Skill UI

This guide details the implementation of a robust, ransomware-resilient backup architecture following the extended 3-2-1-1-0 rule. It covers critical steps such as classifying assets, defining RPO/RTO, implementing immutable or air-gapped storage, and isolating backup credentials from the production domain. Use this knowledge to design a multilayered defense against data loss and ensure reliable recovery points.

This skill guides the deployment and comprehensive configuration of Rapid7 InsightVM. It covers setting up the Security Console and distributed Scan Engines for both authenticated and unauthenticated vulnerability scanning. Learn how to manage diverse scan templates (e.g., PCI, HIPAA), utilize various credential types (SSH, WMI), and integrate endpoint assessment for robust cybersecurity posture management.

Implement Kubernetes RBAC to enforce least-privilege access across namespaces, covering Role/ClusterRole design, binding configuration, service account hardening, OIDC integration, and audit logging for multi-tenant clusters.

This skill guides the implementation of Gitleaks for robust secret scanning across development lifecycles. It covers setting up pre-commit hooks to prevent secrets from being committed, integrating scanning into CI/CD pipelines (like GitHub Actions), and writing custom regex rules to detect and remediate hardcoded credentials (API keys, passwords, tokens) in Git history, ensuring adherence to secure SDLC practices.

This comprehensive guide details the deployment of HashiCorp Vault for robust, centralized secrets management in hybrid and multi-cloud environments. It covers configuring dynamic secret engines for databases (PostgreSQL) and cloud providers (AWS), integrating diverse authentication methods (OIDC, AppRole, Kubernetes), and securely delivering short-lived secrets to Kubernetes workloads via agents. The primary goal is to enforce zero-trust principles by eliminating hardcoded, long-lived credentials from application code and CI/CD pipelines.

This skill guides the implementation of security chaos engineering experiments. It involves deliberately degrading or disabling security controls (like WAF, firewalls, or log pipelines) in a controlled environment to rigorously verify the detection, alerting, and response capabilities of the Security Operations Center (SOC). Users learn to use tools like boto3 and Python to simulate failure scenarios and assess system resilience and compliance posture.

This guide details the implementation of comprehensive security monitoring using Datadog Cloud SIEM, Cloud Security Management (CSM), and Workload Protection. It covers deploying the Datadog Agent across hybrid cloud infrastructure (AWS, Azure, GCP), ingesting critical log sources (CloudTrail, VPC Flow Logs, etc.), configuring Workload Protection, and creating custom detection rules to detect threats, enforce compliance, and provide centralized SOC visibility.

This guide details how to implement advanced SIEM correlation rules to detect sophisticated Advanced Persistent Threats (APTs). By chaining multiple event types—including Windows authentication events, process execution telemetry, and network connection logs—across hosts, users can surface complex attack sequences that are invisible to single-event detections. It utilizes Splunk SPL and Sigma rule formats for robust security posture enhancement.

Systematically optimizes Security Information and Event Management (SIEM) detection rules in platforms like Splunk and Elastic. This process involves analyzing historical alert volumes, establishing environmental baselines, creating context-aware whitelists, and statistically adjusting detection thresholds to significantly reduce false positives, improving overall security efficacy.

This skill guides the process of designing, implementing, and validating advanced security detection use cases for Security Information and Event Management (SIEM) platforms like Splunk, Elastic, and Microsoft Sentinel. It focuses on mapping organizational threat profiles to the MITRE ATT&CK framework to build formal, high-fidelity detection rules, thereby strengthening Security Operations Center (SOC) coverage and reducing blind spots.

This skill guides the implementation of Security Orchestration, Automation, and Response (SOAR) workflows using platforms like Splunk Phantom. It automates the entire incident lifecycle, including alert triage, IOC enrichment (via VirusTotal, CrowdStrike), containment actions, and ticket creation (ServiceNow). Ideal for SOC teams needing to reduce Mean Time To Respond (MTTR) and standardize complex security procedures across multiple tools.

This guide details how to implement sophisticated Security Orchestration, Automation, and Response (SOAR) playbooks using Palo Alto Cortex XSOAR. It demonstrates full lifecycle automation, such as phishing incident investigation, requiring enrichment of URLs, IPs, and files, followed by automated containment actions (e.g., blocking senders, purging mailboxes). Mastering this allows SOC teams to drastically reduce Mean Time To Respond (MTTR) by automating detection, analysis, and remediation steps across multiple security tools.