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Detecting And Responding

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telagod
detecting-and-responding

蓝队与紫队工程:检测规则编写、SIEM/EDR 调优、事件响应、数字取证、威胁狩猎、ATT&CK 映射、紫队演练闭环。Use when writing Sigma/YARA detection rules, tuning SIEM noise, responding to security incidents, conducting forensic analysis, hunting threats, or running purple team exercises.

Overview

Publishertelagod
Repositorycode-abyss
Skill namedetecting-and-responding
Stars
242
Forks
33
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by telagod on GitHub. Read the source before you install it.

Installation

Install the Detecting And Responding AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/telagod/code-abyss/tree/main/skills/detecting-and-responding
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/telagod/code-abyss.git /tmp/code-abyss
mkdir -p .claude/skills
cp -r /tmp/code-abyss/skills/detecting-and-responding .claude/skills/detecting-and-responding
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Detecting And Responding in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Detecting And Responding on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Detecting And Responding is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

蓝队检测与响应 · 镇魔盾

判断先于执行:决定「是否做 / 选什么 / 如何取舍」(栈、方案、架构、权衡)前,先读领域判断内核 skills/_kernel/security/SKILL.md——它管 judgment,本秘典管 execution;冲突时以内核判断为准。

检测是工程,不是运气。每条规则必须能回答四问:what / why / FP rate / response。 站在防御侧,把告警当代码维护、把事件当事故管理、把狩猎当假设验证。 信级:项目日志/EDR 原始事件 > Sigma/YARA 规则库 > ATT&CK 官方矩阵 > 训练记忆(标 [unverified])。

路由

意图秘典触发词
SIEM/EDR 规则与调优siem-and-edrSigma, YARA, Splunk, Elastic, Sentinel, EDR, LOLBins, detection-as-code
事件响应与取证incident-responseIR, NIST 800-61, triage, chain of custody, Volatility, memory, runbook, postmortem
威胁狩猎与紫队threat-huntinghunt, hypothesis, IOC, IOA, TTP, ATT&CK, Atomic Red Team, Caldera, 蜜罐

执行链

检测:日志源 → 规则编写 → 告警分级 → 调优降噪 → 覆盖矩阵
响应:识别 → 遏制 → 根因 → 清除 → 恢复 → 复盘
狩猎:假设 → 数据源 → 验证 → 规则化 → 自动化 → 紫队闭环

每环必须可回答「我看的是哪条日志?我证伪的是哪条假设?我下一步动作是什么?」

何时使用

场景用不用
写 Sigma/YARA 规则、调 SIEM✅ siem-and-edr—
处理已发生入侵、取证✅ incident-response—
假设驱动狩猎 / 紫队演练✅ threat-hunting—
ATT&CK 检测覆盖打分✅ threat-hunting—
设计应用层防御代码❌defending-applications
渗透测试、写 PoC❌securing-systems (pentest/red-team)
威胁建模、IAM 架构❌architecting-security
代码静态扫描胶水❌analyzing-security
云配置基线、K8s 加固❌securing-cloud-and-supply-chain

联动

  • securing-systems/red-team:攻方 TTP 是本 skill 检测规则的设计输入。
  • securing-systems/threat-intel:IOC/CTI 投喂本 skill 的规则与狩猎假设。
  • architecting-security/threat-modeling:威胁模型的 detective control 在本 skill 落地。
  • analyzing-security:本 skill 产出的 detection-as-code 接入 CI 门禁。
  • automating-devops/observability:日志/指标/链路三支柱的安全维。

铁律

  1. 无噪不出闸 — 任何规则上线前必须有基线 + FP rate 测量;FP > 5% 直接打回调优,不准带病上线。
  2. 不证伪即假设 — 狩猎必须有可证伪的假设;找不到不是结论,是数据缺失或假设错。
  3. 取证不破坏现场 — 先采易失证据(内存/网络/进程),再动磁盘;写阻断器 + 哈希链 + 时间戳三件套必须齐。
  4. 检测即代码 — 规则进 git、有 unit test、过 CI、有 owner;改规则等同改生产代码。
  5. 闭环到 ATT&CK — 每条规则、每次事件、每次狩猎必须映射到 ATT&CK 技术 ID;无 ID 不归档。

输出约束

  • 规则示例必须给完整 frontmatter + detection + condition + 反例说明(为什么不这样写)。
  • 命令示例标注操作系统与权限要求(root / SYSTEM / 普通用户)。
  • 日志样例脱敏:IP 用 192.0.2.0/24、域名用 example.com、用户名用 <analyst>。
  • 每条检测规则必须附 FP 来源清单与响应动作(containment / enrichment / kill)。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Detecting And Responding AI skill do?

蓝队与紫队工程:检测规则编写、SIEM/EDR 调优、事件响应、数字取证、威胁狩猎、ATT&CK 映射、紫队演练闭环。Use when writing Sigma/YARA detection rules, tuning SIEM noise, responding to security incidents, conducting forensic analysis, hunting threats, or running purple team exercises.

Why use Detecting And Responding on TypingMind?

Because you install it once and use it with any model. Detecting And Responding is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Detecting And Responding in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/telagod/code-abyss/tree/main/skills/detecting-and-responding. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Detecting And Responding?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Detecting And Responding?

As many as you like. As long as a model supports skills, you can use Detecting And Responding with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Detecting And Responding AI skill free?

Yes. It is published on GitHub by telagod under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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