Skill UI

This tool provides comprehensive analysis of the cybersecurity threat landscape using the Malware Information Sharing Platform (MISP). It allows users to query event statistics, analyze attribute distributions (IPs, domains, hashes), identify top threat actors and malware families, and track temporal trends. It is essential for SOC analysts performing incident response, threat hunting, and building advanced detection rules.

This skill provides a comprehensive workflow for building vendor-agnostic detection rules using the Sigma format. It empowers security operations center (SOC) engineers to translate raw threat intelligence and MITRE ATT&CK techniques into standardized, portable detection logic. The process guides users through rule validation and conversion into specific queries for major SIEM platforms, including Splunk, Elastic, and Microsoft Sentinel, ensuring robust detection coverage.

This skill outlines the development of an automated pipeline to ingest raw Indicators of Compromise (IOCs) from various sources. It performs normalization, defanging (e.g., converting 'http://' to 'hxxp://'), and converts indicators into the standardized STIX 2.1 format. The processed, safe indicators can then be securely distributed via TAXII feeds, MISP, and other threat intelligence platforms.

This framework provides structured templates for managing communications during malware incidents. It generates tailored reports for various stakeholders, including C-level executives, technical IT teams, and regulatory bodies. The system accounts for severity levels (P1-P4) and different threat types, ensuring consistent, timely, and compliant information dissemination during a crisis.

This guide details the deployment and usage of MISP (Malware Information Sharing Platform) to centralize, correlate, and distribute threat intelligence. It covers architectural concepts, integrating diverse OSINT and commercial feeds (like abuse.ch, AlienVault OTX), and automating the flow of Indicators of Compromise (IOCs) into SIEM and SOAR systems via Docker and Python APIs.

A comprehensive system for systematically collecting, categorizing, and enriching Indicators of Compromise (IOCs) from various sources (network logs, memory dumps, email, etc.). It supports the entire incident response lifecycle, ensuring structured data representation using STIX/TAXII formats for robust threat intelligence sharing and defensive system automation.

MISP (Malware Information Sharing Platform) is an open-source platform designed for gathering, storing, and correlating Indicators of Compromise (IOCs). This skill guides users through deploying MISP using Docker, configuring various threat feeds (MISP, TAXII, CSV), and utilizing the PyMISP Python API. It enables the building of automated pipelines to aggregate diverse threat data, such as IP addresses, domains, and hashes, for enhanced security operations.

This guide details the comprehensive deployment of Palo Alto Networks Prisma Access for implementing a modern SASE-based Zero Trust Network Access (ZTNA). It covers configuring the cloud infrastructure, deploying ZTNA Connectors, defining granular application policies, enforcing device posture via Host Information Profile (HIP), and utilizing GlobalProtect agents for secure, enterprise-grade remote access.

This tool analyzes Web Application Firewall (WAF) logs (ModSecurity, AWS WAF, Cloudflare) to detect sophisticated SQL injection attack campaigns. It parses diverse log formats, identifies common SQLi payloads (UNION SELECT, OR 1=1), correlates multi-stage attacks, tracks source IPs, and generates detailed incident reports classified by OWASP standards for SOC analysts and security researchers.

This skill guides security testers in identifying excessive data exposure in REST and GraphQL APIs. It involves intercepting API responses and analyzing them for leaked Personally Identifiable Information (PII), internal identifiers, or sensitive business data that the client UI does not display but the API transmits. It maps directly to OWASP API3:2023 Broken Object Property Level Authorization, helping prevent data leaks via over-fetching.

This utility performs comprehensive forensic analysis on memory dumps. It leverages industry-standard tools like Volatility and Mimikatz to extract sensitive information, including cached credentials, NTLM/LM hashes, Kerberos tickets, and authentication tokens. It is crucial for incident response, assessing the scope of credential compromise, and investigating lateral movement attacks.

This skill detects anti-forensic timestomping by analyzing NTFS Master File Table (MFT) entries. It compares timestamps from the $STANDARD_INFORMATION attribute (user-modifiable) against the $FILE_NAME attribute (kernel-protected). Discrepancies, such as SI Created < FN Created, strongly indicate malicious manipulation and defense evasion. This methodology is crucial for advanced threat hunting and digital forensic investigations.