Worked on the Tencent/AI-Infra-Guard repository to enhance JupyterLab detection capabilities, focusing on improving asset inventory accuracy and vulnerability management. Addressed a critical issue in the YAML-based detection logic by refining the appVersion extraction regex, ensuring more reliable configuration management. Introduced fingerprinting improvements by adding an icon hash and standardized references to CVE-2025-53002, which increased the precision of vulnerability detection. These updates strengthened the reproducibility and correctness of system fingerprinting processes, reduced risk exposure, and improved the operational cleanliness of detection pipelines. The work demonstrated depth in YAML configuration, vulnerability management, and systematic enhancement of security telemetry workflows.