
Jorge Hernandez developed and enhanced security content and threat detection workflows across Splunk’s contentctl, security_content, and attack_data repositories. He built new CLI subcommands and robust data models in Python, focusing on AWS cloud security and MITRE ATT&CK integration. His work included implementing S3 decommissioned bucket monitoring, generating baseline datasets in CSV and YAML, and refining MITRE ATT&CK map generation for improved analyst usability. By leveraging skills in data modeling, JSON manipulation, and backend development, Jorge delivered features that improved operational efficiency, enabled reproducible detection baselines, and provided richer, auditable threat mapping for security engineering and detection teams.

June 2025: Delivered a richer MITRE ATT&CK enrichment and Attack Navigator integration in splunk/contentctl. Implemented a robust data model, improved processing, and enhanced metadata and Navigator formatting to enable precise threat mapping, faster triage, and auditable detections.
June 2025: Delivered a richer MITRE ATT&CK enrichment and Attack Navigator integration in splunk/contentctl. Implemented a robust data model, improved processing, and enhanced metadata and Navigator formatting to enable precise threat mapping, faster triage, and auditable detections.
March 2025: Delivered MITRE ATT&CK map generation enhancements for splunk/contentctl, improving data fidelity and usability. Changes include storing detection type, ID, and name separately; constructing per-detection research URLs; and refining the layer JSON for Navigator compatibility. No major bugs fixed this month. Business value: faster, more accurate MITRE mappings enable analysts to investigate and report more efficiently. Technical skills demonstrated: data modeling, JSON schema refinement, URL generation, and clean Git contribution with a focused commit history.
March 2025: Delivered MITRE ATT&CK map generation enhancements for splunk/contentctl, improving data fidelity and usability. Changes include storing detection type, ID, and name separately; constructing per-detection research URLs; and refining the layer JSON for Navigator compatibility. No major bugs fixed this month. Business value: faster, more accurate MITRE mappings enable analysts to investigate and report more efficiently. Technical skills demonstrated: data modeling, JSON schema refinement, URL generation, and clean Git contribution with a focused commit history.
February 2025 monthly summary for the Splunk repositories. Key deliverables across contentctl, security_content, and attack_data improved threat-hunting capabilities and standardized validation, aligning technical work with business value. Highlights include the robust addition of a Contentctl recognize subcommand with a dedicated RecognizeCommand dataclass and improved command/config handling, enhanced feedback tailored to security detection engineering and threat hunting, new S3 decommissioned bucket monitoring with a baseline and two detection rules (shipping as experimental), standardized test data sources and configurations, and the introduction of a baseline dataset for the S3 bucket deletion attack technique (T1485). These changes collectively improve operational efficiency, reduce time-to-detection, and provide reproducible baselines for detections and datasets across the security content workflow.
February 2025 monthly summary for the Splunk repositories. Key deliverables across contentctl, security_content, and attack_data improved threat-hunting capabilities and standardized validation, aligning technical work with business value. Highlights include the robust addition of a Contentctl recognize subcommand with a dedicated RecognizeCommand dataclass and improved command/config handling, enhanced feedback tailored to security detection engineering and threat hunting, new S3 decommissioned bucket monitoring with a baseline and two detection rules (shipping as experimental), standardized test data sources and configurations, and the introduction of a baseline dataset for the S3 bucket deletion attack technique (T1485). These changes collectively improve operational efficiency, reduce time-to-detection, and provide reproducible baselines for detections and datasets across the security content workflow.
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