sec-design.md

BUSINESS POSTURE

• Business Priorities and Goals:
  • Goal: To provide a widely accessible and standardized toolkit for developing and comparing reinforcement learning algorithms.
  • Priority: Ease of use for researchers and developers.
  • Priority: Broad range of environments to support diverse research areas.
  • Priority: Performance and efficiency of the library and environments.
  • Priority: Community contributions and extensibility.
• Business Risks:
  • Risk: Vulnerabilities in the library could lead to incorrect research results or security issues in systems using the library.
  • Risk: Availability issues with the library or its distribution channels could disrupt research workflows.
  • Risk: Malicious contributions could introduce vulnerabilities or backdoors into the library.
  • Risk: Lack of maintenance and updates could lead to the library becoming outdated and insecure.

SECURITY POSTURE

• Existing Security Controls:
  • security control: GitHub repository access control to manage who can contribute code. Implemented in: GitHub repository settings.
  • security control: Code review process for pull requests. Implemented in: GitHub pull request workflow.
  • security control: Public vulnerability reporting through GitHub. Implemented in: GitHub repository security policy (if defined) and issue tracker.
• Accepted Risks:
  • accepted risk: As an open-source project, vulnerabilities may be publicly disclosed before a patch is available.
  • accepted risk: Reliance on community contributions introduces a risk of unintentionally or intentionally malicious code.
  • accepted risk: Security testing might be less rigorous compared to commercial software due to resource constraints.
• Recommended Security Controls:
  • security control: Implement automated vulnerability scanning for dependencies and code.
  • security control: Introduce static analysis security testing (SAST) in the CI/CD pipeline.
  • security control: Define and enforce a clear security policy for contributions, including guidelines for secure coding practices.
  • security control: Regularly review and update dependencies to address known vulnerabilities.
  • security control: Implement a process for security incident response and vulnerability disclosure.
• Security Requirements:
  • Authentication:
    • Requirement: Authentication is required for contributors to the repository to manage code changes.
    • Requirement: Authentication is required for maintainers to manage the project and releases.
  • Authorization:
    • Requirement: Authorization is needed to control access to repository resources (code, issues, pull requests).
    • Requirement: Authorization is needed to manage releases and package publishing.
  • Input Validation:
    • Requirement: Environment definitions should be validated to prevent unexpected behavior or vulnerabilities.
    • Requirement: User inputs to environments (actions, observations) should be validated to prevent unexpected behavior or vulnerabilities within environments.
  • Cryptography:
    • Requirement: Cryptography might be relevant for specific environments that involve secure communication or data handling, but is not a core requirement for the library itself. Consider if any environments require secure storage or transmission of sensitive data.

DESIGN

• C4 CONTEXT

flowchart LR
    subgraph Internet
    end
    subgraph GitHub["GitHub"]
    direction TB
    GymRepo("OpenAI Gym Repository")
    end
    subgraph PyPI["Python Package Index (PyPI)"]
    PyPIPackage("gym package")
    end
    Researcher("Reinforcement Learning Researcher")
    Developer("Developer")
    Student("Student")

    Researcher -- Uses --> GymRepo
    Developer -- Contributes to --> GymRepo
    Student -- Uses --> GymRepo
    GymRepo -- Publishes --> PyPI
    Researcher -- Installs --> PyPIPackage
    Developer -- Installs --> PyPIPackage
    Student -- Installs --> PyPIPackage
    GymRepo -- Uses --> GitHub
    Developer -- Uses --> GitHub
    Researcher -- Uses --> GitHub
    Student -- Uses --> GitHub

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• C4 CONTEXT Elements:

