{"id":47712610,"url":"https://github.com/pangerlkr/ctias-lab","last_synced_at":"2026-04-02T18:40:33.618Z","repository":{"id":335027942,"uuid":"1143843725","full_name":"pangerlkr/ctias-lab","owner":"pangerlkr","description":"Multi-language cybersecurity platform for threat intelligence, IOC analysis, attack surface mapping, and collaborative threat detection","archived":false,"fork":false,"pushed_at":"2026-02-16T15:25:47.000Z","size":101,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-02-16T22:27:59.192Z","etag":null,"topics":["cybersecurity"],"latest_commit_sha":null,"homepage":"https://pangerlkr.github.io/ctias-lab","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pangerlkr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-01-28T02:52:36.000Z","updated_at":"2026-02-16T15:25:52.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/pangerlkr/ctias-lab","commit_stats":null,"previous_names":["pangerlkr/ctias-lab"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/pangerlkr/ctias-lab","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangerlkr%2Fctias-lab","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangerlkr%2Fctias-lab/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangerlkr%2Fctias-lab/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangerlkr%2Fctias-lab/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pangerlkr","download_url":"https://codeload.github.com/pangerlkr/ctias-lab/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pangerlkr%2Fctias-lab/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31313150,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-02T12:59:32.332Z","status":"ssl_error","status_checked_at":"2026-04-02T12:54:48.875Z","response_time":89,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cybersecurity"],"created_at":"2026-04-02T18:40:32.883Z","updated_at":"2026-04-02T18:40:33.604Z","avatar_url":"https://github.com/pangerlkr.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Cyber Threat Intelligence \u0026 Attack Surface Lab (CTIAS Lab)\n\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![Python 3.9+](https://img.shields.io/badge/Python-3.9%2B-blue)](https://www.python.org/downloads/)\n[![Java 11+](https://img.shields.io/badge/Java-11%2B-red)](https://www.oracle.com/java/)\n[![Docker](https://img.shields.io/badge/Docker-Supported-blue)](https://www.docker.com/)\n\nA **multi-language, extensible cybersecurity platform** for threat analysis, IOC enrichment, attack surface reconnaissance, and collaborative threat detection. Built with **Python, Java, JavaScript, HTML, and CSS** for enterprise-grade threat intelligence and detection operations.\n\n---\n\n## Project Goals\n\nCTIAS Lab empowers security analysts, students, and researchers to:\n\n- **Run collaborative threat analysis** in a controlled, sandboxed environment\n- **Analyze Indicators of Compromise (IOCs)** using ML and rule-based detection\n- **Perform attack surface reconnaissance** with visual mapping and recon modules\n- **Build custom detection rules** and contribute them back to the community\n- **Learn cybersecurity** through guided labs and real-world attack scenarios\n- **Integrate multiple languages** seamlessly into a single threat intel platform\n\n---\n\n## Key Features\n\n### 1. Attack Surface Mapping\n- Discover and map target infrastructure (domains, IPs, services)\n- Visual graph representation of hosts, ports, and vulnerabilities\n- Multi-stage recon modules: DNS, WHOIS, SSL/TLS fingerprinting, port scanning\n\n### 2. IOC Analyzer\n- Submit IPs, domains, URLs, file hashes for analysis\n- Parallel processing with Python, Java, and JS modules\n- Reputation checks, malware correlation, and threat feeds\n\n### 3. Event \u0026 Log Processing\n- Upload logs (Apache, Nginx, Windows, syslog, etc.)