Skip to content

Latest commit

 

History

History
237 lines (179 loc) · 18 KB

sec-design.md

File metadata and controls

237 lines (179 loc) · 18 KB

DragonflyDB Project Design Document for Threat Modeling

Version: 1.1 Date: October 26, 2023 Author: Gemini (AI Expert in Software, Cloud, and Cybersecurity Architecture) Project: DragonflyDB - In-Memory Datastore

1. Introduction

This document provides an enhanced design overview of the DragonflyDB project (https://github.com/dragonflydb/dragonfly), specifically tailored for threat modeling. Building upon version 1.0, this document aims for greater clarity, specificity, and a stronger focus on security implications. It details the system architecture, key components, data flow, inferred technology stack, and crucial security considerations to facilitate a comprehensive threat modeling exercise. The information is based on public information and best practices for in-memory datastore design.

2. Project Overview

DragonflyDB is positioned as a high-performance, in-memory datastore with full compatibility with both Redis and Memcached protocols. Its core objectives are to deliver:

  • Protocol Agnostic Compatibility: Seamlessly supports existing Redis and Memcached clients, simplifying adoption and migration.
  • Extreme Performance: Achieves low latency and high throughput through architectural optimizations and efficient algorithms.
  • Horizontal Scalability: Designed for distributed deployments, enabling scaling to handle massive datasets and request loads.
  • Resource Efficiency: Minimizes memory and CPU footprint compared to traditional in-memory solutions, optimizing operational costs.
  • Modern & Secure Design: Built with contemporary languages and security principles in mind for maintainability and inherent security.

3. System Architecture

The following diagram illustrates the DragonflyDB architecture, emphasizing security-relevant components and data flow.

graph LR
    subgraph "External Clients"
        A["Redis Clients"]
        B["Memcached Clients"]
    end
    C["External Load Balancer (Optional)"] --> D["DragonflyDB Instance 1"];
    C --> E["DragonflyDB Instance N"];
    D --> F["Network Listener"];
    E --> F;
    F --> G["Protocol Parser & Command Router"];
    G --> H["Authentication & Authorization Module"];
    H --> I["Command Execution Core"];
    I --> J["Data Storage Layer"];
    J --> K["In-Memory Manager"];
    I --> L["Replication Controller (HA)"];
    L --> D;
    L --> E;
    J --> M["Persistence Manager (Optional)"];
    M --> N["Persistent Storage (Optional)"];

    style A fill:#f9f,stroke:#333,stroke-width:2px
    style B fill:#f9f,stroke:#333,stroke-width:2px
    style D fill:#ccf,stroke:#333,stroke-width:2px
    style E fill:#ccf,stroke:#333,stroke-width:2px
    style N fill:#eee,stroke:#333,stroke-width:2px

    linkStyle 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14 stroke:#333,stroke-width:1px;
Loading

3.1. Component Description (Security Focused)

  • "External Clients": Applications using standard Redis or Memcached client libraries. These are untrusted entities from a security perspective.

    • Security Relevance: Primary attack vector. Clients can send malicious commands, exploit protocol vulnerabilities, or be compromised themselves.

  • "External Load Balancer (Optional)": Distributes traffic across DragonflyDB instances. Can be hardware or software based.

    • Security Relevance: Single point of entry if used. Misconfiguration or vulnerabilities can lead to service disruption or unauthorized access. SSL/TLS termination often happens here, making its security crucial for confidentiality.

  • "DragonflyDB Instance 1...N": Individual DragonflyDB server processes. These are the core processing units.

    • Security Relevance: Contains sensitive data in memory. Vulnerabilities here directly impact confidentiality, integrity, and availability. Instance isolation and secure configuration are vital.

  • "Network Listener": Accepts incoming client connections and manages network sockets.

    • Security Relevance: First point of contact for network attacks. Vulnerabilities in socket handling, protocol implementation, or lack of rate limiting can lead to DoS or connection hijacking. Should enforce secure connection protocols (TLS).

