Skip to content

Latest commit

 

History

History
279 lines (223 loc) · 94.5 KB

sec-design.md

File metadata and controls

279 lines (223 loc) · 94.5 KB

Project Design Document: Hangfire Background Job Processing System

Document Version: 1.1 Date: 2023-10-27 Author: AI Cloud & Security Architect

1. Introduction

This document provides a detailed design overview of Hangfire, an open-source background job processing system for .NET applications. This document is intended to serve as a foundation for threat modeling and security analysis of systems utilizing Hangfire. It outlines the system's architecture, components, data flow, technology stack, deployment model, and initial security considerations.

Hangfire allows developers to perform background processing in .NET applications reliably and efficiently. It supports various job types, persistence options, and monitoring capabilities, making it a versatile solution for offloading time-consuming tasks from the main application thread. This ensures responsive user interfaces and efficient resource utilization by deferring non-interactive tasks to the background.

This document is based on the publicly available information and documentation for Hangfire, primarily from the official GitHub repository: https://github.com/hangfireio/hangfire.

2. Project Overview

Project Name: Hangfire

Project Description: Hangfire is an easy way to perform fire-and-forget, delayed and recurring background processing in .NET applications. Think of it as a .NET equivalent to Celery or Resque. It's backed by persistent storage, meaning that your background tasks are guaranteed to be processed at least once, even if your application or server restarts.

Key Features:

  • Fire-and-Forget Jobs: Execute tasks immediately in the background for immediate offloading.
  • Delayed Jobs: Schedule tasks to be executed at a specific time in the future, useful for scheduled notifications or batch processing.
  • Recurring Jobs: Schedule tasks to be executed repeatedly based on a cron-like expression, ideal for maintenance tasks or periodic data processing.
  • Job Persistence: Jobs are stored in a persistent storage (e.g., database) ensuring reliability and fault tolerance.
  • Job Monitoring Dashboard: Provides a web-based UI to monitor job status, queues, and server health, offering operational visibility.
  • Scalability: Supports scaling out job processing by adding more Hangfire servers to handle increased workload.
  • Extensibility: Offers extension points for custom job filters, storage providers, and more, allowing for tailored integrations.
  • Integration: Seamlessly integrates with ASP.NET and other .NET application frameworks, simplifying adoption in existing projects.

Common Use Cases:

  • Sending Emails: Offloading email sending to the background to improve web application responsiveness.
  • Image/Video Processing: Performing resource-intensive media processing tasks in the background.
  • Data Synchronization: Synchronizing data between systems without blocking user interactions.
  • Batch Processing: Executing large batch jobs without impacting the performance of the main application.
  • Scheduled Tasks: Running regular maintenance tasks, reports generation, or data cleanup.

Target Audience: Developers and operations teams using Hangfire to implement background processing in their .NET applications.

3. System Architecture

The following diagram illustrates the high-level architecture of a system using Hangfire.

graph LR
    subgraph "Client Application"
        A["Web Application / Service"]
    end

    subgraph "Hangfire Infrastructure"
        B["Job Storage (e.g., SQL Server, Redis)"]
        C["Hangfire Server(s)"]
        D["Hangfire Dashboard"]
    end

    A -->|Enqueue Job| B
    C -->|Fetch & Process Job| B
    D -->|Read Job Data| B
    A -->|Access Dashboard (Optional)| D
    C -->|Report Status & Heartbeat| B
Loading

Diagram Components:

  • "Client Application" ("Web Application / Service"): This represents the .NET application that utilizes Hangfire to enqueue background jobs. It could be a web application, API, or any other type of .NET service that needs to offload tasks.
  • "Job Storage" ("e.g., SQL Server, Redis"): This is the persistent storage mechanism used by Hangfire to store job information, queues, server state, and other metadata. Supported storage options include SQL Server, Redis, MongoDB, and others, allowing flexibility based on performance and operational needs.
  • "Hangfire Server(s)": These are background processes responsible for fetching jobs from the storage, processing them, and updating their status. Multiple servers can be deployed for scalability and high availability, distributing the workload.
  • "Hangfire Dashboard": An optional web-based user interface that provides monitoring and management capabilities for Hangfire jobs and servers. It offers insights into system health and job execution.

