Let AI Catch the Bugs: Uncoder AI Validates Detection Rule Syntax and Logic

How It Works

In fast-paced detection engineering, syntax mistakes and structural oversights happen — especially when working across multiple platforms or under tight response deadlines. Catching and fixing these issues manually is tedious, time-consuming, and often overlooked.

With Uncoder AI’s Syntax and Structure Validation, detection authors can now validate their rules — both syntactically and logically — in real-time using a secure, AI-powered engine.

In the use case above, a Splunk SPL detection is automatically reviewed. The system:

  • Checks for correct usage of commands like index=, eventcode=, stats, rex, and where
  • Analyzes logical flow between pipeline segments (bin, group by, filter)
  • Flags any potential inefficiencies, regex complexity, or ambiguous logic
  • Provides clear, line-by-line feedback in an organized summary view

This validation is powered by a locally hosted Llama 3.3 model, fine-tuned for detection engineering and running entirely within SOC Prime’s SOC 2-compliant private cloud infrastructure.

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Why It’s Innovative

Unlike static linters or one-line validators, Uncoder AI goes beyond surface checks. It understands platform-specific logic, reviews the use of regular expressions, evaluates performance impact, and flags ambiguous logic — even when technically correct.

Highlights:

  • Support for 56 detection languages, including Splunk SPL, Microsoft Sentinel KQL, Sigma, Elastic Stack, ArcSight, CrowdStrike Falcon LogScale, and more
  • No data leaves the platform — queries are validated securely within SOC Prime’s infrastructure
  • Actionable recommendations instead of vague syntax errors
  • Context-aware interpretation of what the query is meant to do — not just how it’s written

Operational Value

  • Saves Engineering Time: Eliminate hours lost to manual debugging.
  • Accelerates Deployment: Get real-time feedback during rule development.
  • Enables Junior Analysts: Help less experienced team members write solid, production-ready detections.
  • Reduces Risk: Catch logic flaws that pass syntax checks — like overly broad filters or ineffective groupings.
  • Keeps You Compliant: Aligns detection logic with schema requirements for Microsoft Sentinel and other supported platforms.

From Guesswork to Precision: AI as Your Syntax Co-Pilot

Every minute you spend debugging rule syntax is a minute you’re not detecting threats. With Uncoder AI’s validation capability, detection engineers can write, check, and improve their rules with AI-powered guidance — right inside the workflow. No exports. No context switching. Just instant answers, from a model trained to understand detection.

Now your rules aren’t just functional. They’re bulletproof.

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