February 2026 monthly summary for splunk/attack_data: Focused on macOS datasets and observability enhancements to strengthen detection coverage and data analysis capabilities. Implemented and consolidated new datasets for Mac OSX attack techniques using osquery, improving the attack range environment and data fidelity. Enhanced logging for hidden files on macOS to improve visibility and incident response readiness. Fixed a YAML formatting issue in the dataset configuration to ensure reliable ingestion and reproducibility across environments.

Monthly summary for 2026-01: Implemented a new Telnet Authentication Bypass and Privilege Escalation Dataset in the splunk/attack_data repository, including metadata and log paths to support rapid analysis of exploitation techniques. No major bugs fixed this month. This addition strengthens threat intel capabilities by enabling CVE-informed detection, contextual analytics, and faster incident response through improved data quality and traceability.

December 2025: Delivered key threat intel data enhancements in the splunk/attack_data repository, expanding coverage for attack techniques and network indicators. Implemented datasets for named pipes (T1055), C2 user agents, and enhanced HTTP user agents with Suricata log entries. Drove improvements through three commits, enabling richer threat hunting and faster analytics.

Monthly performance summary for 2025-11 focusing on delivering value through attacker simulation capabilities and improved observability. Two main features were delivered in splunk/attack_data to enhance realism of attack scenarios and to aid debugging/monitoring.

In Oct 2025, the attack_data repository delivered expanded threat emulation datasets and a targeted YAML config fix. Key features were added to enhance coverage for request smuggling (T1190) and web shell activity (T1505.003 via WSUS data sources), along with a bug fix to improve YAML syntax readability. These changes strengthen data fidelity for analysts and support more realistic ATT&CK simulations across Nginx, Suricata, WSUS environments, and Windows logs.

September 2025 Monthly Summary (2025-09). Overview: Focused on expanding NotDoor coverage through data collection and detection capabilities across two key Splunk repositories, delivering end-to-end visibility for a high-risk malware family and strengthening phishing/macro detection. The work enables faster detection, richer telemetry, and clearer alignment with security operations. Key features delivered this month: - NotDoor malware log data and attack range configuration added in splunk/attack_data, including new log data, configuration files, and log files to cover multiple execution scenarios using Windows Sysmon data. (Commit c4f9f91ff4f6ab5e261d8affd378471326e0d222) - NotDoor Outlook detection rules introduced in splunk/security_content to identify unauthorized Outlook registry key modifications and creation of macro files, enhancing protection against phishing and data exfiltration. (Commit 1a85b440dd0bf7c1627f71e5144fb04b6e750f88) Major bugs fixed: - No major bugs reported this month. Maintained stability while expanding data collection and detection capabilities. Overall impact and accomplishments: - Significantly improved threat visibility for NotDoor by bridging data collection with proactive detections, enabling faster SOC response. - Strengthened defense-in-depth against phishing and macro-based attacks through end-to-end NotDoor coverage. Technologies and skills demonstrated: - Windows Sysmon data integration for log collection and scenario-based configuration. - Detection rule development and telemetry modeling in Splunk Security Content. - Cross-repo collaboration and traceability from commits to feature delivery. Business value: - The delivered features reduce dwell time for NotDoor threats, improve incident response quality, and provide richer telemetry to security operations for proactive risk mitigation.

August 2025 highlights focused on dataset generation for security analytics and expanded cross-repo detection coverage. In splunk/attack_data, we delivered three new datasets/logs with configuration to simulate gdrive usage (Windows and Linux) and metadata (version, OID, size), added Medusa rootkit log data for T1014, and introduced a SpeechRuntime hijacking dataset for T1021.003, enabling practical research and defense testing. In splunk/security_content, we refreshed China-Nexus Threat Activity with gdrive-related detections for Linux/Windows, added suspicious VMware Tools child process monitoring, propagated the China-Nexus tag across ESXi firewall/VIB detections to improve monitoring accuracy, added Medusa Linux detection and installation artifact monitoring, and introduced/refined Windows SpeechRuntime detections for COM hijacking DLL loads and related suspicious processes. Overall, these changes increase detection coverage, accelerate threat research, and provide ready-to-use datasets for analytics and defense testing across Windows and Linux.

July 2025: Focused on strengthening ESXi threat detection data and Splunk content integration. Key features delivered include: 1) Threat Detection Datasets for ESXi Attack Techniques and vmtoolsd Execution, adding ESXi sample data and a vmtoolsd execution dataset to enable security analysis and threat research. 2) VMware Tools Dataset Configuration URL Path Fix to ensure proper referencing of Sysmon-related logs. 3) VMware ESXi syslog data ingestion and detection rules enhancements in security_content: introduced a new ESXi data source, updated attribution to use dest instead of host, expanded post-compromise detection rules, and added output_fields for the ESXi syslog data source. 4) VMware ESXi Splunk Add-ons integration to streamline data collection via Add-ons. Major impact: improved data fidelity and attribution for ESXi detections, faster threat research, and better operational monitoring. Technologies/skills demonstrated: Splunk content development, ESXi log data ingestion, dataset and data-source configuration, detection rule authoring/updating, and Add-ons integration.

June 2025 monthly summary for splunk/security_content: Delivered a new Remote Employment Fraud Detection feature with a targeted threat model to identify Remote Employment Fraud (REF). Implemented detection rules for suspicious Zoom activity (high video latency, rare devices) and Okta anomalies (unlikely geographic locations, non-standard VPN usage) to enable faster investigation and containment. This work is foundational for proactive REF monitoring and risk reduction across customer environments.