Skill UI

TLS 1.3 is the latest Transport Layer Security protocol, offering significant security and performance improvements over TLS 1.2. This guide details how to configure and validate TLS 1.3 on various environments, including Nginx, Apache, and Python applications. It covers advanced topics such as Perfect Forward Secrecy (PFS), HSTS implementation, modern cipher suites, and best practices for securing modern web services.

This comprehensive guide provides a structured, multi-stage workflow for containing active security breaches. It details both short-term and long-term strategies, including network segmentation, endpoint isolation, credential revocation, and evidence preservation. Use this process during confirmed intrusions, ransomware attacks, or lateral movement events to effectively stop adversary activity and secure critical assets before eradication.

Guides SOC teams through validating alerts, isolating networks and endpoints, preserving evidence, and disabling compromised accounts to rapidly contain an active breach while minimizing business impact.

This skill guides SOC analysts and detection engineers on how to correlate complex, multi-stage attacks within the IBM QRadar SIEM platform. It covers advanced usage of AQL (Ariel Query Language) for deep event investigation, building custom correlation rules (Building Blocks and Offenses), and cross-source data correlation (e.g., auth failures with network flows). It is essential for reducing false positives and improving threat detection accuracy.

This skill correlates disparate security incidents, Indicators of Compromise (IOCs), and adversary behaviors across time and organizations. It systematically identifies unified threat campaigns, attributes them to common threat actors, and extracts shared indicators for significantly improved detection capabilities. Ideal for cross-organizational threat intelligence sharing and building comprehensive campaign reports.

A comprehensive toolkit designed for cybersecurity professionals to deobfuscate malicious JavaScript code. It reverses complex encoding layers (Base64, Hex, Unicode), eval chains, and control flow obfuscation techniques found in phishing pages, web skimmers, and dropper scripts, revealing the original malicious logic for thorough forensic analysis and threat intelligence gathering.

This tool deploys decoy canary files in critical system directories to provide early warning against ransomware attacks. Utilizing Python's watchdog library, it monitors for any read, modify, rename, or delete operations on these decoy files. Detection triggers immediate alerts via multiple channels (Email, Slack, Syslog), helping security teams identify and respond to malicious activity before full data encryption occurs. It serves as a crucial detection layer in a layered security defense.

Tailscale provides a WireGuard-based, zero-trust mesh VPN solution. It establishes end-to-end encrypted, peer-to-peer connections using identity-aware controls and granular Access Control Lists (ACLs). Ideal for modernizing network security, replacing traditional VPNs, and ensuring compliant, identity-gated access across diverse environments (Cloud, On-Prem).

A comprehensive guide for security professionals on detecting and preventing ARP spoofing and poisoning attacks. The skill covers multiple layers of defense, including implementing Dynamic ARP Inspection (DAI) on managed switches, utilizing ARPWatch for continuous monitoring, performing deep packet inspection with Wireshark, and developing custom Python scripts for real-time anomaly detection. Essential for mitigating Man-in-the-Middle (MitM) attacks at Layer 2.

This skill analyzes AWS CloudTrail logs to detect suspicious API call patterns, such as new event sources, geographic anomalies, or high-frequency usage. It establishes a statistical baseline of normal activity and flags deviations indicative of compromised credentials, privilege escalation, or insider threats, providing a detailed JSON report for security investigation and threat hunting.

A comprehensive solution for identifying and preventing the accidental commitment of exposed AWS credentials, API keys, and session tokens within source code, configuration files, and git history. It integrates TruffleHog and git-secrets into CI/CD pipelines and pre-commit hooks, providing critical protection against credential theft and unauthorized cloud access in a DevSecOps environment. Essential for security auditing and compliance.

This skill analyzes AWS IAM policies using boto3 and Cloudsplaining principles to detect potential privilege escalation paths in AWS accounts. It identifies overly permissive policies, dangerous permission combinations (such as combining role passing and resource creation), and violations of least-privilege principles. It is designed for security incident investigation, threat hunting, and validating overall cloud security posture.