Manual Windows security patching creates significant risks: delayed remediation, human errors, inconsistent documentation, and poor scalability. Our solution provides a fully automated CI/CD pipeline that intelligently processes vulnerability reports and executes patches using AI-driven decision-making.
Key Benefits:
- AI-enhanced patching decisions using Amazon SageMaker
- Failure intelligence via Amazon Bedrock for log analysis and recommendations
- End-to-end traceability with comprehensive logging
- Event-driven automation requiring zero manual intervention
- Input: Security team uploads CSV vulnerability report to S3
- Trigger: S3 event automatically triggers Lambda → Jenkins pipeline
- Filter: AWS Glue processes CSV, filtering Critical/High severity CVEs
- Classify: Amazon Bedrock classifies unknown severity CVEs using LLM
- Predict: SageMaker predicts patch duration and success probability
- Execute: AWS Systems Manager runs PowerShell patches on Windows servers
- Analyze: Bedrock analyzes patch logs and provides failure recommendations
- Report: Summary emailed to security team with results and insights
- Amazon S3: Secure storage for vulnerability reports
- AWS Lambda: Event-driven pipeline triggering
- Jenkins on EC2: Central CI/CD orchestration
- AWS Glue: Serverless ETL for data processing
- Amazon Bedrock: AI classification and log analysis
- Amazon SageMaker: ML-based patch outcome prediction
- AWS Systems Manager: Secure remote patch execution
- Amazon CloudWatch: Comprehensive logging and monitoring
- Amazon SNS: Automated report delivery
This solution transforms manual, error-prone patching into an intelligent, automated process that:
- Reduces vulnerability exposure time
- Eliminates human errors in patch prioritization
- Provides complete audit trails
- Scales efficiently across large Windows environments
- Uses AI to optimize patching decisions and troubleshoot failures