Skip to content

Latest commit

 

History

History
35 lines (30 loc) · 3.98 KB

threat-modeling.md

File metadata and controls

35 lines (30 loc) · 3.98 KB

Threat Model Analysis for faker-ruby/faker

Threat: Threat 1: Production Data Leakage

  • Description: An attacker observes nonsensical or unrealistic data in the production application. This occurs because the application is inadvertently using faker-generated data instead of real data in the production environment. The attacker might try to exploit this by submitting forms with fake data, attempting to trigger errors, or simply noting the unprofessional appearance. This is a direct misuse of faker by deploying code that uses it in a production context.
    • Impact:
      • Loss of user trust and damage to the application's reputation.
      • Potential legal issues if fake data is used where real data is required (e.g., financial transactions).
      • Operational problems (e.g., failed deliveries due to fake addresses).
      • Exposure of the fact that the application is using fake data, potentially revealing development practices.
    • Affected Faker Component: All faker modules and methods are potentially affected. The core issue is the misuse of the gem in a production environment.
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Environment Separation: Strictly separate development/testing and production environments. Use environment variables (e.g., RAILS_ENV, NODE_ENV) to control faker usage.
      • Conditional Logic: Wrap faker calls in conditional logic that checks the environment (e.g., if Rails.env.development? || Rails.env.test?).
      • Code Reviews: Mandatory code reviews to check for faker usage outside of allowed contexts.
      • Automated Testing: Implement integration and end-to-end tests that specifically verify that production data is not generated by faker.
      • Feature Flags: Use feature flags to enable/disable demo modes that might use faker data, ensuring they are disabled in production.
      • Configuration Files: Use a configuration file to enable/disable faker based on the environment.

Threat: Threat 2: Predictable Data Exploitation

  • Description: An attacker exploits the predictability of faker's default seed. If the application uses faker to generate seemingly random data (e.g., temporary IDs, one-time codes) without setting a custom, random seed, the attacker can predict the sequence of generated values. The attacker might repeatedly access the application, observing the generated data and deducing the pattern. This directly involves faker's random number generation mechanism.
    • Impact:
      • Bypass of security controls that rely on the "randomness" of faker-generated data (e.g., predicting a temporary ID to access another user's data).
      • Information disclosure if the predictable data is used in a way that reveals sensitive information.
      • Increased risk of replay attacks if the predictable data is used as a nonce.
    • Affected Faker Component: Faker::Config.random (or the lack of its proper use). Any faker method that relies on the default random number generator is affected.
    • Risk Severity: High
    • Mitigation Strategies:
      • Custom Seed: Always set a unique, cryptographically secure random seed for faker in each environment using Faker::Config.random = Random.new(SecureRandom.random_number(2**32)).
      • SecureRandom: Use Ruby's SecureRandom module to generate the seed, ensuring it's truly random.
      • Environment-Specific Seeds: Use different seeds for development, testing, staging, and production. Store seeds securely (e.g., in environment variables).
      • Avoid Security-Critical Use: Do not use faker to generate data that requires true randomness for security purposes (e.g., passwords, tokens, encryption keys). Use dedicated cryptographic libraries for these.