Data Flow:

  1. Enqueue Job: The Client Application enqueues a background job by calling Hangfire API methods. Job details (job type, arguments, etc.) are serialized and stored in the Job Storage.
  2. Fetch & Process Job: Hangfire Server(s) continuously poll the Job Storage for new jobs. When a server finds an available job, it fetches the job details from the storage.
  3. Job Execution: The Hangfire Server deserializes the job details and executes the corresponding job logic within its process.
  4. Report Status & Heartbeat: During job processing and periodically, Hangfire Servers update the job status and send heartbeat signals to the Job Storage to indicate their availability and health.
  5. Read Job Data: The Hangfire Dashboard queries the Job Storage to retrieve job data, server status, and queue information for display in the UI.
  6. Access Dashboard (Optional): Authorized users can access the Hangfire Dashboard through a web browser to monitor and manage jobs.

4. Component Description

4.1. Client Application (Web Application / Service)

  • Functionality:
    • Job Enqueueing: Uses the Hangfire client API to create and enqueue background jobs. This involves specifying the job method to be executed and any necessary arguments.
    • Job Scheduling: Utilizes Hangfire API to schedule delayed or recurring jobs, providing flexibility in task execution timing.
    • Dashboard Access (Optional): May provide links or access points to the Hangfire Dashboard for authorized users, simplifying navigation.
  • Responsibilities:
    • Defining and initiating background tasks based on application logic.
    • Providing necessary data for job execution, ensuring jobs have the required context.
    • Handling potential errors during job enqueueing, implementing error handling and logging.
    • (Optionally) Providing user interface elements for job management via the Dashboard, enhancing user experience for administrators.
  • Technology: .NET Framework or .NET, Hangfire Client Library.
  • Considerations:
    • Serialization: Ensure job arguments are serializable by the chosen serializer (default is JSON).
    • Error Handling: Implement robust error handling around job enqueueing to prevent job loss.
    • Performance: Minimize the overhead of job enqueueing to avoid impacting the main application's performance.

4.2. Job Storage (e.g., SQL Server, Redis)

  • Functionality:
    • Job Persistence: Stores all information related to background jobs, including job state, arguments, results, and execution history, ensuring data durability.
    • Queue Management: Maintains job queues, allowing Hangfire Servers to efficiently fetch and process jobs in a FIFO or priority-based manner.
    • Server State Management: Stores information about active Hangfire Servers, their health, and capabilities, enabling monitoring and server management.
    • Distributed Locking: Provides mechanisms for distributed locking to ensure job processing consistency and prevent race conditions between multiple Hangfire Servers, crucial for data integrity.
  • Responsibilities:
    • Reliably storing and retrieving job data, guaranteeing data persistence.
    • Ensuring data consistency and integrity, maintaining the accuracy of job information.
    • Providing efficient data access for Hangfire Servers and the Dashboard, optimizing performance.
    • Handling concurrency and distributed access from multiple Hangfire Servers, managing concurrent operations.
  • Technology: Relational Databases (SQL Server, PostgreSQL, MySQL), NoSQL Databases (Redis, MongoDB), or other supported storage providers. The choice of storage impacts performance, scalability, and operational complexity.
  • Considerations:
    • Storage Type Selection: Choose the storage type based on performance requirements, scalability needs, and operational expertise. SQL databases offer strong consistency, while NoSQL databases like Redis provide high performance for queue operations.
    • Scalability and Performance: Ensure the chosen storage can handle the expected job volume and concurrency.
    • Backup and Recovery: Implement proper backup and recovery strategies for the Job Storage to prevent data loss.
    • Security: Secure access to the Job Storage and consider data encryption at rest and in transit.

