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Ai Cybersecurity Analyzer

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Cybersecurity Analyzer is an AI-powered web application that scans and analyzes Python code for security vulnerabilities. By combining cutting-edge AI with robu

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Описание

Cybersecurity Analyzer is an AI-powered web application that scans and analyzes Python code for security vulnerabilities. By combining cutting-edge AI with robust static analysis tools, this platform helps developers identify and resolve security issues in their codebase.

README

CI

Web app that analyzes Python code for security issues using Semgrep (static analysis) and an OpenAI Agents workflow via the Semgrep MCP server.

Features

  • Security scanning: Semgrep findings with AI-assisted explanation and remediation hints
  • Simple local dev: Next.js UI (port 3000) + FastAPI API (port 8000)
  • Single-container production: FastAPI serves the statically exported frontend on port 8000
  • Infrastructure as code: Terraform stacks for AWS / Azure / GCP (optional)

Stack

Layer Tech
Frontend Next.js (TypeScript), Tailwind
Backend Python 3.12, FastAPI, uv
Analysis Semgrep, MCP, OpenAI Agents
Infra Terraform (AWS, Azure, GCP)

Prerequisites

  • Python 3.12+ and uv
  • Node.js 20+ and npm
  • Docker (optional, for container run)
  • Terraform (optional, for cloud deploy)

Environment

Create a .env in the repo root (do not commit it):

  • OPENAI_API_KEY — OpenAI API access
  • SEMGREP_APP_TOKEN — Semgrep (Semgrep Cloud / App token as required by your setup)

Run locally

Backend (port 8000):

cd backend
uv sync
uv run server.py

Frontend (port 3000, separate terminal):

cd frontend
npm install
npm run dev

Open http://localhost:3000.

Run with Docker

From the repo root (with .env present):

docker build -t cyber-analyzer .
docker run --rm -p 8000:8000 --env-file .env cyber-analyzer

Open http://localhost:8000.

Repo layout

├── backend/     # FastAPI app, MCP / agent wiring
├── frontend/    # Next.js UI (static export in production)
├── terraform/   # azure/, gcp/, aws/ — infra as code
├── scripts/     # deploy-aws.sh, destroy-aws.sh
├── Dockerfile   # Single-container production build

Deployment

Terraform stacks live under:

  • terraform/aws (AWS App Runner + ECR)
  • terraform/azure (Azure Container Apps)
  • terraform/gcp (GCP Cloud Run)

See terraform/README.md for per-cloud details and prerequisites.

Deploy with scripts (recommended)

From the repo root:

aws sts get-caller-identity
./scripts/deploy-aws.sh

It prints the Service URL at the end.

Validate deploy / cleanup

./scripts/check-aws-deploy.sh
./scripts/check-aws-cleanup.sh

Azure and GCP (optional)

Use the Terraform stacks in terraform/azure and terraform/gcp. The quickest way to get oriented is to start with:

  • terraform/README.md (overview + commands)
  • terraform/azure (Azure Container Apps)
  • terraform/gcp (GCP Cloud Run)

from github.com/aditya-caltechie/ai_cybersecurity_analyzer

Установка Ai Cybersecurity Analyzer

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/aditya-caltechie/ai_cybersecurity_analyzer

FAQ

Ai Cybersecurity Analyzer MCP бесплатный?

Да, Ai Cybersecurity Analyzer MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Ai Cybersecurity Analyzer?

Нет, Ai Cybersecurity Analyzer работает без API-ключей и переменных окружения.

Ai Cybersecurity Analyzer — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Ai Cybersecurity Analyzer в Claude Desktop, Claude Code или Cursor?

Открой Ai Cybersecurity Analyzer на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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