How It Works
This Uncoder AI feature showcases its ability to analyze and validate Chronicle UDM queries involving multiple domain-based conditions. In this example, Uncoder AI processes a threat-hunting query associated with Sandworm (UAC-0133) activity, which targets a set of .sh and .so domains.
The platform automatically identifies that the detection logic uses a field-level comparison on target.hostname, a standard field in Google SecOps (Chronicle) schema. The query employs repeated OR operators to check for matches across a list of suspicious hostnames — such as opf.sh, zjk.sh, and env.so.
On the right panel, Uncoder AI performs an AI-generated validation, breaking down the structure for:
- Query logic (OR chaining)
- Field/value formatting
- Schema alignment
- Performance impact
It confirms that the syntax is valid while recommending improvements such as using an IN operator for better performance.
Why It’s Innovative
Traditional Chronicle query validation requires manual review of syntax, logic, and schema accuracy — a time-consuming and error-prone task. Uncoder AI replaces this with real-time, AI-powered validation and optimization, driven by natural language processing (NLP) and logic parsing.
Key AI contributions include:
- Automatic schema recognition of
target.hostname - Performance-aware suggestions based on query complexity
- Flagging anomalous entries, like
“3}.sh”, which may indicate misformatted or malformed IOC values - Auto-generation of improved syntax, recommending a condensed and readable IN block to replace dozens of repetitive ORs
This reduces the overhead of query writing and debugging for detection engineers while maintaining full compatibility with Google’s Chronicle UDM query structure.
Operational Value
For security teams working in Google SecOps environments, this feature enables:
Faster Detection Engineering
Security analysts can convert domain lists into validated Chronicle queries instantly, skipping manual formatting.
Higher Confidence in Query Quality
Built-in validation logic ensures that all fields used are schema-compliant, and suspicious formatting (e.g., malformed domains) is flagged for review.
Improved Performance Readiness
Recommendations to use IN operators instead of long OR chains reduce query execution time and make detections easier to maintain at scale.
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