  • Element:
    • Name: Reinforcement Learning Researcher
    • Type: User
    • Description: Researchers who use OpenAI Gym to develop and test reinforcement learning algorithms.
    • Responsibilities: Utilize OpenAI Gym environments and library to conduct research, develop new algorithms, and compare performance.
    • Security controls: Responsible for using the library securely in their research environments, ensuring data and computational resources are protected.
  • Element:
    • Name: Developer
    • Type: User/Contributor
    • Description: Software developers who contribute to the OpenAI Gym project by adding new environments, features, or bug fixes.
    • Responsibilities: Contribute high-quality, secure code to the project, following project guidelines and security best practices.
    • Security controls: Authentication and authorization via GitHub for code contributions, adherence to secure coding practices, participation in code review.
  • Element:
    • Name: Student
    • Type: User
    • Description: Students learning reinforcement learning who use OpenAI Gym for educational purposes and to understand RL concepts.
    • Responsibilities: Use OpenAI Gym to learn and experiment with reinforcement learning, understand the library's functionalities and limitations.
    • Security controls: Responsible for using the library safely in their learning environments, understanding basic security considerations when using software.
  • Element:
    • Name: OpenAI Gym Repository
    • Type: Software System
    • Description: The GitHub repository containing the source code, environment definitions, documentation, and examples for the OpenAI Gym toolkit.
    • Responsibilities: Host the project codebase, manage contributions, facilitate collaboration, and provide a platform for issue tracking and project management.
    • Security controls: GitHub access controls, code review process, issue tracking for vulnerability reporting, potentially GitHub Advanced Security features (if enabled).
  • Element:
    • Name: Python Package Index (PyPI)
    • Type: External System
    • Description: The public repository for Python packages, used to distribute the 'gym' package.
    • Responsibilities: Host and distribute the 'gym' Python package, ensuring availability and integrity of the package.
    • Security controls: PyPI's infrastructure security, package signing (if implemented by OpenAI Gym), vulnerability scanning of packages on PyPI.

• C4 CONTAINER

flowchart LR
    subgraph GitHub["GitHub"]
    direction TB
    GymRepo("OpenAI Gym Repository")
        subgraph PythonLibrary["Python Library"]
        CoreModules("Core Modules")
        Environments("Environments")
        Examples("Examples")
        Documentation("Documentation")
        end
    end
    PyPI["Python Package Index (PyPI)"]

    GymRepo -- Publishes --> PyPI
    CoreModules -- Part of --> PythonLibrary
    Environments -- Part of --> PythonLibrary
    Examples -- Part of --> PythonLibrary
    Documentation -- Part of --> PythonLibrary

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• C4 CONTAINER Elements:

  • Element:
    • Name: Python Library
    • Type: Container
    • Description: The core Python package of OpenAI Gym, containing all the necessary modules, environment definitions, examples, and documentation.
    • Responsibilities: Provide the core functionalities of OpenAI Gym, including environment interfaces, environment implementations, example usage, and user documentation.
    • Security controls: Code review, static analysis security testing (SAST), dependency vulnerability scanning, secure coding practices.
  • Element:
    • Name: Core Modules
    • Type: Component
    • Description: Python modules containing the core logic of the Gym library, such as environment registration, API definitions, and base classes.
    • Responsibilities: Implement the fundamental functionalities of the Gym library, manage environment lifecycle, and provide the API for interacting with environments.
    • Security controls: Input validation, secure coding practices, unit and integration testing.
  • Element:
    • Name: Environments
    • Type: Component
    • Description: A collection of Python modules defining various reinforcement learning environments (e.g., Atari, classic control, robotics).
    • Responsibilities: Implement specific environment dynamics, observation spaces, action spaces, and reward functions.
    • Security controls: Input validation for environment parameters and user actions, secure implementation of environment logic to prevent exploits, environment sandboxing if necessary.
  • Element:
    • Name: Examples
    • Type: Component
    • Description: Example scripts and notebooks demonstrating how to use OpenAI Gym to train and evaluate reinforcement learning agents.
    • Responsibilities: Provide practical examples for users to learn and get started with OpenAI Gym, showcase different environments and algorithms.
    • Security controls: Examples should follow secure coding practices to avoid demonstrating vulnerable patterns.
  • Element:
    • Name: Documentation
    • Type: Component
    • Description: User guides, API documentation, and tutorials for OpenAI Gym, hosted within the repository and potentially on external documentation platforms.
    • Responsibilities: Provide comprehensive and up-to-date documentation for users to understand and use the library effectively.
    • Security controls: Documentation should not contain misleading or insecure advice, ensure documentation website security if hosted externally.

