The what:

Over the past 12 months, I believe I have performed strongly, delivering significant technical and strategic contributions that improved detection coverage, enhanced rule quality, and supported key client projects. I consistently focused on quality, automation and collaboration, which resulted in measurable improvements and positive feedback from stakeholders. Highlights include:

EDR Rule Development
Developed 83 new threat intelligence-driven rules (72 for S1, 11 for DFE) toward a target of 130. While the target wasn’t fully met, the focus shifted during the year from quantity to quality, ensuring higher accuracy and effectiveness while considering technical limitations on rule count.
Impact: In 2024, custom STAR detections on S1 generated 107 confirmed threat incidents, accounting for 39% of all S1 incidents. This year, custom detections generated 177 incidents, representing 43% of total S1 incidents, compared to 52% from out-of-the-box rules - a 4% year-over-year increase, demonstrating the growing value of custom detection logic.

Detection Logic Quality Assurance
Reviewed and enhanced approximately 162 detection rules across S1, DFE, and CS platforms. Key improvements included fixing 41 broken S1 rules, implementing ~98 intelligence-driven logic optimizations, and correcting 23 misconfigured rules for CS and DFE. These efforts significantly improved detection accuracy, reduced false positives and strengthened overall rule reliability.

Proactive Threat Hunting and Mitigation of Undetected Threats
Identified 15 threats across managed service provider (MSP) environments, along with 1 incident response (IR) case, that were not detected by automated security systems. These findings highlight gaps in automated detection and demonstrate the value of proactive threat hunting in strengthening overall security posture. In year 2024, I've uncovered 10 malicious campaigns.

Accelerated S1QL 2.0 Migration
Enhanced the S1QL converter to enable semi-automated rule development, significantly reducing manual effort. Delivered 136 out of 256 rules, including 50 manually created and 86 generated via the semi-automated converter. Successfully mitigated the risk of visibility loss caused by S1QL 1.0 auto-demotion, ensuring uninterrupted detection coverage.

External Kroll Purple Team Consultancy Project
Successfully led fifth consultancy engagement for AMINA bank since the start of the project in 2023 from the Detection Engineering side, ensuring high-quality delivery and alignment with client objectives. Completed multiple ad-hoc tasks related to reporting, consultancy, and advisory services. Developed 11 new detections covering both detected and undetected activities, strengthening threat coverage. The project concluded with confirmed customer satisfaction and agreement on project continuity.

The how:
Throughout this review period, I have actively contributed to Kroll's growth and culture by driving cross-team collaboration, enhancing operational efficiency through automation, and delivering high-quality client outcomes that support long-term business growth.

External Kroll Purple Team Consultancy Project
Successfully led consultancy engagements that delivered high-quality outcomes and confirmed project continuity, contributing to client satisfaction and long-term revenue opportunities.

Cross-Team Collaboration
Partnered with IR and SOC teams to validate detection effectiveness during live incidents through monthly review calls. Shared insights and learnings from proactive threat hunts to continuously improve detection logic and rule quality, fostering stronger collaboration and knowledge exchange across teams.

Tooling & Automation
Developed a semi-automated S1QL 1.0 to 2.0 converter, enabling scalable migration and significantly reducing manual effort. This solution improved consistency across rule sets and accelerated delivery timelines, ensuring a smooth transition to S1QL 2.0.

Peer Collaboration
Actively contributed to peer reviews, ensuring high-quality detection logic and adherence to best practices. Shared findings and logic improvements across teams and platforms to promote consistency, enhance detection effectiveness, and foster a culture of continuous improvement.

Overall Summary and Performance Rating

Performance rating descriptions
5. Leading
Best in class. Consistently raises the bar and recognized by peers and clients.
4. Outperforming
Very strong performance, strives to raise the bar, regularly exceeds goal expectations.
3. Performing
Good performance and consistently meets the expectations of the role.
2. Developing
Variable performance, requires additional support and time to develop in role.
1. UnderperformingUnderperforming
Does not meet performance expectations of the role.

Can you help to write overall summary not too long and kind of not too many fancy words also the rating

Overall Summary:
Over the past year, I have delivered strong technical and strategic outcomes that enhanced detection coverage, rule quality, and client satisfaction. I successfully developed and optimized a significant number of detection rules across multiple platforms, contributed to key client consultancy projects and advanced automation initiatives/opportunities. My proactive threat hunting identified previously undetected threats, strengthening overall security posture. I have also actively supported collaboration across teams, contributing to improved processes, knowledge sharing, and consistent high-quality delivery. These efforts have collectively driven measurable improvements in detection performance and operational efficiency.

Performance Rating: 4 – Outperforming
Demonstrated strong and consistent performance that regularly exceeded expectations. Delivered high-quality technical and strategic outcomes through innovative detection development, proactive threat hunting, and successful client delivery. Showed leadership in driving collaboration and contributing to automation efforts, raising the standard for quality, efficiency, and client satisfaction.