\n- Parse and normalize events with Java-based engines\n- Real-time detection with ML anomaly detectors and rule engines\n\n### 4. Rule \u0026 Playbook Studio\n- YAML/JSON rule editor with live validation\n- Sigma-like rule format for portability\n- Test rules against sample data before deployment\n\n### 5. Training Lab\n- Guided cybersecurity exercises with real attack traces\n- Interactive scenarios demonstrating detection and response\n- Sample datasets, playbooks, and best practices\n\n### 6. Multi-Language Architecture\n- **Python**: ML models, PCAP analysis, IOC enrichment, anomaly detection\n- **Java**: Log normalization, rule engines, high-throughput processing\n- **JavaScript**: Browser-based analyzers, URL deobfuscation, client-side crypto\n- **Go/Rust (Optional)**: Fast scanners, OSINT collectors, performance-critical tasks\n\n---\n\n## Quick Start\n\n### Prerequisites\n- Docker \u0026 Docker Compose (recommended)\n- OR: Python 3.9+, Java 11+, Node.js 16+, PostgreSQL 13+\n- Git\n\n### Clone \u0026 Deploy\n\n```bash\ngit clone https://github.com/pangerlkr/ctias-lab.git\ncd ctias-lab\ndocker-compose up -d\n```\n\nThen open: **http://localhost:3000** (Frontend) and **http://localhost:8000** (API)\n\n---\n\n## Project Structure\n\n```\nctias-lab/\n  frontend/                 # React/Vue SPA + UI components\n  gateway/                  # Python FastAPI backend\n  modules-java/             # Java microservices\n  modules-python/           # Python analysis modules\n  modules-js/               # JavaScript/TypeScript analyzers\n  rules/                    # Community-contributed detection rules\n  scenarios/                # Training labs \u0026 sample datasets\n  docs/                     # Architecture, operations, contributing\n  docker/                   # Docker Compose \u0026 Dockerfiles\n  tests/                    # Integration \u0026 unit tests\n  CONTRIBUTING.md\n  SECURITY.md\n  LICENSE (MIT)\n```\n\nSee [ARCHITECTURE.md](./docs/ARCHITECTURE.md) for detailed system design.\n\n---\n\n## Technology Stack\n\n| Component | Technology | Purpose |\n|-----------|-----------|----------|\n| **Frontend** | React/Vue, HTML5, CSS3, Chart.js | Web UI for analysts |\n| **Gateway API** | Python FastAPI | REST/GraphQL API, job orchestration |\n| **Backend Services** | Java, Spring Boot | High-performance processing |\n| **ML/Analysis** | Python, scikit-learn, pandas | Anomaly detection, enrichment |\n| **Web Tools** | JavaScript, TypeScript | Browser-based analyzers |\n| **Database** | PostgreSQL | Events, rules, users |\n| **Cache/Queue** | Redis | Job queue, session cache |\n| **Containerization** | Docker, Docker Compose | Reproducible deployments |\n| **CI/CD** | GitHub Actions | Automated testing \u0026 releases |\n\n---\n\n## Contributing\n\nWe welcome contributions from security professionals, data scientists, and developers. See [CONTRIBUTING.md](./CONTRIBUTING.md) for:\n\n- How to add new detection modules in Java, Python, or JavaScript\n- Language-specific style guides\n- Testing \u0026 CI/CD requirements\n- Pull request workflow\n\n### Quick Contribution Paths\n\n**For Security Engineers**: Add detection rules, log parsers, and playbooks  \n**For Data Scientists**: Implement ML models and anomaly detectors  \n**For Full-Stack Developers**: Enhance UI, add API endpoints, optimize performance  \n**For DevOps Engineers**: Create Kubernetes manifests and CI/CD pipelines  \n\n---\n\n## Documentation\n\n- **[ARCHITECTURE.md](./docs/ARCHITECTURE.md)** - System design, module contracts, data flow\n- **[THREAT_MODELS.md](./docs/THREAT_MODELS.md)** - Security assumptions, threat scenarios\n- **[OPERATIONS.md](./docs/OPERATIONS.md)** - Deploy, monitor, scale, troubleshoot\n- **[API_REFERENCE.md](./docs/API_REFERENCE.md)** - Gateway endpoints and schemas\n- **[CONTRIBUTING.md](./CONTRIBUTING.md)** - Developer onboarding guide\n\n---\n\n## Security \u0026 Ethics\n\n**CTIAS Lab is designed for defensive and educational purposes only.**\n\n- All reconnaissance and testing occurs in a **controlled lab environment**\n- Do **NOT** use this platform for unauthorized testing\n- Always obtain proper authorization before running any attack simulations\n- Comply with local laws and regulations\n- See **[SECURITY.md](./SECURITY.md)** for responsible disclosure\n\n---\n\n## Contact\n\n**Project Maintainer**: Pangerkumzuk Longkumer (@pangerlkr)  \n**Organization**: NEXUSCIPHERGUARD INDIA  \n**Contact**: contact@pangerlkr.link  \n**Location**: Kohima, Nagaland, India  \n\n---\n\n## License\n\nCTIAS Lab is licensed under the **MIT License**. See [LICENSE](./LICENSE) for details.\n\n---\n\n**Star this repo and contribute to make it better!**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpangerlkr%2Fctias-lab","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpangerlkr%2Fctias-lab","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpangerlkr%2Fctias-lab/lists"}