AIsecTest Bridge Secure AI for Inclusive Digital Experiences

AIsecTest Bridge is a multi-agent security platform designed to enhance digital trust and accessibility.

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🛡️ AIsecTest Bridge — Secure AI for Inclusive Digital Experiences

AIsecTest Bridge is a multi-agent security platform designed to enhance digital trust and accessibility. Built for the AWS Breaking Barriers Hackathon, it integrates AI-based threat detection and inclusive response flows using AWS Bedrock, SageMaker, Lambda, and DynamoDB.

📁 Project Structure

aisectest-bridge/
├── agents/
│   ├── monitor_agent/
│   │   └── monitor.py
│   ├── analysis_agent/
│   │   └── analyze.py
│   ├── response_agent/
│   │   └── respond.py
│   └── coordinator_agent/
│       └── main.py
├── utils/
│   └── logger.py
├── data/
├── deploy/
├── .env.example
├── docker-compose.yml
└── README.md

🚀 Key Features

  • 🔍 Detect anomalous behavior in login flows or user interactions
  • 🧠 Analyze security threats with generative AI (Amazon Bedrock)
  • 🔐 Trigger automatic security actions using AWS Lambda
  • 📄 Log secure events in DynamoDB for traceability
  • 🌐 Designed to be inclusive, scalable, and resilient

🤖 Agent Roles

Agent Function
Monitor Agent Detects suspicious or irregular activity
Analysis Agent Uses AI to determine threat level
Response Agent Executes security actions (block, alert, log)
Coordinator Agent Orchestrates multi-agent logic

🧰 Tech Stack

  • Amazon Bedrock – Generative AI model inference (e.g., Titan, Claude)
  • Amazon SageMaker – Optional for fine-tuned security scoring models
  • AWS Lambda – Event-driven automated response
  • Amazon DynamoDB – Secure event logging and audit trails
  • Docker & Compose – Local simulation of full agent logic

⚙️ Local Testing

  1. Clone the repo:

    git clone https://github.com/YOUR_USERNAME/aisectest-bridge.git
cd aisectest-bridge

  2. Create .env file:

    cp .env.example .env

  3. Add your AWS credentials and config.

  4. Run agents:

    docker-compose up --build

☁️ AWS Integration

See /deploy for:

  • Lambda function deployment for responses
  • API Gateway setup for secure entry points
  • Bedrock model inference sample via AWS SDK

📄 Example Log Output

[2025-05-19 10:42:01] [Monitor Agent] Suspicious login pattern detected from unusual device
[2025-05-19 10:42:02] [Analysis Agent] Risk score: 0.91
[2025-05-19 10:42:03] [Response Agent] Triggering AWS Lambda to lock account

🎯 Use Cases

  • Securing authentication workflows for underserved users
  • Scalable event-driven threat response
  • Deploying explainable security agents in regulated environments

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