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Agent Skill · 研究检索

pentest-outbound-interaction-oob-detection(pentest 出站交互 oob 检测)

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-outbound-interaction-oob-detection 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,权限为执行命令;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 51,212。

总安装 588周安装 24GitHub Stars 公开资料未说明下载 188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-outbound-interaction-oob-detection(pentest 出站交互 oob 检测)
来源仓库:https://github.com/crtvrffnrt/skills
仓库路径:skills/pentest-outbound-interaction-oob-detection
安装命令:
npx skills add https://github.com/crtvrffnrt/skills --skill pentest-outbound-interaction-oob-detection
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/crtvrffnrt/skills --skill pentest-outbound-interaction-oob-detection

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。

检测出站交互(Out-of-Band)通道滥用的安全测试模块。识别 DNS、HTTP 外带、ICMP 隧道等隐蔽通信路径的存在。适用于 SSRF、XXE 等漏洞的深度验证与数据渗漏风险评估。外带请求可能产生公网流量,请监控带宽消耗与日志记录。

pentest-outbound-interaction-oob-detection 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-outbound-interaction-oob-detection

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/crtvrffnrt/skills --skill pentest-outbound-int…;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

    它需要执行命令,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-outbound-interaction-oob-detection 怎么安装?

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

pentest-outbound-interaction-oob-detection 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-outbound-interaction-oob-detection 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/crtvrffnrt/skills --skill pentest-outbound-interaction-oob-detection 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

pentest-outbound-interaction-oob-detection 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-outbound-interaction-oob-detection 用的人多吗?

公开数据是累计安装 588 次,近一周安装 24 次,下载 188 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。

pentest-outbound-interaction-oob-detection 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

  • 需要执行命令,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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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-outbound-interaction-oob-detection

pentest 出站交互 oob 检测 · 本页

588—执行命令未明确有提醒

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

Outbound Interaction & OOB Detection

Purpose

Use this skill for outbound interaction and out-of-band validation when the hypothesis requires callback evidence rather than an immediate in-band response.

Primary use cases:

  • SSRF callback confirmation
  • Blind XSS beacons
  • Blind XXE
  • Webhook delivery validation
  • DNS, HTTP, or HTTPS callback correlation
  • Asynchronous server-side interaction proof
  • Reverse-shell-adjacent egress testing where the goal is callback validation, not shell handling

Do not use this skill when the finding can be confirmed fully in-band.

Operating Rules

  • Treat OOB validation as evidence collection, not only payload delivery.
  • Generate a unique correlation token for every test case.
  • Keep control and test payloads separate.
  • Correlate events by token, subdomain or path, and timestamp before confirming a finding.
  • Preserve session state and callback logs on disk.
  • Keep the listener running long enough for delayed interactions.
  • Use the minimum protocol set that can validate the hypothesis.
  • Do not claim confirmation from background traffic or uncorrelated callbacks.
  • Do not send real secrets in callback payloads.

Activation Triggers (Positive)

Use this skill when the request or observed behavior includes:

  • ssrf callback
  • blind xss
  • webhook abuse
  • oob
  • dns interaction
  • asynchronous callback
  • xxe out of band
  • blind xxe
  • http callback
  • https callback
  • egress validation

Exclusion Triggers (Negative)

Do not use this skill when the task is:

  • fully in-band exploitation
  • static review only
  • report drafting only

Validation Standard

Only confirm the finding if all of the following are true:

  1. A unique per-test token was generated before payload delivery.
  2. The payload under test embedded the expected callback identifier.
  3. An interaction was observed in the allowed test window.
  4. The observed interaction matches the token plus path or subdomain plus timestamp.
  5. Control cases do not explain the same signal.

Verdicts:

  • confirmed: deterministic correlation exists
  • inconclusive: partial signal without enough correlation
  • not confirmed: no matching interaction or controls invalidate the claim

Instructions

  1. Generate unique per-test correlation identifiers before sending payloads.
  2. Ensure callback listener scope and retention are sufficient for delayed events.
  3. Correlate callbacks by token, path, and time window before confirmation.
  4. Differentiate noisy background traffic from test-linked interactions.
  5. Use control payloads to reduce false positives.
  6. Pass confirmed primitives to exploit or logic skills with full correlation evidence.