  • "Protocol Parser & Command Router": Interprets Redis/Memcached protocol commands and directs them to the appropriate handler.

    • Security Relevance: Critical for preventing command injection and protocol abuse. Parsing vulnerabilities can allow attackers to bypass security checks or execute unintended commands. Must handle malformed requests safely.

  • "Authentication & Authorization Module": Verifies client identity and permissions before command execution.

    • Security Relevance: Enforces access control. Weak authentication, authorization bypasses, or lack of proper role-based access control (RBAC) can lead to unauthorized data access and manipulation.

  • "Command Execution Core": Executes validated and authorized commands, interacting with the data storage layer.

    • Security Relevance: Core logic for data operations. Vulnerabilities in command handlers can lead to data corruption, privilege escalation, or information disclosure. Secure coding practices are paramount.

  • "Data Storage Layer": Manages the in-memory data structures holding the database.

    • Security Relevance: Stores sensitive data in memory. Vulnerabilities in data structure implementations or memory management can lead to data leaks, corruption, or DoS. In-memory data protection mechanisms are relevant.

  • "In-Memory Manager": Allocates and manages memory for the Data Storage Layer.

    • Security Relevance: Improper memory management can lead to memory leaks, buffer overflows, and other memory safety issues exploitable for DoS or code execution.

  • "Replication Controller (HA)": Manages data replication between DragonflyDB instances for high availability and fault tolerance.

    • Security Relevance: Transmits sensitive data between instances. Unencrypted or unauthenticated replication channels can lead to data interception or tampering. Replication lag can have security implications in consistency models.

  • "Persistence Manager (Optional)": Handles optional data persistence to disk for durability.

    • Security Relevance: Manages data at rest. Lack of encryption for persistent data exposes it to unauthorized access if disk storage is compromised. Secure key management for encryption is crucial.

  • "Persistent Storage (Optional)": Underlying disk storage for persistent data.

    • Security Relevance: Physical security of storage is vital if persistence is enabled. Access control to storage volumes must be enforced.

4. Data Flow Diagram (Security Perspective)

This diagram highlights the data flow for a client SET command, emphasizing security checkpoints.

graph LR
    subgraph "Client Application"
        A["Client Sends SET Request (key, value)"]
    end
    B["Network Listener receives Request"] --> C["Protocol Parser (Redis SET)"];
    C --> D["Command Router"];
    D --> E["Authentication Module"];
    E -- "Authenticated" --> F["Authorization Module (SET command)"];
    F -- "Authorized" --> G["Command Execution Core (SET)"];
    G --> H["Data Storage Layer (Store key-value pair)"];
    H --> I["In-Memory Manager (Allocate/Access Memory)"];
    I --> J["Replication Controller (Propagate SET - if enabled)"];
    J --> B["Replicate to other Instances"];
    H --> K["Persistence Manager (Write to WAL/Snapshot - if enabled)"];
    K --> L["Persistent Storage"];
    H --> M["Response Formatter (Redis Protocol)"];
    M --> N["Network Listener sends Response"];
    N --> O["Client Receives Response"];

    style A fill:#f9f,stroke:#333,stroke-width:2px
    style O fill:#f9f,stroke:#333,stroke-width:2px

    linkStyle 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 stroke:#333,stroke-width:1px;
Loading

Data Flow Description (Security Context):

