FEUP-MEIC-DS-2024-25/ai4sd
Nov 2024 – Dec 2024
2 Months active
Languages Used
DockerfilePythonJavaScript
Technical Skills
API DevelopmentCode AnalysisDockerFastAPIGenerative AIOllama
Daniel Cabral Bernardo
PROFILE
Daniel Cabral Bernardo
Daniel contributed to the FEUP-MEIC-DS-2024-25/ai4sd repository by developing and containerizing the WardenAI code vulnerability analysis tool. He implemented a Docker-based workflow using Python and FastAPI, enabling reproducible local and runtime environments for security analysis. Daniel integrated Ollama’s llama3.1 and Google Cloud Vertex AI to provide both online and offline vulnerability assessments, exposing API endpoints that return structured JSON results. He also enhanced the tool’s reporting capabilities by adding features in JavaScript and React to export vulnerability reports in plain text and Markdown with timestamped files, improving data portability, traceability, and usability for security teams.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
206
Activity Months2
Work History
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for FEUP-MEIC-DS-2024-25/ai4sd: Delivered a feature to download vulnerability reports in plain text and Markdown formats, with a refactored export flow that generates timestamped report files for easier archiving and sharing. This enhances data portability and usability of the Warden AI assistant. No major bugs fixed this month. Overall impact: reduced manual steps, strengthened security reporting capabilities, and better traceability. Technologies/skills demonstrated: JavaScript/TypeScript module refactor, file I/O for timestamped exports, format-specific export logic, and commit-based change traceability.
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for FEUP-MEIC-DS-2024-25/ai4sd: Delivered a feature to download vulnerability reports in plain text and Markdown formats, with a refactored export flow that generates timestamped report files for easier archiving and sharing. This enhances data portability and usability of the Warden AI assistant. No major bugs fixed this month. Overall impact: reduced manual steps, strengthened security reporting capabilities, and better traceability. Technologies/skills demonstrated: JavaScript/TypeScript module refactor, file I/O for timestamped exports, format-specific export logic, and commit-based change traceability.
December 2024
November 2024
1 Commits • 1 Features
Nov 1, 2024Month 2024-11 — Delivered WardenAI Code Vulnerability Analysis Tool Setup in the FEUP-MEIC-DS-2024-25/ai4sd repository. Implemented a containerized workflow with a Dockerfile and Python scripts to set up and run WardenAI, a code vulnerability analysis tool leveraging Ollama (llama3.1) and Google Cloud Vertex AI (gemini-1.5-flash-002). Exposed API endpoints for online and offline analysis that return JSON results. This work establishes a reproducible, scalable security analysis workflow that can be integrated into CI/CD pipelines and security dashboards.
November 2024
1 Commits • 1 Features
Nov 1, 2024Month 2024-11 — Delivered WardenAI Code Vulnerability Analysis Tool Setup in the FEUP-MEIC-DS-2024-25/ai4sd repository. Implemented a containerized workflow with a Dockerfile and Python scripts to set up and run WardenAI, a code vulnerability analysis tool leveraging Ollama (llama3.1) and Google Cloud Vertex AI (gemini-1.5-flash-002). Exposed API endpoints for online and offline analysis that return JSON results. This work establishes a reproducible, scalable security analysis workflow that can be integrated into CI/CD pipelines and security dashboards.
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance90.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
DockerfileJavaScriptPython
Technical Skills
API DevelopmentCode AnalysisDockerFastAPIFrontend DevelopmentGenerative AIOllamaPythonReactVertex AI
Repositories Contributed To
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