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Malicious URL Analysis Workflow

analyzing-malicious-url-with-urlscan

mukul975/Anthropic-Cybersecurity-Skills

Step-by-step guide for using URLScan.io via web UI and API to investigate phishing and credential-harvesting URLs, capture page screenshots, DOM, network logs, and certificates, extract IOCs, and correlate results with VirusTotal, PhishTank, and Google Safe Browsing while keeping analysts isolated.

Autoruns Malware Persistence Analysis

analyzing-malware-persistence-with-autoruns

mukul975/Anthropic-Cybersecurity-Skills

Use Sysinternals Autoruns to scan Windows ASEPs, flag unsigned binaries, suspicious paths, and LOLBin launch strings, compare results to clean baselines, and validate persistence indicators for malware hunting and response.

Phishing Email Header Analysis

analyzing-phishing-email-headers

mukul975/Anthropic-Cybersecurity-Skills

Analyze email headers to uncover sender origins, routing chains, and authentication results, enabling defenders to validate legitimacy and spot phishing indicators using manual inspection and automation scripts.

Arxiv Paper Retriever

wanshuiyin/Auto-claude-code-research-in-sleep

Searches arXiv for topics or IDs, lists results with metadata, downloads PDFs into a local library, and summarizes titles, authors, categories, abstracts, and contributions for easy literature review.

DefectDojo Vulnerability Dashboard

building-vulnerability-dashboard-with-defectdojo

mukul975/Anthropic-Cybersecurity-Skills

Deploy DefectDojo as a centralized vulnerability dashboard that aggregates scanner results, deduplicates findings, tracks metrics, and feeds Jira/CI/CD workflows for security teams.

Vulnerability Scanning Workflow

building-vulnerability-scanning-workflow

mukul975/Anthropic-Cybersecurity-Skills

Creates a structured vulnerability scanning workflow that uses Nessus, Qualys, or OpenVAS to discover, prioritize, and track remediation across infrastructure, integrates scan results with SIEM and dashboards, and defines cadence, risk-based prioritization, and SLA-driven remediation tracking for SOC teams.

AI Data Scraping Agent

data-scraper-agent

affaan-m/everything-claude-code

Build an automated AI-driven collector that monitors any public source—jobs, pricing, news, GitHub, sports, etc.—enriches results via Gemini Flash, stores them in Notion/Sheets/Supabase, runs on GitHub Actions, and learns from feedback.

Distroless Minimal Container Image

implementing-container-image-minimal-base-with-distroless

mukul975/Anthropic-Cybersecurity-Skills

Guides teams on building container images with Google Distroless minimal bases to shrink attack surfaces by removing shells and package managers, covering image choices, multi-stage build patterns, debugging guidance, and scan results for hardened deployments.

Continuous Security Validation

implementing-continuous-security-validation-with-bas

mukul975/Anthropic-Cybersecurity-Skills

Automates continuous validation of security controls by emulating real attack techniques with BAS platforms such as SafeBreach, AttackIQ, or Cymulate, aligning results with MITRE ATT&CK and operational readiness.

Osquery Endpoint Monitoring Setup

implementing-osquery-for-endpoint-monitoring

mukul975/Anthropic-Cybersecurity-Skills

Automate the deployment of osquery scheduled queries to continuously monitor endpoints, covering process inventory, network listeners, file integrity, and persistence mechanisms; generate osquery.conf, configure differential logging, analyze suspicious results, and produce a security report.

Phishing SOAR Playbook Automation

implementing-soar-playbook-for-phishing

mukul975/Anthropic-Cybersecurity-Skills

Automates phishing incident response by parsing suspicious emails, creating Splunk SOAR containers and artifacts via the REST API, and triggering investigation playbooks while polling for results to deliver summarized verdicts.

Monitor Experiment Results

monitor-experiment

wanshuiyin/Auto-claude-code-research-in-sleep

Track running experiments by inspecting remote screen sessions, gathering logs, parsing JSON outputs, and optionally pulling WandB metrics before summarizing baselines, deltas, and costs for Vast.ai or Modal runs.

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