a GitHub URL instead:

cd "$SHANNON_HOME/repos"
git clone "$GITHUB_URL" "$REPO_NAME"

Step 2: Configure Authentication (if needed)

If the target requires login, help the user create a YAML config:

# $SHANNON_HOME/configs/target-config.yaml
authentication:
  type: form            # "form" or "sso"
  login_url: "http://localhost:3000/login"
  credentials:
    username: "admin"
    password: "password123"
  flow: "Navigate to login page, enter username and password, click Sign In"
  success_condition:
    url_contains: "/dashboard"

rules:
  avoid:
    - "/logout"
    - "/admin/delete"
  focus:
    - "/api/"
    - "/auth/"

pipeline:
  max_concurrent_pipelines: 5  # 1-5, default 5

Only create a config if the target requires authentication or has specific scope rules. For open/unauthenticated targets, no config is needed.


Step 3: Verify API Credentials

Check that AI provider credentials are available:

cd "$SHANNON_HOME"

# Check for Anthropic API key (primary)
if [ -n "${ANTHROPIC_API_KEY:-}" ]; then
  echo "✅ ANTHROPIC_API_KEY is set"
elif [ -n "${CLAUDE_CODE_OAUTH_TOKEN:-}" ]; then
  echo "✅ CLAUDE_CODE_OAUTH_TOKEN is set"
elif [ "${CLAUDE_CODE_USE_BEDROCK:-}" = "1" ]; then
  echo "✅ AWS Bedrock mode enabled"
elif [ "${CLAUDE_CODE_USE_VERTEX:-}" = "1" ]; then
  echo "✅ Google Vertex AI mode enabled"
else
  echo "❌ No AI credentials found."
  echo "Set one of: ANTHROPIC_API_KEY, CLAUDE_CODE_OAUTH_TOKEN, or enable Bedrock/Vertex"
  exit 1
fi

If no credentials are found, explain the options:

  • Direct API (recommended): export ANTHROPIC_API_KEY=sk-ant-...
  • OAuth: export CLAUDE_CODE_OAUTH_TOKEN=...
  • AWS Bedrock: export CLAUDE_CODE_USE_BEDROCK=1 + AWS credentials
  • Google Vertex: export CLAUDE_CODE_USE_VERTEX=1 + service account in ./credentials/

Also recommend: export CLAUDE_CODE_MAX_OUTPUT_TOKENS=64000


Step 4: Launch the Pentest

CRITICAL: Confirm with the user before launching. Display the full command and wait for approval.

cd "$SHANNON_HOME"

# Build the command
CMD="./shannon start URL={TARGET_URL} REPO={REPO_NAME}"

# Add optional flags
# CONFIG=configs/target-config.yaml  (if auth config exists)
# WORKSPACE={WORKSPACE}              (if user specified)
# OUTPUT=./audit-logs/               (default)

echo "Ready to launch:"
echo "  $CMD"
echo ""
echo "This will start Docker containers and begin the pentest."
echo "Runtime: ~1-1.5 hours │ Cost: ~\$50 (Claude Sonnet)"

After user confirms, run in background:

cd "$SHANNON_HOME" && ./shannon start URL={TARGET_URL} REPO={REPO_NAME} {EXTRA_FLAGS}

Use run_in_background: true with a timeout of 600000ms (10 minutes for initial setup). The pentest itself runs in Docker and will continue independently.


Step 5: Monitor Progress

While the pentest runs, the user can check status:

cd "$SHANNON_HOME"

# List active workspaces
./shannon workspaces

# View logs for a specific workflow
./shannon logs ID={workflow-id}

Explain the 5-phase pipeline:

Shannon Pipeline (5 phases, parallel where possible):
├─ Phase 1: Pre-Recon — Source code analysis + external scans (Nmap, Subfinder, WhatWeb)
├─ Phase 2: Recon — Live attack surface mapping via browser automation
├─ Phase 3: Vulnerability Analysis — 5 parallel agents (Injection, XSS, SSRF, Auth, AuthZ)
├─ Phase 4: Exploitation — Dedicated agents execute real attacks to validate findings
└─ Phase 5: Reporting — Executive summary with reproducible PoCs

Step 6: Read and Interpret Results

Reports are saved to $SHANNON_HOME/audit-logs/{hostname}_{sessionId}/.

cd "$SHANNON_HOME"

# Find the latest report
LATEST=$(ls -td audit-logs/*/ 2>/dev/null | head -1)
if [ -n "$LATEST" ]; then
  echo "Latest report: $LATEST"
  # Find the main report file
  find "$LATEST" -name "*.md" -type f | head -5
fi

Read the report and present a summary:

🔐 Shannon Pentest Report: {TARGET}
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

🔴 Critical: {N} vulnerabilities
🟠 High:     {N} vulnerabilities
🟡 Medium:   {N} vulnerabilities
🔵 Low:      {N} vulnerabilities

Top Findings:
1. [CRITICAL] {Vuln type} — {location} — PoC: {brief description}
2. [HIGH] {Vuln type} — {location} — PoC: {brief description}
3. ...

