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Detect DNS Threats in Google SecOps: Katz Stealer Rule Conversion with Uncoder AI
- Google SecOps now offers the capability to convert Sigma rules into UDM to detect DNS threats like Katz Stealer.
- The original Sigma rule is designed to identify DNS queries related to known Katz Stealer domains.
- The left panel displays the Sigma rule logic with detection conditions for specific Katz Stealer domains.
- Uncoder AI generates an equivalent UDM query in the right panel, making it platform-specific for Google SecOps.
- The AI tool automates the conversion process, adapting syntax and regex rules for efficient threat detection.
- This innovation eliminates the manual rewriting of detection content for different platforms, enhancing scalability.
- Key benefits for SOC teams include time savings, improved threat coverage, and consistent translation accuracy.
- Security professionals can quickly deploy DNS-based detections for Katz Stealer in Google environments using this feature.
- The approach ensures precision, consistency, and extensibility of detection capabilities across platforms.
- Security teams can effectively leverage open-source detection content by converting it into actionable UDM queries.
- The feature enhances response times and boosts visibility within Google SecOps deployments.
- The post emphasizes the benefits of utilizing Uncoder AI in detecting and converting DNS threats in Google SecOps.
- Uncoder AI simplifies threat detection by automatically transforming Sigma rules into UDM queries.
- The tool ensures the preservation of detection intent while streamlining the process for security professionals.
- Overall, the integration of Uncoder AI in Google SecOps offers a more efficient and effective solution for detecting DNS threats like Katz Stealer.
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