Skill UI

This skill provides a comprehensive framework for monitoring Mistral AI API usage in production. It includes an instrumented client wrapper (TypeScript) to automatically capture critical metrics like latency, token consumption, cost, and error rates. Furthermore, it integrates with Prometheus for metric storage and Grafana for visualization, allowing users to set up sophisticated alerting rules for performance degradation, rate limiting, or cost spikes.

This skill guides users through analyzing suspicious URLs using the URLScan.io platform or API. It provides a safe environment to capture screenshots, DOM content, network traffic, and analyze JavaScript behavior to investigate phishing attempts, credential harvesting, and sophisticated malicious redirects without risking the analyst's system.

A comprehensive guide for analyzing PCAP files captured during malware execution. It demonstrates advanced techniques using Wireshark, Zeek, Suricata, and Python (scapy) to identify Command and Control (C2) communications, data exfiltration channels, Domain Generation Algorithms (DGA), and periodic beaconing patterns. Essential for malware reverse engineering and network threat detection.

A comprehensive guide for deep packet inspection and network forensics using Wireshark and tshark. This skill is critical for incident response, where it allows users to capture, filter, and analyze network packet data to identify malicious command-and-control traffic, diagnose complex protocol issues, extract indicators of compromise (IOCs), and reconstruct data exfiltration paths. Use it for validating security rules and understanding network anomalies.

A comprehensive guide to deploying and configuring Suricata, a high-performance IDS/IPS. This skill covers setting up multi-threaded packet capture, integrating Emerging Threats rulesets, generating structured EVE JSON logs, and enabling deep protocol inspection (HTTP, TLS, DNS). It enables real-time threat detection and seamless SIEM integration for centralized security monitoring.

CAPE is an open-source sandbox built for automated malware analysis, derived from Cuckoo. It provides advanced behavioral monitoring, payload dumping, and configuration extraction using over 70 parsers for known malware families (e.g., Emotet, Cobalt Strike). It captures network IOCs, dropped files, and detects anti-evasion techniques, making it ideal for security assessments and incident response workflows via its robust API.

This comprehensive guide outlines a structured workflow for conducting digital forensics investigations across major cloud providers, including AWS, Azure, and GCP. It covers critical steps such as evidence preservation (snapshots, metadata capture), systematic log collection (CloudTrail, Activity Logs, Audit Logs, VPC Flow Logs), and advanced analysis techniques to trace unauthorized accesses and identify root causes of security breaches.

A comprehensive guide to executing cloud-native incident containment procedures across major platforms including AWS, Azure, and GCP. Learn how to systematically isolate compromised resources, revoke malicious credentials, apply network restrictions (Security Groups/ACLs), and capture forensic evidence to prevent lateral movement during a security event. Essential for security assessments and incident response.

A comprehensive provider for integrating Eufy security cameras (supporting local P2P or cloud connectivity). This tool facilitates stable RTSP streaming for live monitoring and efficiently captures event-triggered video clips. It is designed for advanced systems that require continuous video feeds and reliable event-based data input for AI analysis and monitoring solutions.

This tool provides comprehensive integration for Reolink security cameras, supporting both RTSP streaming and HTTP API access. It allows users to discover cameras via ONVIF, capture live streams, take snapshots, and even capture motion-triggered video clips. It is ideal for developers building robust, networked surveillance or monitoring systems.

This skill helps users create specialized 'steering documents' or project memory for highly specific domains (e.g., API standards, testing strategies, security patterns). By analyzing the existing codebase and following predefined architectural principles, it synthesizes concise, actionable guides that capture technical patterns, best practices, and domain-specific rules, ensuring project consistency and knowledge retention.

This skill provides a deep dive into the architecture of low-level keyloggers. It covers techniques such as kernel driver hooks, using WH_KEYBOARD_LL, ETW-based input capture, and analyzing user-mode vs. kernel-mode approaches. Use this methodology to understand input capture mechanisms, research EDR evasion methods, or analyze malware architecture for advanced security threat detection.