  1. "Client Sends SET Request (key, value)": Client initiates a SET command, potentially containing sensitive data in 'value'.
  2. "Network Listener receives Request": Network layer receives the request. Security Checkpoint: Is the connection encrypted (TLS)? Is rate limiting in place to prevent DoS?
  3. "Protocol Parser (Redis SET)": Parses the request to identify the command and arguments. Security Checkpoint: Vulnerability to protocol parsing errors or injection attacks? Input validation needed.
  4. "Command Router": Routes the parsed command.
  5. "Authentication Module": Verifies client identity. Security Checkpoint: Strong authentication mechanism? Resistance to brute-force?
  6. "Authorization Module (SET command)": Checks if the authenticated client is authorized to execute the SET command. Security Checkpoint: Granular authorization model? Prevention of privilege escalation?
  7. "Command Execution Core (SET)": Executes the SET command. Security Checkpoint: Secure coding practices in command handler to prevent vulnerabilities?
  8. "Data Storage Layer (Store key-value pair)": Stores the data in memory. Security Checkpoint: In-memory data protection? Vulnerabilities in data structure implementation?
  9. "In-Memory Manager (Allocate/Access Memory)": Manages memory allocation. Security Checkpoint: Memory safety vulnerabilities (buffer overflows, leaks)?
  10. "Replication Controller (Propagate SET - if enabled)": If replication is enabled, propagates the SET operation. Security Checkpoint: Secure replication channel (encryption, authentication)? Data integrity during replication?
  11. "Replicate to other Instances": Data is replicated.
  12. "Persistence Manager (Write to WAL/Snapshot - if enabled)": If persistence is enabled, writes data to persistent storage. Security Checkpoint: Data at rest encryption? Secure storage configuration?
  13. "Persistent Storage": Data is written to disk.
  14. "Response Formatter (Redis Protocol)": Formats the response.
  15. "Network Listener sends Response": Sends the response back to the client.
  16. "Client Receives Response": Client receives confirmation.

5. Technology Stack (Inferred & Security Implications)

Based on project characteristics and performance goals, the likely technology stack and its security implications are:

  • Core Language:

    • C++: Highly probable for performance-critical components (Network Listener, Protocol Parser, Command Execution, Data Storage).
      • Security Implication: Requires rigorous memory management to prevent vulnerabilities like buffer overflows, use-after-free, and other memory corruption issues. Static analysis and fuzzing are crucial.
    • Rust: Possible for newer modules or components requiring enhanced memory safety and concurrency.
      • Security Implication: Rust's memory safety features mitigate many C++ memory-related vulnerabilities. However, logic errors and unsafe code blocks still require careful review.

  • Networking:

    • Asynchronous I/O Library (e.g., io_uring, epoll with non-blocking sockets, or Asio/Boost.Asio): For high-performance network handling.
      • Security Implication: Correct and secure implementation of asynchronous I/O is vital to prevent DoS attacks and ensure proper resource management. Vulnerabilities in the chosen library or its usage can be exploited.
    • TLS/SSL Library (e.g., OpenSSL, BoringSSL, or similar): For encrypted communication.
      • Security Implication: Proper configuration and secure usage of TLS/SSL are essential for data confidentiality and integrity in transit. Vulnerabilities in the TLS library itself or misconfiguration can weaken security.

  • Memory Management:

    • Custom Memory Allocator (e.g., jemalloc, tcmalloc, or in-house optimized allocator): For efficient memory allocation and deallocation in high-load scenarios.
      • Security Implication: Custom allocators must be robust and free from vulnerabilities like double-free, heap corruption, and memory leaks. Thorough testing and security audits are necessary.

  • Data Structures & Algorithms:

    • Optimized Hash Tables, Skip Lists, or similar: For efficient in-memory data storage and retrieval. Likely custom implementations for performance.
      • Security Implication: Custom data structures must be implemented securely to prevent algorithmic complexity attacks (e.g., hash collision DoS) and vulnerabilities in data structure manipulation logic.

  • Build System & Dependencies:

    • CMake: Standard for C++ projects, facilitating cross-platform builds and dependency management.
      • Security Implication: Secure dependency management is crucial. Vulnerable dependencies must be identified and updated promptly. Supply chain security practices are relevant.

  • Operating System:

    • Linux (Primarily): Optimized for Linux environments, potentially with cross-platform support.
      • Security Implication: Reliance on OS security features. OS hardening, kernel security, and regular patching are essential for the overall security posture.

6. Security Considerations for Threat Modeling (Categorized)

This section categorizes security considerations to facilitate structured threat modeling.