4.3. Hangfire Server(s)

  • Functionality:
    • Job Fetching: Continuously polls the Job Storage for new jobs in the queues, ensuring timely job processing.
    • Job Processing: Executes the actual background job logic, performing the defined tasks. This involves deserializing job arguments, invoking the specified job method, and handling exceptions.
    • Job State Management: Updates the job status in the Job Storage (e.g., "Enqueued", "Processing", "Succeeded", "Failed"), providing job lifecycle tracking.
    • Retry Mechanism: Implements job retry policies for transient failures, enhancing job reliability.
    • Heartbeat & Monitoring: Sends periodic heartbeat signals to the Job Storage to indicate server availability and health, enabling server monitoring.
    • Worker Management: Manages worker threads or processes to execute jobs concurrently, maximizing throughput.
  • Responsibilities:
    • Reliably processing background jobs, ensuring tasks are executed successfully.
    • Managing job execution lifecycle, tracking job progress and status.
    • Handling job failures and retries according to configured policies, improving fault tolerance.
    • Maintaining server health and reporting status, providing operational insights.
    • Scaling job processing capacity by adding more server instances, adapting to workload changes.
  • Technology: .NET Framework or .NET, Hangfire Server Library, potentially hosted in various environments (e.g., Windows Service, Console Application, Web Application, Docker container).
  • Considerations:
    • Scaling Strategy: Determine the appropriate scaling strategy (vertical vs. horizontal) based on workload patterns.
    • Resource Management: Configure worker thread/process count and resource limits to optimize performance and prevent resource exhaustion.
    • Monitoring and Logging: Implement comprehensive monitoring and logging to track server health, job processing performance, and errors.
    • Deployment Environment: Choose the deployment environment based on scalability, availability, and operational requirements.

4.4. Hangfire Dashboard

  • Functionality:
    • Job Monitoring: Displays real-time information about job queues, job statuses, and job execution history, providing operational visibility.
    • Server Monitoring: Provides insights into the status and health of Hangfire Servers, enabling server health checks.
    • Job Management: Allows administrators to retry failed jobs, delete jobs, and perform other management actions, offering administrative control.
    • Configuration Overview: Displays Hangfire configuration and statistics, providing system information.
    • Security & Authentication: (Potentially) Implements authentication and authorization to control access to the dashboard, securing access to sensitive information and actions.
  • Responsibilities:
    • Providing a user-friendly interface for monitoring and managing Hangfire, simplifying operations.
    • Presenting accurate and up-to-date information about the system, ensuring reliable data.
    • Enforcing security policies for dashboard access, protecting sensitive functionalities.
  • Technology: ASP.NET (or ASP.NET Core), HTML, CSS, JavaScript, Hangfire Dashboard Library. Typically hosted within the Client Application or as a separate web application.
  • Considerations:
    • Security: Implement strong authentication and authorization to protect the dashboard from unauthorized access.
    • Performance: Optimize dashboard performance to handle a large number of jobs and servers.
    • Accessibility: Ensure the dashboard is accessible to authorized personnel and meets accessibility standards.
    • Deployment Location: Decide whether to host the dashboard within the Client Application or as a separate application based on security and operational needs.

5. Data Flow Details

Job Enqueueing Process:

  1. The Client Application calls a Hangfire API method (e.g., BackgroundJob.Enqueue, BackgroundJob.Schedule, RecurringJob.AddOrUpdate).
  2. Hangfire Client Library serializes the job method information (method name, assembly, arguments) into a format suitable for storage (often JSON).
  3. The serialized job data, along with job state information (e.g., "Enqueued"), is written to the Job Storage within the appropriate job queue.

Job Processing Process:

  1. A Hangfire Server periodically queries the Job Storage for jobs in the "Enqueued" state.
  2. Upon finding an available job, the server attempts to acquire a distributed lock on the job to prevent concurrent processing by multiple servers.
  3. The server fetches the job data from the Job Storage.
  4. The server deserializes the job data to reconstruct the job method and arguments.
  5. The server executes the job method within its process.
  6. During execution, the server may update the job state in the Job Storage (e.g., "Processing", "Succeeded", "Failed").
  7. After job completion (success or failure), the server releases the distributed lock on the job.
  8. If the job fails and retry policies are configured, the job state may be updated to "Retrying", and it will be re-enqueued for later processing.