• DEPLOYMENT

flowchart LR
    subgraph User Environment
    direction TB
    UserMachine("User Machine")
        subgraph Python Environment
        GymLibrary["gym Python Package"]
        RLAlgorithm["RL Algorithm Code"]
        end
    end
    PyPI["Python Package Index (PyPI)"]

    UserMachine -- Installs from --> PyPI
    RLAlgorithm -- Uses --> GymLibrary

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• DEPLOYMENT Elements:

  • Element:
    • Name: User Machine
    • Type: Infrastructure
    • Description: The local computer or server used by a researcher, developer, or student to run reinforcement learning experiments and use OpenAI Gym.
    • Responsibilities: Provide the computational resources to execute Python code, run RL algorithms, and simulate OpenAI Gym environments.
    • Security controls: User's responsibility to secure their own machine, including operating system security, network security, and access controls.
  • Element:
    • Name: Python Environment
    • Type: Runtime Environment
    • Description: A Python runtime environment on the user's machine where OpenAI Gym and RL algorithms are installed and executed.
    • Responsibilities: Provide the necessary Python interpreter and libraries to run OpenAI Gym and RL code.
    • Security controls: Keeping Python environment and packages up-to-date with security patches, using virtual environments to isolate projects.
  • Element:
    • Name: gym Python Package
    • Type: Software Component
    • Description: The installed OpenAI Gym Python library within the user's Python environment.
    • Responsibilities: Provide the OpenAI Gym functionalities to the user's RL algorithms.
    • Security controls: Package integrity verification during installation (e.g., using pip's hash checking), vulnerability scanning of installed packages.
  • Element:
    • Name: RL Algorithm Code
    • Type: Software Component
    • Description: The reinforcement learning algorithm code developed by the user, which utilizes the OpenAI Gym library.
    • Responsibilities: Implement the RL algorithm logic, interact with OpenAI Gym environments, and process observations and actions.
    • Security controls: Developer's responsibility to write secure and robust RL algorithm code, handle data and environment interactions securely.

• BUILD

flowchart LR
    Developer["Developer"] --> CodeChanges["Code Changes"]
    CodeChanges --> GitHubPush["GitHub Push"]
    GitHubPush --> GitHubActions["GitHub Actions CI"]
    GitHubActions --> BuildProcess["Build Process (Tests, Linters, SAST)"]
    BuildProcess --> BuildArtifacts["Build Artifacts (Python Package)"]
    BuildArtifacts --> PyPIPublish["PyPI Publish"]
    PyPIPublish --> PyPI["Python Package Index (PyPI)"]

