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Found 39 Skills
Analyzes system and application logs to detect anomalies and security threats in blue-team operations.
Predictive analytics for Dynatrace — time series forecasting with the timeseries-forecast tool, capacity saturation planning, trend and anomaly detection across hosts, services, and infrastructure.
Real-time monitoring and detection of adversarial attacks and model drift in production
Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.
This skill covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, detect outliers, find key drivers, or leverage generative AI capabilities in BigQuery.
Expert knowledge for Azure AI Metrics Advisor development including decision making, security, configuration, and integrations & coding patterns. Use when configuring data feeds, tuning anomaly detection, managing alert hooks, or integrating the Metrics Advisor APIs, and other Azure AI Metrics Advisor related development tasks. Not for Azure AI Anomaly Detector (use azure-anomaly-detector), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
Guides structured security log analysis across authentication, network, endpoint, and cloud audit log sources. Auto-invoked when the user shares log data, asks about suspicious events, needs help interpreting Windows Event IDs or Linux auth logs, or is establishing baselines for anomaly detection. Produces log source taxonomy, anomaly identification, baseline recommendations, and correlation findings mapped to MITRE ATT&CK v16 techniques.
Use when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.
Detect anomalies in data using statistical and ML methods. Z-score, IQR, Isolation Forest, and time-series anomalies.
Investigate traffic anomalies, spikes, and service degradation on Cloudflare-protected domains. Uses Cloudflare MCP tools for GraphQL analytics, JA4 fingerprint analysis, bot/WAF security scoring, and incident reporting. Use this skill whenever traffic spikes, service overloads, 429 errors, circuit breaker events, Cloudflare analytics, or domain performance issues are mentioned — even if the user doesn't explicitly say "traffic spike". Also triggers when asked to check Cloudflare data for any domain.
Expert in data forensics, anomaly detection, audit trail analysis, fraud detection, and breach investigation