Skill UI

Query BindingDB for measured drug-target affinities (Ki, Kd, IC50, EC50) via REST endpoints or downloaded TSVs to support target-centric drug discovery, SAR analysis, lead profiling, and benchmarking datasets.

Access multi-dimensional cancer genomics data via cBioPortal REST API for mutation, copy-number, expression, and survival insights across TCGA/GENIE studies, enabling target validation and clinical association analyses programmatically with Python clients.

Access DepMap data to fetch CRISPR Chronos dependency scores, drug sensitivity readouts, and gene effect profiles for cancer cell lines, supporting target validation, biomarker discovery, and synthetic-lethality research via API or downloads.

This tool parses API Gateway access logs from various providers (AWS, Kong, Nginx). It performs statistical analysis using pandas to detect critical security threats such as Broken Object Level Authorization (BOLA/IDOR), credential stuffing, rate limit bypass attempts, and injection vulnerabilities. Ideal for SOC analysts or security engineers investigating API abuse and building advanced threat detection rules.

Detects abnormal access patterns across major cloud storage platforms, including AWS S3, GCS, and Azure Blob Storage. By analyzing cloud audit logs (CloudTrail, etc.), this tool identifies critical security threats such as after-hours bulk data downloads, sudden spikes in API calls (GetObject spikes), access from new geographic IPs, and potential data exfiltration. It utilizes statistical baselines and time-series anomaly detection for proactive threat hunting and security incident investigation.

This tool parses Kubernetes API server audit logs (JSON lines) to detect critical security events. It specifically targets unauthorized access, secret enumeration, RBAC escalation, privileged pod creation, and shell access (exec/attach). Use it for incident response, threat hunting, or building SIEM detection rules.

This skill implements User and Entity Behavior Analytics (UEBA) to detect sophisticated insider threats. It builds behavioral baselines from diverse log sources (authentication, file access, network) using Elasticsearch/OpenSearch. It calculates anomaly scores and performs peer group analysis to identify deviations indicative of data exfiltration, privilege abuse, or unauthorized access patterns.

This skill analyzes network logs, including proxy access logs, DNS query logs, and netflow data, to detect unauthorized Software as a Service (SaaS) applications and cloud services (Shadow IT). It classifies domains against known catalogs, measures data exfiltration volumes, calculates risk scores, and generates comprehensive reports for security and compliance teams.

This skill provides a structured methodology for detecting process injection techniques (MITRE ATT&CK T1055), which adversaries use for defense evasion and privilege escalation. It analyzes granular security logs, specifically utilizing Sysmon Event IDs 8 (CreateRemoteThread) and 10 (ProcessAccess), alongside source-target process relationship mapping to identify suspicious malicious behavior over general system activity.

A comprehensive guide on implementing AWS CloudTrail log analysis for robust security monitoring, threat detection, and forensic investigation. Learn how to configure CloudTrail, use Amazon Athena for SQL querying, and leverage CloudWatch Logs Insights and SIEM integration to identify unauthorized access, privilege escalation, and suspicious API activity across AWS services.

This skill performs User and Entity Behavior Analytics (UEBA) to identify anomalous user activities such as impossible travel, unusual access patterns, and privilege abuse. It establishes behavioral baselines using SIEM logs and statistical analysis, helping SOC teams detect insider threats and compromised accounts by flagging deviations from normal user behavior. Use when monitoring security hygiene and suspicious activity is critical.

This comprehensive guide provides a detailed workflow for parsing Windows LNK shortcut files in a digital forensics context. It extracts critical artifacts including target paths, timestamps (creation, access, modification), volume serial numbers, and machine identifiers. It is essential for reconstructing user file access history, tracking accessed files on network shares, and building robust forensic timelines.