Dashboard Data Retrieval:

  1. When a user accesses the Hangfire Dashboard, the dashboard application makes requests to the Job Storage.
  2. The dashboard queries the Job Storage to retrieve various data, including:
    • Job queue statistics (enqueued, processing, succeeded, failed counts).
    • List of jobs with their statuses and details.
    • Hangfire Server status and metrics.
    • Configuration information.
  3. The Job Storage returns the requested data to the dashboard.
  4. The dashboard application processes and displays the data in the user interface.

6. Technology Stack

  • Programming Language: C# (.NET Framework or .NET)
  • Job Storage Options:
    • Relational Databases: SQL Server, PostgreSQL, MySQL, Oracle, etc. (using ADO.NET or ORM frameworks like Entity Framework) - Suitable for strong consistency and transactional needs.
    • NoSQL Databases: Redis, MongoDB, Azure Cosmos DB, etc. (using respective .NET drivers) - Suitable for high-performance queue operations and scalability.
  • Web Framework (for Dashboard): ASP.NET MVC or ASP.NET Core MVC - Provides a robust framework for building the web-based dashboard.
  • Serialization: JSON (typically using libraries like System.Text.Json or Newtonsoft.Json) - Standard format for data serialization and interoperability.
  • Distributed Locking: Storage-specific mechanisms (e.g., database transactions, Redis locks) - Ensures data consistency in a distributed environment.
  • Background Processing Libraries: Hangfire Server and Client libraries - Core libraries providing Hangfire functionality.
  • Operating System: Windows, Linux, macOS (depending on deployment environment) - Offers flexibility in deployment platforms.
  • Hosting Environment: IIS, Kestrel, Azure App Service, AWS EC2, Docker, Kubernetes, etc. - Wide range of hosting options to suit different needs and scales.

7. Deployment Model

Hangfire can be deployed in various configurations depending on the application requirements and infrastructure.

Deployment Model Options:

| Model | Description | Pros ## 8. Security Considerations (Initial)

This section outlines initial security considerations for Hangfire, categorized by component. A more detailed threat model will be developed based on this design document.

8.1. Job Storage Security:

  • Threats:
    • Unauthorized Access: Attackers gaining unauthorized access to job data, potentially reading sensitive information or manipulating job states.
    • Data Breach: Exposure of sensitive job data due to storage vulnerabilities or misconfigurations.
    • Data Integrity Violation: Malicious modification or deletion of job data, leading to data corruption or denial of service.
    • SQL Injection (if using SQL-based storage): Exploiting vulnerabilities in SQL queries to gain unauthorized access or manipulate data.
  • Mitigations:
    • Strong Authentication and Authorization: Implement robust authentication and authorization mechanisms provided by the storage technology (e.g., database user accounts, access control lists).
    • Principle of Least Privilege: Grant only necessary permissions to Hangfire Servers and Dashboard accounts accessing the storage.
    • Network Segmentation: Isolate the Job Storage within a secure network segment, limiting network access.
    • Data Encryption at Rest: Encrypt sensitive job data stored in the Job Storage using encryption features provided by the storage technology (e.g., Transparent Data Encryption in SQL Server).
    • Data Encryption in Transit: Enforce encrypted communication (TLS/SSL) between Hangfire components and the Job Storage.
    • Regular Security Audits and Vulnerability Scanning: Regularly audit storage configurations and scan for vulnerabilities.
    • Input Validation and Parameterized Queries (for SQL): Use parameterized queries or ORM frameworks to prevent SQL injection vulnerabilities.

