tinysocs-validation-and-qa

Defines evidence standards for validating TinySocs detection rules via xUnit tests and Atomic Red Team harness.

Updated Oct 12, 2025
One-click install
npx skills add https://github.com/lukefitzg/tinysocs --skill tinysocs-validation-and-qa-lukefitzg
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tinysocs-validation-and-qa
Source: https://github.com/lukefitzg/tinysocs/tree/main/.claude/skills/tinysocs-validation-and-qa
Command: npx skills add https://github.com/lukefitzg/tinysocs --skill tinysocs-validation-and-qa-lukefitzg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? It prevents false detection-efficacy claims by defining exactly what counts as proof that a TinySocs detection rule works, distinguishing synthetic xUnit tests from live Atomic Red Team attack validation. ## Core Features & Use Cases - Two-mechanism validation model: Explains what xUnit synthetic-event tests (48 executable cases) prove versus what the Atomic Red Team live-attack harness proves, and why neither alone is sufficient. - Numbers discipline: Enforces which efficacy figures are quotable (88.9% curated) versus banned (57.1% raw, March 100%), with curated-vs-raw denominator rules. - Harness scar-tissue documentation: Catalogs deliberate engineering choices in Test-AtomicDetection.ps1 (curl over Invoke-RestMethod, _source projection, day-scoped indices) that must not be cleaned up. - Use Case: When asked "is rule TS-061 validated" or "what does 88.9% mean", consult this Skill to answer honestly using the harness-validated definition and current atomic-results.json state. ## Quick Start Ask the AI to load the tinysocs-validation-and-qa skill and explain whether detection rule TS-070 is validated and what evidence backs that claim.

Frequently Asked Questions about tinysocs-validation-and-qa

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check if a TinySocs detection rule is validated?

A rule is harness-validated only if it fired in an Atomic Red Team run under a rule definition equivalent to today's. Check tests/atomic-results.json for live attack-to-alert evidence, and confirm the xUnit tests in DetectionEngineTests.cs prove it fires on synthetic events.

What is the difference between xUnit tests and the Atomic Red Team harness?

xUnit tests fire synthetic AgentEvent objects at the C# DetectionEngine to prove a rule can fire and stay silent off-target. The Atomic harness runs real attack techniques on a Windows VM against live OpenSearch to prove the full pipeline produces an alert.

Why does the dashboard disagree with atomic-results.json?

Same-week harness re-runs silently clobber run_id because normalize_validation_run.py defaults the sequence to 001. The public dashboard can go stale, showing an older unfiltered rule set while atomic-results.json reflects the newer curated run.

Can I quote the 100% or 57.1% detection efficacy figures?

No. The March 100% figure predates the test-fidelity overhaul and is banned outright, and 57.1% is a raw first-run number that miscounted deliberately deferred rules as misses. Only the curated 88.9% (8 of 9 executed enabled-rule techniques) is quotable.

Why does Test-AtomicDetection.ps1 use curl.exe instead of Invoke-RestMethod?

PowerShell 5.1's Schannel TLS handshake fails against the OpenSearch endpoint, and Invoke-RestMethod swallowed the exception into empty results, turning real detections into silent false misses. This is deliberate scar-tissue engineering that must not be simplified.

When should I not use this validation skill?

Do not use it for running the publication pipeline, authoring a new atomic test's fallback command, deciding whether a candidate rule is worth adding, or choosing externally safe efficacy figures. Those belong to the publication-campaign, validation-toolkit, research-methodology, and external-positioning skills respectively.