{"id":20508996,"url":"https://github.com/tdevuit/ie105-malicious-code-scanner","last_synced_at":"2026-04-08T20:36:41.346Z","repository":{"id":260091646,"uuid":"880245829","full_name":"TDevUIT/IE105-Malicious-Code-Scanner","owner":"TDevUIT","description":"A Next.js 14 application that leverages machine learning models to detect malicious code in uploaded files, featuring a FastAPI backend.","archived":false,"fork":false,"pushed_at":"2024-10-29T11:55:18.000Z","size":62,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-05T22:25:21.023Z","etag":null,"topics":["fastapi","malicious","nextjs","python","typescript"],"latest_commit_sha":null,"homepage":"https://ie-105-malicious-code-scanner.vercel.app","language":"TypeScript","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/TDevUIT.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-10-29T11:39:53.000Z","updated_at":"2024-11-01T08:26:17.000Z","dependencies_parsed_at":"2024-10-29T13:53:37.051Z","dependency_job_id":null,"html_url":"https://github.com/TDevUIT/IE105-Malicious-Code-Scanner","commit_stats":null,"previous_names":["vanthaita/ie105-malicious-code-scanner"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/TDevUIT/IE105-Malicious-Code-Scanner","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TDevUIT%2FIE105-Malicious-Code-Scanner","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TDevUIT%2FIE105-Malicious-Code-Scanner/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TDevUIT%2FIE105-Malicious-Code-Scanner/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TDevUIT%2FIE105-Malicious-Code-Scanner/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TDevUIT","download_url":"https://codeload.github.com/TDevUIT/IE105-Malicious-Code-Scanner/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TDevUIT%2FIE105-Malicious-Code-Scanner/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31573788,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-08T14:31:17.711Z","status":"ssl_error","status_checked_at":"2026-04-08T14:31:17.202Z","response_time":54,"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":["fastapi","malicious","nextjs","python","typescript"],"created_at":"2024-11-15T20:21:43.130Z","updated_at":"2026-04-08T20:36:41.329Z","avatar_url":"https://github.com/TDevUIT.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://ie-105-malicious-code-scanner.vercel.app/\"\u003e\n    \u003cimg src=\"https://github.com/user-attachments/assets/86d7edbe-df3f-4c3e-86b3-11f21bb11d5e\" height=\"96\" alt=\"QR code scan\"\u003e\n    \u003ch3 align=\"center\"\u003eMalicious Code Scanner\u003c/h3\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003eA Next.js 14 application that leverages machine learning models to detect malicious code in uploaded files, featuring a FastAPI backend.\u003c/p\u003e\n\n\u003cbr/\u003e\n\n## Introduction\n\nThe **Malicious Code Scanner** is a robust web app developed using Next.js and FastAPI, designed to enable users to upload files in various formats and scan for potential malicious code. It features a user-friendly, dashboard-like UI for selecting models, monitoring upload progress, and displaying scan results. This tool is ideal for developers and security teams needing quick, reliable file safety assessments using custom AI/ML models.\n\n## How It Works\n\nThe Python/FastAPI backend handles the AI/ML models, seamlessly integrated with the Next.js frontend through `/api/` endpoints. File uploads trigger model-based scans, with results presented in a structured dashboard format.\n\nThe integration is facilitated through [`next.config.js` rewrites](https://github.com/vanthaita/malicious-code-scanner/blob/main/next.config.js), routing requests to `/api/py/:path*` directly to FastAPI.\n\nLocally, the FastAPI server runs at `127.0.0.1:8000`, while in production, it operates as [serverless Python functions](https://vercel.com/docs/concepts/functions/serverless-functions/runtimes/python) on Vercel.\n\n## Demo\n\nExplore the live demo here: [Malicious Code Scanner](https://ie-105-malicious-code-scanner.vercel.app/)\n\n## Deploy Your Own\n\nClone \u0026 deploy it to Vercel in one click:\n\n[![Deploy with Vercel](https://vercel.com/button)](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2Fvanthaita%2Fmalicious-code-scanner%2Ftree%2Fmain)\n\n## Developing Locally\n\nSet up the repository with:\n\n```bash\nnpx create-next-app malicious-code-scanner --example \"https://github.com/vanthaita/IE105-Malicious-Code-Scanner.git\"\n```\n\n## Getting Started\n\n### 1. Set up a virtual environment\n\n```bash\npython3 -m venv venv\nsource venv/bin/activate\n```\n\n### 2. Install dependencies\n\nFor the frontend, run:\n\n```bash\nnpm install\n# or\nyarn\n# or\npnpm install\n```\n\nFor the backend, install Python packages listed in `requirements.txt`.\n\n### 3. Run the development server\n\nStart the development server:\n\n```bash\nnpm run dev\n# or\nyarn dev\n# or\npnpm dev\n```\n\nAccess the app at [http://localhost:3000](http://localhost:3000), with the FastAPI backend running at [http://127.0.0.1:8000](http://127.0.0.1:8000). Update the port in `package.json` and `next.config.js` as needed.\n\n## Key Features\n\n- **File Uploads**: Supports PDF and other common file formats.\n- **Model Selection**: Allows users to choose from multiple models (in `.h5` format) for scanning.\n- **Progress \u0026 Results Display**: Visualize scan progress and results in a dashboard format with graphical displays.\n\n## Learn More\n\nFor further resources, check out:\n\n- [Next.js Documentation](https://nextjs.org/docs)\n- [FastAPI Documentation](https://fastapi.tiangolo.com/)\n\nWe welcome your feedback and contributions via [our GitHub repository](https://github.com/vanthaita/malicious-code-scanner)!\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftdevuit%2Fie105-malicious-code-scanner","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftdevuit%2Fie105-malicious-code-scanner","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftdevuit%2Fie105-malicious-code-scanner/lists"}