March 20, 2024
• Project
An intelligent code review assistant that uses machine learning to identify potential bugs, security vulnerabilities, and code quality issues automatically.
Features Automated Code Analysis: Leverages GPT-4 and custom ML models to analyze pull requests Security Scanning: Detects common security vulnerabilities (SQL injection, XSS, etc.) Code Quality Metrics: Provides detailed metrics on code complexity, maintainability Integration: Works with GitHub, GitLab, and Bitbucket Custom Rules: Define team-specific coding standards Tech Stack Backend: Python, FastAPI, PostgreSQL ML: TensorFlow, Transformers, OpenAI GPT-4 Frontend: React, TypeScript, Tailwind CSS Infrastructure: Docker, Kubernetes, AWS Key Achievements Reduced code review time by 40% Detected 95% of security vulnerabilities before production Used by 500+ developers across 50+ repositories 99.
Read more →September 20, 2023
• Project
An automated threat intelligence platform that aggregates data from multiple sources, identifies patterns, and provides actionable security insights.
Problem Security teams are overwhelmed with threat data from various sources. Manual analysis is time-consuming and misses emerging threats.
Solution Automated platform that:
Aggregates threat feeds from 50+ sources Uses ML to identify patterns and correlations Prioritizes threats based on risk scoring Provides remediation recommendations Integrates with existing security tools (SIEM, firewalls) Key Features Threat Aggregation Real-time collection from OSINT sources Commercial threat feed integration Dark web monitoring Vulnerability databases (CVE, NVD) Intelligence Analysis ML-based threat classification IOC (Indicator of Compromise) extraction Attack pattern recognition Attribution analysis Automation Automated threat hunting queries SOAR integration for response Custom alert rules Report generation Technical Stack Backend: Python, FastAPI, Celery Database: ElasticSearch, PostgreSQL ML: Scikit-learn, NLTK, spaCy Frontend: Vue.
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