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Agent Skill · 研究检索

pentest-validation(渗透测试验证)

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

pentest-validation 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 35,589。

总安装 2,060周安装 85GitHub Stars 329下载 673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:pentest-validation(渗透测试验证)
来源仓库:https://github.com/proffesor-for-testing/agentic-qe
仓库路径:skills/pentest-validation
安装命令:
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill pentest-validation
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/proffesor-for-testing/agentic-qe --skill pentest-validation

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。

标准化渗透测试流程与结果验证的参考框架。定义从侦察到报告各阶段的质量门禁与验收标准。适用于 QA 团队对红队输出成果进行合规性与完整性核查。验证方法需与项目安全策略对齐,不可替代专业渗透测试。pentest-validation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/pentest-validation

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/proffesor-for-testing/agentic-qe --skill pente…;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

pentest-validation 怎么安装?

在终端执行 npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill pentest-validat…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pentest-validation 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。

pentest-validation 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。

pentest-validation 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。

pentest-validation 用的人多吗?

公开数据是累计安装 2,060 次,近一周安装 85 次,下载 673 次,GitHub 329 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。

pentest-validation 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
pentest-validation

渗透测试验证 · 本页

2,060329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

Pentest Validation

<default_to_action> When validating security findings:

  1. REQUIRE explicit authorization for target URL
  2. SCAN with qe-security-scanner (SAST + dependency + secrets)
  3. ANALYZE with qe-security-reviewer + qe-security-auditor (parallel)
  4. VALIDATE with qe-pentest-validator (graduated exploitation, parallel per vuln type)
  5. REPORT only confirmed findings with PoC evidence ("No Exploit, No Report")
  6. UPDATE exploit playbook with new patterns

Quality Gates:

  • Authorization confirmed before ANY exploitation
  • Target URL is staging/dev (NOT production)
  • Budget cap enforced ($15 default)
  • Time cap enforced (30 min default)
  • All exploitation attempts logged </default_to_action>

Quick Reference Card

The 4-Phase Pipeline

PhaseAgent(s)PurposeParallelism
1. Reconqe-security-scannerSAST, DAST, dependency scan, secretsInternal parallel
2. Analysisqe-security-reviewer + qe-security-auditorCode review + compliance checkBoth in parallel
3. Validationqe-pentest-validatorGraduated exploit validationPer-vuln-type parallel
4. Reportqe-quality-gate"No Exploit, No Report" filterSequential

Graduated Exploitation Tiers

TierHandlerCostLatencyUse When
1Agent Booster (WASM)$0<1msCode pattern is conclusive (eval, innerHTML, hardcoded creds)
2Haiku$0.0002~500msNeed payload test against live target
3Sonnet/Opus$0.003-$0.0152-5sFull exploit chain with data proof

When to Use This Skill

ScenarioTierEstimated Cost
PR security review (source only)1$0
Pre-release validation (staging)1-2$1-5
Full pentest validation1-3$5-15
Compliance audit evidence1-3$5-15

Configuration

pentest:
  target_url: https://staging.app.com    # REQUIRED for Tier 2-3
  source_repo: ./src                      # REQUIRED for Tier 1+
  exploitation_tier: 2                    # 1=pattern-only, 2=payload-test, 3=full-exploit
  vuln_types:                             # Which pipelines to run
    - injection                           # SQL, NoSQL, command injection
    - xss                                 # Reflected, stored, DOM XSS
    - auth                                # Auth bypass, session, JWT
    - ssrf                                # URL scheme abuse, metadata
  max_cost_usd: 15                        # Budget cap per run
  timeout_minutes: 30                     # Time cap per run
  require_authorization: true             # MUST confirm target ownership
  no_production: true                     # Block production URLs
  production_patterns:                    # URL patterns to block
    - "*.prod.*"
    - "api.*"
    - "www.*"

Safeguards (Mandatory)

Authorization Gate

Every pentest validation run MUST:

  1. Display target URL and exploitation tier to user
  2. Require explicit confirmation: "I own/authorized testing of this target"
  3. Log authorization with timestamp
  4. Block if target URL matches production patterns

What This Skill Does NOT Do

  • Full autonomous reconnaissance (Nmap, Subfinder)
  • Zero-day exploit development
  • Attack targets without explicit authorization
  • Test production systems
  • Store actual exfiltrated data (only proof of access)
  • Social engineering or phishing simulation
  • Port scanning or service discovery

Validation Pipelines

Injection Pipeline

AttackTier 1 (Pattern)Tier 2 (Payload)Tier 3 (Full)
SQL injectionString concat in query' OR '1'='1 response diffUNION SELECT data extraction
NoSQL injection$where, $gt in queryOperator injection testCollection enumeration
Command injectionexec(), system() callsCommand delimiter testReverse shell proof
LDAP injectionString concat in filterWildcard injectionDirectory enumeration