A. Network & Access Control:

  • Unencrypted Network Communication: Lack of TLS/SSL for client-server and instance-to-instance communication.
  • Weak Authentication: Simple password-based authentication, susceptibility to brute-force attacks, lack of multi-factor authentication (MFA).
  • Insufficient Authorization: Coarse-grained access control, potential for privilege escalation, lack of RBAC.
  • Default Ports & Services: Using default ports, exposing unnecessary services, increasing attack surface.
  • DoS/DDoS Vulnerability: Susceptibility to network-level and application-level DoS attacks.
  • Lack of Rate Limiting: Absence of rate limiting on connection attempts and command execution.

B. Input Validation & Command Handling:

  • Protocol Parsing Vulnerabilities: Exploitable flaws in Redis/Memcached protocol parsing logic.
  • Command Injection: Vulnerability to command injection through crafted client requests.
  • Input Sanitization Failures: Inadequate input validation and sanitization leading to various injection attacks.
  • Malformed Request Handling: Improper handling of malformed or invalid client requests, potentially causing crashes or unexpected behavior.

C. Memory Management & Data Security:

  • Buffer Overflows & Memory Corruption: Vulnerabilities in C++ code leading to buffer overflows, heap corruption, and other memory safety issues.
  • Memory Leaks: Resource exhaustion due to memory leaks, leading to DoS.
  • In-Memory Data Confidentiality: Lack of in-memory encryption or protection for sensitive data. Potential for memory dumping and data breaches.
  • Algorithmic Complexity Attacks: Vulnerability to attacks exploiting algorithmic complexity of data structures, leading to DoS.

D. Replication & Persistence Security:

  • Unsecured Replication Channel: Unencrypted and unauthenticated replication, exposing data in transit.
  • Replication Data Integrity Issues: Potential for data corruption or inconsistencies during replication.
  • Data at Rest Encryption (Persistence): Lack of encryption for persistent data on disk.
  • Secure Storage Configuration (Persistence): Misconfigured or insecure persistent storage, allowing unauthorized access.
  • Key Management (Persistence Encryption): Weak or insecure key management for data at rest encryption.

E. Operational & Dependency Security:

  • Dependency Vulnerabilities: Vulnerabilities in third-party libraries used by DragonflyDB.
  • Insufficient Logging & Monitoring: Lack of comprehensive security logging and monitoring for anomaly detection and incident response.
  • Insecure Default Configuration: Default configurations that are not secure, requiring manual hardening.
  • Lack of Security Update Process: Absence of a clear process for applying security updates and patches.
  • Insufficient Security Testing: Inadequate security testing (penetration testing, vulnerability scanning) during development and release cycles.

7. Assumptions and Out of Scope (Refined)

Assumptions:

  • This document is based on publicly available information and architectural best practices. Actual DragonflyDB implementation details may vary.
  • Technology stack inferences are based on common practices for high-performance datastores and require verification against the codebase.
  • Security features are assumed to be configurable but may require explicit enabling and secure configuration by operators.
  • Threat modeling will be performed based on this design document as a starting point, requiring further investigation and validation.

Out of Scope (Clarified):

  • Detailed source code review and vulnerability analysis of DragonflyDB.
  • Specific deployment scenarios, infrastructure configurations, and cloud provider integrations.
  • Performance and scalability benchmarking, detailed performance tuning guidance.
  • Operational runbooks, incident response plans, and detailed operational procedures.
  • Specific threat modeling methodologies (e.g., STRIDE, PASTA) and risk scoring. This document prepares for, but does not execute, threat modeling.

8. Conclusion

This enhanced design document provides a more detailed and security-focused foundation for threat modeling DragonflyDB. By outlining the architecture, data flow, technology stack, and categorized security considerations, it enables a structured approach to identifying and mitigating potential threats. This document is a crucial prerequisite for conducting a thorough threat modeling exercise and improving the overall security posture of DragonflyDB deployments. Further steps include using this document to perform threat modeling workshops, identify specific threats, assess risks, and define appropriate security controls.