8.2. Hangfire Dashboard Security:

  • Threats:
    • Unauthorized Access to Dashboard: Attackers gaining access to the Dashboard without proper authentication, potentially monitoring jobs, viewing sensitive data, or performing administrative actions.
    • Cross-Site Scripting (XSS): Injecting malicious scripts into the Dashboard UI to steal user credentials or perform actions on behalf of authenticated users.
    • Cross-Site Request Forgery (CSRF): Forcing authenticated users to perform unintended actions on the Dashboard.
    • Clickjacking: Tricking users into clicking malicious links or buttons within the Dashboard interface.
    • Information Disclosure: Exposure of sensitive job data or system information through the Dashboard.
  • Mitigations:
    • Robust Authentication: Implement strong authentication mechanisms for Dashboard access (e.g., Forms Authentication, Windows Authentication, OAuth 2.0).
    • Authorization and Role-Based Access Control (RBAC): Define roles and permissions to restrict access to sensitive Dashboard features based on user roles.
    • Input Sanitization and Output Encoding: Sanitize user inputs and encode outputs to prevent XSS vulnerabilities.
    • CSRF Protection: Implement CSRF protection mechanisms (e.g., anti-forgery tokens).
    • Clickjacking Protection: Implement frame-busting techniques or HTTP headers (e.g., X-Frame-Options) to prevent clickjacking attacks.
    • HTTPS Enforcement: Enforce HTTPS for all Dashboard communication to protect data in transit.
    • Regular Security Updates and Patching: Keep the Dashboard application and its dependencies up-to-date with security patches.
    • Security Headers: Implement security-related HTTP headers (e.g., Content-Security-Policy, Strict-Transport-Security) to enhance browser-side security.

8.3. Job Execution Security:

  • Threats:
    • Code Injection through Job Arguments: If job arguments are not properly validated or sanitized, attackers might inject malicious code that gets executed by Hangfire Servers.
    • Deserialization Vulnerabilities: Exploiting vulnerabilities in the deserialization process of job arguments to execute arbitrary code.
    • Dependency Vulnerabilities: Vulnerabilities in libraries or dependencies used by job implementations, which could be exploited by attackers.
    • Resource Exhaustion: Malicious jobs designed to consume excessive resources (CPU, memory, disk space), leading to denial of service.
  • Mitigations:
    • Input Validation and Sanitization: Thoroughly validate and sanitize job arguments before processing them within job implementations.
    • Secure Deserialization Practices: Avoid deserializing untrusted data directly. If deserialization is necessary, use secure deserialization libraries and techniques.
    • Dependency Management and Vulnerability Scanning: Regularly scan job dependencies for vulnerabilities and keep them updated.
    • Resource Limits and Quotas: Implement resource limits (CPU, memory, execution time) for job processing to prevent resource exhaustion.
    • Code Reviews and Security Testing: Conduct regular code reviews and security testing of job implementations to identify and address potential vulnerabilities.
    • Principle of Least Privilege for Job Execution Context: Run Hangfire Servers with minimal necessary privileges to limit the impact of potential security breaches.

8.4. Communication Security:

  • Threats:
    • Man-in-the-Middle (MITM) Attacks: Interception of communication between Hangfire components (Client Application, Server, Dashboard, Job Storage) to eavesdrop on sensitive data or manipulate communication.
  • Mitigations:
    • TLS/SSL Encryption: Enforce TLS/SSL encryption for all communication channels between Hangfire components, especially over networks.
    • Mutual Authentication (Optional): For highly sensitive environments, consider implementing mutual authentication to verify the identity of both communicating parties.

8.5. Configuration Security:

  • Threats:
    • Exposure of Sensitive Configuration Data: Accidental or intentional exposure of sensitive configuration data (e.g., database credentials, API keys) in configuration files or environment variables.
  • Mitigations:
    • Secure Configuration Storage: Store sensitive configuration data securely, using encrypted configuration files, secrets management systems (e.g., Azure Key Vault, HashiCorp Vault), or environment variables with restricted access.
    • Avoid Hardcoding Secrets: Never hardcode sensitive information directly in code or configuration files.
    • Regular Configuration Reviews: Regularly review Hangfire configurations to ensure they are secure and follow security best practices.

This improved design document provides a more detailed and security-focused overview of Hangfire, enhancing its value for threat modeling and security analysis. The expanded security considerations section offers a starting point for identifying and mitigating potential security risks associated with Hangfire deployments. Further threat modeling exercises should build upon this foundation to create a comprehensive security strategy.