• Introduction
• Threat Model
  • Assumptions
  • Asset Identification
  • Potential Threats
  • Risk Analysis
  • Attack Vectors
  • Potential Impact
• Security Policies
  • Authentication and Authorization
  • Data Protection
  • Network Security
  • Dependency Management
  • Logging and Monitoring
• Proper Use and Best Practices
  • Configuration Recommendations
  • Integrated Security Tools
  • Staying Informed
  • Development Practices
  • Environment Management
• Reporting Security Issues
• Disclaimer

OllaLab-Lean is a lean stack designed to help both novice and experienced developers rapidly set up and begin working on LLM-based projects. This is achievable via simplified environment configuration and a cohesive set of tools for Research and Development (R&D).

This document outlines the threat model for OllaLab-Lean when used in a local environment with strong network border security. It also provides detailed security policies, proper usage guidelines, best practices, and important disclaimers to ensure the secure deployment and operation of the project.

• Local Deployment: The system is intended for local use only, within a secured network environment.
• Strong Network Border Security: The local network has robust security measures to prevent unauthorized external access.
• Trusted Users: Users with access to the system are trusted and adhere to security policies.

• Sensitive Data: Includes notebooks, databases, logs, and any data processed or stored by the services.
• Service Components: Docker containers running services such as Neo4j, Ollama, Jupyter Lab, Streamlit, Prometheus, Grafana, Elasticsearch, Logstash, and Kibana.
• Credentials and Secrets: Passwords, tokens, API keys (e.g., NEO4J_PASSWORD, JUPYTER_TOKEN, GRAFANA_PASSWORD).
• Configuration Files: Docker Compose files, environment variables, service-specific configurations.
• Host System Resources: CPU, memory, storage, and network interfaces of the machine hosting the Docker containers.

• Unauthorized Access: Gaining access to services through exposed ports, weak credentials, or misconfigurations.
• Data Leakage: Exposure of sensitive data via unsecured volumes, logs, backups, or through container vulnerabilities.
• Privilege Escalation: Exploiting service or container vulnerabilities to gain higher-level access.
• Denial of Service (DoS): Overloading services to disrupt availability, potentially halting R&D activities.
• Malware and Ransomware: Introduction of malicious code through dependencies, compromised images, or phishing attacks.
• Network Eavesdropping and Man-in-the-Middle (MitM) Attacks: Intercepting or altering communications between services.

• Exposed Services and Ports: Services mapped to host ports may be accessible if firewall rules are not properly configured.
• Default Credentials: Failure to change default passwords or tokens increases the risk of unauthorized access.
• Vulnerable Dependencies: Outdated or unpatched dependencies can be exploited to compromise the system.
• Insecure Configurations: Misconfigurations in Docker, services, or networks can create vulnerabilities.
• Inter-Container Trust: Overly permissive network configurations between containers may allow lateral movement if one is compromised.

• Local Network Exploits: Attackers on the same network exploiting open ports or vulnerabilities.
• Insider Threats: Authorized users intentionally or unintentionally causing security breaches.
• Supply Chain Attacks: Compromised third-party libraries, Docker images, or updates introducing vulnerabilities.
• Phishing and Social Engineering: Tricks to obtain credentials or persuade users to execute malicious code.
• Brute Force Attacks: Automated attempts to guess passwords or tokens.

• Confidentiality Breach: Unauthorized disclosure of sensitive data and intellectual property.
• Integrity Compromise: Unauthorized alteration of data, configurations, or code.
• Availability Disruption: Services become unavailable, impacting productivity and research timelines.
• Financial Loss: Costs associated with data recovery, system restoration, and potential legal liabilities.
• Reputational Damage: Loss of trust from clients, partners, or the community due to a security breach.

• Strong Passwords: All services must use strong, unique passwords and tokens.
• Role-Based Access Control (RBAC): Implement RBAC where possible to limit user permissions.
• Credential Management: Store credentials securely, avoid hardcoding them in code or configuration files.

• Encryption at Rest: Use encrypted volumes for storing sensitive data if possible.
• Encryption in Transit: Enable SSL/TLS for services that support it to protect data in transit.
• Data Minimization: Only collect and store data that is necessary for operations.

• Firewall Configuration: Use firewalls to restrict access to exposed service ports.
• Network Segmentation: Isolate services using Docker networks to prevent unauthorized inter-service communication.
• Port Binding: Bind services to localhost where external access is not required.

• Regular Updates: Keep all dependencies and Docker images updated to their latest stable versions.
• Vulnerability Scanning: Regularly scan dependencies and images for known vulnerabilities.
• Trusted Sources: Only use official or verified repositories for dependencies and Docker images.

• Comprehensive Logging: Enable detailed logging for all services to track activities and identify anomalies.
• Secure Log Storage: Protect logs from unauthorized access and tampering.
• Monitoring Tools: Utilize Prometheus and Grafana for real-time monitoring of system performance and security metrics.

• Environment Variables: Use .env files or Docker secrets to manage environment variables securely.
• Service Configuration: Review and harden service configurations (e.g., Neo4j, Jupyter Lab) according to best practices.
• Access Tokens: Regenerate tokens periodically and revoke them if they are suspected to be compromised.

• CodeQL: Utilize for automated code scanning to detect vulnerabilities in the codebase.
• OSSAR (Open Source Static Analysis Runner): Implement static analysis to identify security issues in open-source components.
• SNYK: Monitor for vulnerabilities in dependencies and receive remediation advice.

• GitHub Security Tab: Regularly check the repository's Security tab for alerts, advisories, and dependency updates.
• Security Mailing Lists: Subscribe to security advisories related to the technologies used in the project.
• Community Engagement: Participate in relevant forums and discussions to stay updated on security trends and vulnerabilities.

• Secure Coding Standards: Follow best practices for secure coding to prevent introducing vulnerabilities.
• Peer Reviews: Conduct code reviews focusing on security implications before merging changes.
• Continuous Integration/Continuous Deployment (CI/CD): Integrate security testing into the CI/CD pipeline.
• Documentation: Maintain up-to-date documentation on configurations and security measures.

• Access Control: Limit access to the host system and Docker daemon to authorized personnel only.
• Backup Strategy: Implement regular backups of critical data and test recovery procedures.
• Resource Limitation: Use Docker resource constraints to prevent denial-of-service conditions.
• Audit and Compliance: Regularly audit the system for compliance with security policies and standards.

If you discover any security vulnerabilities or have concerns regarding the security of this project, please report them responsibly by contacting the author directly. Please do not disclose security-related issues publicly until they have been properly addressed.

Disclaimer: The author of OllaLab-Lean assumes no responsibility for any negative impacts resulting from the use of this project. Users are solely responsible for ensuring proper usage and maintaining the security posture of their systems. The project is provided "as is," without warranty of any kind, express or implied. Users should perform their own security assessments and take all necessary precautions when deploying and using the software.

Note: By using this project, you agree to the terms outlined in this disclaimer and acknowledge that you are responsible for securing your environment and data.

By following the security policies, proper usage guidelines, and best practices outlined in this document, users can significantly mitigate security risks and ensure a secure and productive environment for developing LLM-based projects with OllaLab-Lean.