Should Do

  • Treat OOB validation as evidence discipline, not only payload dispatch.
  • Preserve immutable callback logs for auditability.
  • Include both positive and negative control outcomes.

Should Not Do

  • Do not claim confirmation without deterministic correlation.
  • Do not reuse tokens across unrelated tests.
  • Do not expose real secrets in callback payloads.

Standard Workflow

  1. Define the hypothesis and expected outbound behavior.
  2. Choose the smallest callback mechanism that can validate it.
  3. Start one listener session for the assessment run.
  4. Generate one unique token per probe.
  5. Embed the tokenized callback endpoint into the payload.
  6. Send the payload and record the timestamp and source context.
  7. Monitor for matching interactions during the expected window.
  8. Compare with controls before reaching a verdict.
  9. Pass confirmed primitives to exploit or logic-abuse workflows with full evidence.

Listener Component

Use the installed interactsh-client for DNS, HTTP, and HTTPS callback validation.

Reference startup pattern:

RUN_DIR="/tmp/interactsh-$(date +%Y%m%d-%H%M%S)"
mkdir -p "$RUN_DIR"

interactsh-client \
  -json \
  -o "$RUN_DIR/interactions.jsonl" \
  -sf "$RUN_DIR/session.txt" \
  -ps \
  -psf "$RUN_DIR/payloads.txt" \
  -pi 5 \
  >"$RUN_DIR/stdout.log" 2>&1 &

echo $! > "$RUN_DIR/interactsh.pid"
sleep 2
cat "$RUN_DIR/payloads.txt"

Listener handling rules:

  • Start one background listener per assessment run unless isolation requires a separate session.
  • Persist interactions.jsonl, session state, generated payload domains, and stdout logs.
  • Keep the listener active for the full validation window.

Per-Test Token Generation

Generate one unique token for each test case:

TEST_TOKEN="$(tr -dc 'a-z0-9' </dev/urandom | head -c 10)"
BASE_DOMAIN="$(head -n1 "$RUN_DIR/payloads.txt" | tr -d '\r\n')"
CALLBACK_FQDN="${TEST_TOKEN}.${BASE_DOMAIN}"

echo "$TEST_TOKEN $CALLBACK_FQDN $(date -Iseconds)" >> "$RUN_DIR/test_tokens.log"

printf '%s\n' "$CALLBACK_FQDN"

Rules:

  • Never reuse a token across unrelated tests.
  • Record token, payload target, source vector, and timestamp.
  • Use path-based correlation in addition to subdomain-based correlation when useful.

Protocol Selection

Choose the protocol that matches the hypothesis:

  • DNS: egress proof, resolver behavior, low-friction SSRF or XXE validation
  • HTTP: webhook delivery, SSRF, application-layer callback verification
  • HTTPS: when the target is likely to enforce TLS-only egress

Prefer the smallest useful set. Do not spray all protocols unless the test requires it.

Reverse-Shell-Adjacent Egress Checks

Use this skill for reverse-shell-adjacent validation only when the objective is to determine whether the target can reach an external endpoint over common egress channels such as 80 or 443.

Rules:

  • Do not use this skill as a shell listener.
  • Use it only to validate outbound reachability and protocol behavior.
  • If shell-capable execution is later confirmed, hand off to the exploit execution workflow.

Evidence to Capture

For each test case, record:

  • hypothesis
  • payload vector
  • generated token
  • callback endpoint
  • request timestamp
  • control payloads
  • observed callback timestamp
  • protocol observed
  • source context
  • verdict

Output Schema

Return:

  • Correlation table with token, payload path or subdomain, timestamp, source context
  • Validation verdict: confirmed, not confirmed, or inconclusive
  • Follow-on opportunities based only on confirmed outbound behavior
  • Reproduction steps with enough detail for another operator to rerun the test

Tooling Notes

  • If interactsh-client is missing, state that clearly and stop short of confirming OOB claims.
  • Do not replace deterministic correlation with assumption.
  • Preserve logs so callback-based claims remain auditable.

平台分布

Codex

36.96%
按下载量换算69

Claude

30.92%
按下载量换算58

Cursor

16.32%
按下载量换算31

Gemini CLI

9.82%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/crtvrffnrt/skills --skill pentest-outbound-interaction-oob-detection 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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