本文へ移動
cccskills
無料GitHub で公開

writing-sigma-detection-rules

Converts hunt findings into portable Sigma detection rules: choosing the right logsource, expressing robust selection/filter logic, setting level and ATT&CK tags, and validating before converting to a SIEM query. Activates for requests to write a Sigma rule, convert a hunt to a detection, or create portable SIEM detection logic.

インストール方法を見る

含まれるファイル(4)

  • SKILL.md3.1 KB
  • LICENSE340 B
  • references/api-reference.md1.2 KB
  • scripts/analyst.py2.0 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Writing Sigma Detection Rules

When to Use

  • A hunt produced reliable logic and you want a portable, SIEM-agnostic detection.
  • You need to share or version a detection in a standard format and tag it to ATT&CK.
  • You are translating a vendor query into Sigma for reuse across backends.

Do not use Sigma for stateful/correlation logic it cannot express well (complex sequence or statistical detections) — keep those in the SIEM's native correlation engine.

Prerequisites

  • The sigma CLI / sigma-cli (pysigma) for validation and conversion.
  • Knowledge of the target log source's field names and the Sigma taxonomy.

Workflow

Step 1: Define the logsource

Pin category/product/service precisely (e.g., product: windows, category: process_creation) so the rule maps to the right pipeline.

Step 2: Write robust selection logic

Express the detection on stable fields. Prefer multiple ANDed conditions over a single brittle string; use contains/endswith modifiers thoughtfully to resist evasion.

python scripts/analyst.py scaffold --title "Encoded PowerShell" --category process_creation \
  --technique T1059.001 --level high

Step 3: Add filters to cut false positives

Use a filter block (negated in the condition) to exclude known-good processes/paths rather than narrowing selection until it misses variants.

Step 4: Tag and document

Add tags (ATT&CK technique), level, status, references, and a falsepositives list so consumers can tune.

Step 5: Validate and convert

Lint the rule, then convert to the target backend and test against true/false-positive data before deploying.

sigma convert -t splunk rules/encoded_powershell.yml

Validation

  • The rule passes Sigma schema validation (sigma check).
  • It fires on the hunt's true positives and not on the documented benign cases.
  • Conversion to the target backend produces a sensible, runnable query.

Pitfalls

  • Over-narrow selection that matches one sample and misses the technique.
  • Wrong logsource, so the rule never sees the relevant events.
  • No falsepositives/filter, producing a noisy alert that gets ignored.

References

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Reverses Android malware: unpacking APKs, decompiling DEX bytecode to readable Java, auditing the manifest for abused permissions and components, and locating dynamically loaded or native payloads. Activates for requests to analyze an APK, decompile DEX, or investigate a suspicious Android app.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Analyzes API call traces from a sandbox or API monitor (JSON) to group calls by category, reconstruct high-level behaviors (process injection, file drops, network, crypto), and flag suspicious call sequences. Activates for requests to analyze an API trace, interpret sandbox API logs, or identify behavior from Win32/Native API calls.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Analyzes Windows Authenticode signatures on PE files: checking for a signature, reading the signer certificate chain, detecting revoked/expired/stolen certs, and recognizing signature-stripping and catalog-signing abuse. Activates for requests to analyze a code signature, verify Authenticode, or assess signer trust on a PE.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Analyzes banking trojan webinject configurations to extract targeted institutions, injected JavaScript/HTML, and data-theft hooks, mapping the fraud workflow. Activates for requests to analyze banking trojan webinjects, parse a webinject config, or map targeted banks and credential-theft injections.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Analyzes Python-based malware packaged as PyInstaller/py2exe executables by detecting the packer, locating the embedded archive, and identifying bundled .pyc modules for extraction and decompilation. Activates for requests to analyze compiled Python malware, unpack a PyInstaller binary, or extract pyc modules from a frozen Python executable.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

Analyzes cryptojacking/coinminer malware by extracting mining pool endpoints (stratum), wallet addresses, algorithm and miner identifiers (XMRig and forks), and persistence or resource-control settings from static strings and config. Activates for requests to analyze a cryptominer, extract mining pool and wallet IOCs, or identify coinminer configuration.

日本語の概要は準備中です。原文の説明を表示しています。

meltedinhex/analyst-ai-pack222026年7月7日 更新

meltedinhex のスキルをすべて見る

このスキルの問題を報告する