XSS Pipeline

AttackTier 1 (Pattern)Tier 2 (Payload)Tier 3 (Full)
Reflected XSSNo output encoding<img onerror> reflectionBrowser JS execution via qe-browser (Vibium)
Stored XSSinnerHTML assignmentPayload stored + retrievedCookie theft PoC
DOM XSSdocument.write(location)Fragment injectionDOM manipulation proof

Auth Pipeline

AttackTier 1 (Pattern)Tier 2 (Payload)Tier 3 (Full)
JWT noneNo algorithm validationModified JWT acceptedAdmin access with forged token
Session fixationNo session rotationPre-set session reusedCross-user session hijack
Credential stuffingNo rate limiting100 attempts unblockedValid credential discovery
IDORNo authorization checkAccess other user dataFull CRUD on foreign resources

SSRF Pipeline

AttackTier 1 (Pattern)Tier 2 (Payload)Tier 3 (Full)
Internal URLUser-controlled URL fetchhttp://169.254.169.254Cloud metadata extraction
DNS rebindingURL validation bypassRebind to internal IPInternal service access
Protocol smugglingURL scheme not restrictedfile:///etc/passwdFile content in response

Agent Coordination

Orchestration Pattern

// Phase 1: Recon (parallel scans)
await Task("Security Scan", {
  target: "./src",
  layers: { sast: true, dast: true, dependencies: true, secrets: true }
}, "qe-security-scanner");

// Phase 2: Analysis (parallel review)
await Promise.all([
  Task("Code Security Review", {
    findings: phase1Results,
    depth: "comprehensive"
  }, "qe-security-reviewer"),

  Task("Compliance Audit", {
    findings: phase1Results,
    frameworks: ["owasp-top-10"]
  }, "qe-security-auditor")
]);

// Phase 3: Validation (graduated exploitation)
await Task("Exploit Validation", {
  findings: [...phase1Results, ...phase2Results],
  target_url: "https://staging.app.com",
  exploitation_tier: 2,
  vuln_types: ["injection", "xss", "auth", "ssrf"],
  max_cost_usd: 15,
  timeout_minutes: 30
}, "qe-pentest-validator");

// Phase 4: Report ("No Exploit, No Report" gate)
await Task("Security Quality Gate", {
  findings: phase3Results.confirmedFindings,
  gate: "no-exploit-no-report",
  require_poc: true
}, "qe-quality-gate");

Finding Classification

StatusMeaningAction
confirmed-exploitableExploitation succeeded with PoCReport with evidence
likely-exploitablePartial exploitation, defenses detectedReport with caveats
not-exploitableAll exploitation attempts failedFilter from report
inconclusiveWAF/defense blocked, unclear if vulnerableReport for manual review

Exploit Playbook Memory

Namespace Structure

aqe/pentest/
 playbook/
  exploit/{vuln_type}/{tech_stack}/{technique}
  bypass/{defense_type}/{technique}
  payload/{vuln_type}/{variant}
 results/
  validation-{timestamp}
 poc/
  {finding_id}-poc

Learning Loop

  1. Before validation: Query playbook for known patterns matching findings
  2. During validation: Try known payloads first (higher success rate)
  3. After validation: Store new successful patterns with confidence scores
  4. Over time: Agent converges on most effective payloads per tech stack

Cost Optimization

Estimated Cost by Scenario

ScenarioTier MixFindingsEst. CostEst. Time
PR check (source only)100% Tier 15$0<5s
Sprint validation70% T1, 30% T215$2-55-10 min
Release validation40% T1, 40% T2, 20% T325$8-1515-30 min
Full pentest20% T1, 30% T2, 50% T340$15-3030-60 min

Cost vs Shannon Comparison

MetricShannonAQE Pentest Validation
Cost per run~$50$5-15 (graduated tiers)
Runtime60-90 min15-30 min (parallel pipelines)
False positive rateLow (exploit-proven)Low (same principle)
LearningNone (static prompts)ReasoningBank playbook

Success Metrics

MetricTargetMeasurement
False positive reduction>60% of findings eliminatedPre/post validator comparison
Exploit confirmation rate>80% of confirmed findings truly exploitableManual PoC verification
Cost per run<$15 USDToken tracking per pipeline
Time per run<30 minutesExecution time metrics
Playbook growth100+ patterns after 6 monthsMemory namespace count

Related Skills


Remember

"No Exploit, No Report." A vulnerability scanner that can't prove exploitation delivers uncertain value. This skill transforms security findings from theoretical risks into proven vulnerabilities with evidence. Every confirmed finding comes with a reproducible proof-of-concept. Every false positive is eliminated before it reaches the report.

Think proof, not prediction. Don't report what MIGHT be vulnerable. Prove what IS vulnerable.

平台分布

Codex

37.22%
按下载量换算250

Claude

29.26%
按下载量换算197

Cursor

17.73%
按下载量换算119

Gemini CLI

10.31%
按下载量换算69

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

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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