detection-engineering-coverage-evaluation

Automate detection engineering in Google SecOps by fetching threat intelligence, generating Threat Detection Opportunities, simulating synthetic UDM events, and evaluating rule coverage. This workflow requires MCP tools and Python libraries to process and evaluate threats end-to-end.

Evaluate YARA-L 2.0 rule coverage by simulating attacker behavior with synthetic UDM events. The evaluation process tests generated rules against these events to identify coverage gaps and ensure comprehensive threat detection.

Generate Threat Detection Opportunities by automatically fetching threat intelligence from various sources. The fetched data is processed to identify potential threats and simulate corresponding attacker behaviors for rule evaluation.

Yes, MCP tools and Python libraries are required dependencies for simulating attacker behavior. They enable the processing and evaluation of synthetic UDM events and the generation of new YARA-L 2.0 rules to close coverage gaps.

Automatically generate new YARA-L 2.0 rules after evaluating rule coverage against synthetic events. The workflow identifies coverage gaps from the evaluation and creates new rules to ensure comprehensive protection against potential threats.

Synthetic event simulation evaluates rule coverage based on simulated attacker behavior rather than live network traffic. It requires accurate UDM event generation and proper MCP tools configuration to effectively identify detection gaps and generate valid YARA-L 2.0 rules.