Each finding includes a reproducible proof-of-concept exploit.

IMPORTANT: Shannon's "no exploit, no report" policy means every finding has a working PoC. But remind the user that LLM-generated content requires human review.


Utility Commands

Check status

cd "$SHANNON_HOME" && ./shannon workspaces

View logs

cd "$SHANNON_HOME" && ./shannon logs ID={workflow-id}

Stop pentest

cd "$SHANNON_HOME" && ./shannon stop

Stop and clean up all data

# DESTRUCTIVE — confirm with user first
cd "$SHANNON_HOME" && ./shannon stop CLEAN=true

Resume a previous workspace

cd "$SHANNON_HOME" && ./shannon start URL={URL} REPO={REPO} WORKSPACE={name}

Targeting Local Apps

If the user's app runs on localhost, explain:

Shannon runs inside Docker. To reach your local app:
├─ Use http://host.docker.internal:{PORT} instead of http://localhost:{PORT}
├─ macOS/Windows: works automatically with Docker Desktop
└─ Linux: add --add-host=host.docker.internal:host-gateway to docker run

Automatically translate localhost URLs to host.docker.internal in the command.


Configuration Reference

Environment Variables

VariableRequiredDescription
ANTHROPIC_API_KEYOne of theseDirect Anthropic API key
CLAUDE_CODE_OAUTH_TOKENrequiredAnthropic OAuth token
CLAUDE_CODE_USE_BEDROCKSet to 1 for AWS Bedrock
CLAUDE_CODE_USE_VERTEXSet to 1 for Google Vertex AI
CLAUDE_CODE_MAX_OUTPUT_TOKENSRecommendedSet to 64000
SHANNON_HOMEOptionalShannon install dir (default: ~/shannon)

YAML Config Options

SectionFieldDescription
authentication.typeform / ssoLogin method
authentication.login_urlURLLogin page
authentication.credentialsobjectusername, password, totp_secret
authentication.flowstringNatural language login instructions
authentication.success_conditionobjecturl_contains or element_present
rules.avoidlistPaths/subdomains to skip
rules.focuslistPaths/subdomains to prioritize
pipeline.retry_presetsubscriptionExtended backoff for rate-limited plans
pipeline.max_concurrent_pipelines1-5Parallel agent count (default: 5)

Vulnerability Coverage

Shannon tests 50+ specific cases across 5 OWASP categories:

CategoryExamples
InjectionSQL injection, command injection, SSTI, NoSQL injection
XSSReflected, stored, DOM-based, via file upload
SSRFInternal service access, cloud metadata, protocol smuggling
Broken AuthDefault creds, JWT flaws, session fixation, MFA bypass, CSRF
Broken AuthZIDOR, privilege escalation, path traversal, forced browsing

Integrated Security Tools (bundled in Docker)

  • Nmap — port scanning and service detection
  • Subfinder — subdomain enumeration
  • WhatWeb — web technology fingerprinting
  • Schemathesis — API schema-based fuzzing
  • Chromium — headless browser for automated exploitation (Playwright)

Context Memory

For the rest of this conversation, remember:

  • SHANNON_HOME: Path to Shannon installation
  • TARGET_URL: The URL being tested
  • REPO_NAME: Source code folder name
  • WORKSPACE: Workspace name (if any)
  • PENTEST_STATUS: running / completed / stopped

When the user asks follow-up questions:

  • Check pentest status and report on progress
  • Read and interpret new findings from audit-logs
  • Help remediate discovered vulnerabilities with code fixes
  • Explain PoC exploits and their impact

Security & Permissions

What this skill does:

  • Clones/updates the Shannon repo from GitHub to ~/shannon (or $SHANNON_HOME)
  • Creates symlinks from user's source code into ~/shannon/repos/
  • Starts Docker containers (Temporal server, worker, optional router) via ./shannon CLI
  • Reads pentest reports from ~/shannon/audit-logs/
  • Optionally creates YAML config files in ~/shannon/configs/

What Shannon does (inside Docker):

  • Executes real exploits against the target URL (SQL injection, XSS, SSRF, etc.)
  • Scans with Nmap, Subfinder, WhatWeb, Schemathesis
  • Automates browser interactions via headless Chromium
  • Sends prompts to Anthropic API (or Bedrock/Vertex) for reasoning
  • Writes reports to audit-logs/ directory

What this skill does NOT do:

  • Does not target any system without user confirmation
  • Does not store or transmit API keys beyond the configured provider
  • Does not modify the user's source code
  • Does not access production systems unless explicitly directed (which it warns against)
  • Does not run without Docker — all attack tools are containerized

Review the Shannon source code before first use: https://github.com/KeygraphHQ/shannon

平台分布

Codex

37.19%
按下载量换算4,957

Claude

28.72%
按下载量换算3,828

Cursor

20.14%
按下载量换算2,684

Gemini CLI

9.87%
按下载量换算1,315

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

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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