The main objective of this project is to conduct a comprehensive vulnerability assessment of atlantiq AI's cloud-based infrastructure and AI systems. Learners will be tasked with identifying potential security weaknesses in our AWS-hosted services, including EC2 instances, S3 buckets, RDS databases, and Lambda functions. They will also assess the security of our AI model deployment pipeline and data processing systems.

The expected outcomes include:

1. A detailed vulnerability assessment report highlighting critical, high, medium, and low-risk vulnerabilities in our cloud infrastructure and AI systems.

2. Specific recommendations for enhancing our security posture, with a focus on protecting sensitive AI models and user data.

3. A security architecture overview that aligns with our unique needs as an AI-powered SaaS startup, including recommendations for secure AI model deployment and data handling practices.

4. Proposed implementation strategies for recommended security measures, considering our resource constraints as a startup.

1. Infrastructure Assessment:

  - Conduct network scans of our AWS environment using tools like Nmap and AWS Inspector

  - Perform vulnerability scans on EC2 instances, S3 buckets, and RDS databases

  - Assess the security configuration of our Kubernetes clusters (EKS)

  - Evaluate IAM policies and roles for least privilege principles

2. AI System Security Analysis:

  - Review the security of our AI model deployment pipeline

  - Assess data processing systems for potential vulnerabilities

  - Evaluate the implementation of our GraphRAG system for security risks

3. Code Review:

  - Conduct a security-focused code review of our Python backend (FastAPI)

  - Analyze our frontend code (Next.js, React) for potential security issues

  - Review our CI/CD pipelines (GitHub Actions) for security best practices

4. Cloud Security Configuration:

  - Assess our use of AWS security features (CloudTrail, CloudWatch)

  - Evaluate our encryption practices for data at rest and in transit

  - Review our backup and disaster recovery procedures

5. Access Control and Authentication:

  - Assess our implementation of Role-Based Access Control (RBAC)

  - Evaluate our Multi-Factor Authentication (MFA) setup

  - Review our session management and token-based authentication system

6. Compliance and Policy Review:

  - Assess our current security policies and procedures

  - Evaluate our compliance with relevant data protection regulations

  - Review our incident response and business continuity plans

7. Reporting and Recommendations:

  - Compile findings into a comprehensive vulnerability assessment report

  - Develop a prioritized list of security recommendations

  - Create a proposed implementation strategy for security enhancements

  - Prepare an executive summary highlighting key findings and recommendations

8. Presentation:

  - Develop a concise presentation of findings for the atlantiq AI leadership team

  - Create visual aids (charts, diagrams) to illustrate key security concepts and recommendations

We are committed to providing robust support and mentorship to ensure learners can successfully complete the project:

1. Dedicated Point of Contact:

  - Parisa, our Technical Lead, will serve as the primary mentor, offering 5+ hours of direct mentorship per week.

  - Esther, our IT Project Manager, will provide additional support and project management guidance.

2. Regular Check-ins:

  - Weekly team meetings to discuss progress, challenges, and next steps.

  - Bi-weekly one-on-one sessions with each learner to provide personalized guidance.

3. Access to Tools and Technology:

  - Provision of secure, sandboxed access to our AWS environment for testing purposes.

  - Access to our development tools, including GitHub repositories (read-only), CI/CD pipelines, and project management software (Asana).

  - Licenses for necessary security tools (e.g., vulnerability scanners, penetration testing software).

4. Documentation and Resources:

  - Comprehensive documentation of our current infrastructure and security practices.

  - Access to our internal knowledge base and relevant whitepapers on AI security.

5. Data Access:

  - Provision of anonymized, non-sensitive datasets for testing and analysis purposes.

  - Access to system logs and performance metrics (with sensitive information redacted).

6. Technical Workshops:

  - Two specialized workshops on AI security and cloud infrastructure security, led by our technical team.

7. Collaboration Tools:

  - Access to our Slack workspace for real-time communication with the atlantiq AI team.

  - Use of our Zoom account for video conferences and screen sharing sessions.

8. Feedback and Review:

  - Regular code and documentation reviews to provide constructive feedback.

  - Detailed evaluation of interim deliverables to guide project direction.

9. Professional Development:

  - Opportunity to present findings to our executive team, providing valuable presentation experience.

  - Letters of recommendation for outstanding performers.