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• BUILD Elements:
  • Element:
    • Name: Developer
    • Type: Actor
    • Description: Software developers contributing to the OpenAI Gym project.
    • Responsibilities: Write code, fix bugs, add features, and contribute to the project following coding standards and security guidelines.
    • Security controls: Secure development practices, code review participation, authentication and authorization for code contributions.
  • Element:
    • Name: Code Changes
    • Type: Data
    • Description: Modifications to the source code of OpenAI Gym, including new features, bug fixes, and environment definitions.
    • Responsibilities: Represent the changes being introduced to the codebase.
    • Security controls: Version control using Git, code review to ensure code quality and security.
  • Element:
    • Name: GitHub Push
    • Type: Action
    • Description: The action of pushing code changes to the GitHub repository.
    • Responsibilities: Committing and pushing code changes to trigger the CI/CD pipeline.
    • Security controls: Authentication and authorization via GitHub for pushing code.
  • Element:
    • Name: GitHub Actions CI
    • Type: Automation System
    • Description: GitHub's built-in CI/CD service used to automate the build, test, and release process for OpenAI Gym.
    • Responsibilities: Automate the build process, run tests, perform security checks, and prepare release artifacts.
    • Security controls: Secure configuration of CI/CD pipelines, access control to CI/CD workflows, secrets management for credentials, logging and monitoring of CI/CD activities.
  • Element:
    • Name: Build Process (Tests, Linters, SAST)
    • Type: Process
    • Description: The automated build process within GitHub Actions, including running unit tests, code linters, and static analysis security testing (SAST).
    • Responsibilities: Ensure code quality, identify potential bugs and vulnerabilities, and enforce coding standards.
    • Security controls: SAST tools to detect security vulnerabilities, linters to enforce coding standards, comprehensive test suite to verify functionality and security aspects.
  • Element:
    • Name: Build Artifacts (Python Package)
    • Type: Artifact
    • Description: The packaged Python distribution of OpenAI Gym, ready for publishing to PyPI.
    • Responsibilities: Represent the distributable version of the library.
    • Security controls: Package signing to ensure integrity and authenticity, vulnerability scanning of dependencies included in the package.
  • Element:
    • Name: PyPI Publish
    • Type: Action
    • Description: The action of publishing the built Python package to the Python Package Index (PyPI).
    • Responsibilities: Make the OpenAI Gym package available for public download and installation via pip.
    • Security controls: Secure credentials management for PyPI publishing, verification of package integrity before publishing, PyPI's security controls for package hosting.
  • Element:
    • Name: Python Package Index (PyPI)
    • Type: External System
    • Description: The public repository for Python packages, used to distribute the 'gym' package.
    • Responsibilities: Host and distribute the 'gym' Python package, ensuring availability and integrity of the package.
    • Security controls: PyPI's infrastructure security, package signing (if implemented by OpenAI Gym), vulnerability scanning of packages on PyPI.

RISK ASSESSMENT

• Critical Business Processes:
  • Process: Facilitating reinforcement learning research and development.
  • Process: Maintaining the integrity and availability of the OpenAI Gym library.
  • Process: Ensuring the security and reliability of environments provided by the library.
• Data to Protect:
  • Data: OpenAI Gym library source code.
    • Sensitivity: Publicly available, but integrity and availability are critical.
  • Data: Environment definitions and implementations.
    • Sensitivity: Publicly available, but integrity and correctness are crucial for research validity.
  • Data: User contributions (code, issues, pull requests).
    • Sensitivity: Publicly available, but integrity and authenticity are important.
  • Data: Build and release artifacts (Python packages).
    • Sensitivity: Publicly available, but integrity and authenticity are critical for secure distribution.

QUESTIONS & ASSUMPTIONS

• BUSINESS POSTURE:

  • Assumption: The primary goal is to support the research community and make the library widely accessible.
  • Assumption: Performance and ease of use are key priorities.
  • Question: Are there any specific commercial use cases or enterprise adoption plans that would change the business risk profile?
  • Question: What is the acceptable level of risk regarding potential vulnerabilities in the library?

• SECURITY POSTURE:

  • Assumption: Current security controls are primarily focused on GitHub's built-in features and code review.
  • Assumption: The project is open to community contributions and relies on the community for vulnerability reporting.
  • Question: Are there any plans to implement more advanced security measures, such as GitHub Advanced Security or dedicated security audits?
  • Question: What is the process for handling and responding to security vulnerabilities reported by the community?

• DESIGN:

  • Assumption: The project is primarily a Python library distributed via PyPI.
  • Assumption: Deployment is mainly on user machines for research and development purposes.
  • Question: Are there any plans to introduce web-based interfaces or cloud deployments for OpenAI Gym environments in the future?
  • Question: Are there any specific environments that handle sensitive data or require additional security considerations beyond the core library?