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Home » How We Audited a High-Traffic Ruby Enterprise Stack on Google Cloud and Mitigated Insecure Deserialization in legacy session handling

How We Audited a High-Traffic Ruby Enterprise Stack on Google Cloud and Mitigated Insecure Deserialization in legacy session handling

Deep Dive: Auditing a High-Traffic Ruby Enterprise Stack on Google Cloud

This post details a recent security audit of a high-traffic Ruby on Rails enterprise application hosted on Google Cloud Platform (GCP). The primary objective was to identify and mitigate critical vulnerabilities, with a specific focus on insecure deserialization within legacy session handling mechanisms. The stack involved multiple microservices, a complex data pipeline, and a significant user base, making a thorough, systematic approach paramount.

Phase 1: Reconnaissance and Attack Surface Mapping

The initial phase involved understanding the application’s architecture, deployment topology, and external-facing components. This included:

  • Infrastructure Inventory: Cataloging all GCP resources (GCE instances, GKE clusters, Cloud SQL, Cloud Storage, Load Balancers, VPCs, Firewalls).
  • Application Mapping: Identifying all Ruby on Rails applications, their dependencies, API endpoints, and inter-service communication patterns.
  • Authentication & Authorization Flows: Documenting how users authenticate and how access is controlled across different services.
  • Data Flow Analysis: Tracing critical data paths, especially those involving user-provided input or sensitive information.

Tools used:

  • gcloud CLI for GCP resource enumeration.
  • nmap and masscan for network port scanning.
  • Burp Suite Professional for web application traffic interception and analysis.
  • Custom scripts for API endpoint discovery and dependency analysis.

Phase 2: Vulnerability Identification – The Session Handling Weakness

During the dynamic analysis phase, we observed that session data was being stored in a serialized format within cookies. The application utilized a legacy session store that relied on Ruby’s built-in Marshal module for serialization and deserialization. This is a well-known vulnerability vector for insecure deserialization.

The Core Problem: Ruby’s Marshal.load (and its equivalent in older versions, YAML.load when used with unsafe options) can execute arbitrary Ruby code when deserializing specially crafted data. If an attacker can control the serialized data that is later deserialized by the application, they can achieve Remote Code Execution (RCE).

Exploitation Scenario: Insecure Deserialization via Session Cookies

The typical flow for this vulnerability in a Rails application looks like this:

  • The application serializes session data (e.g., user ID, preferences) using Marshal.dump and stores it in a cookie.
  • The user’s browser sends this cookie back with subsequent requests.
  • The Rails application deserializes the cookie data using Marshal.load to reconstruct the session.
  • If an attacker can tamper with the session cookie data (e.g., by intercepting it with a proxy and modifying it), they can inject malicious serialized Ruby objects.

A common payload involves creating a Ruby object that, when loaded, triggers a method call that leads to code execution. For instance, an object that overrides _load or has a specific structure that Marshal interprets as executable code.

Phase 3: Proof of Concept and Mitigation Strategy

Crafting a Malicious Session Payload

We used a Ruby script to generate a malicious serialized payload. The goal was to execute a simple command, like `id` or `whoami`, on the server. The exact payload structure can vary based on the Ruby version and specific libraries in use, but a common pattern involves leveraging Ruby’s object serialization to instantiate and call methods on malicious objects.

Here’s a simplified conceptual example of how such a payload might be constructed (this is illustrative and not directly runnable without a vulnerable environment):

# This is a conceptual example. Actual payloads are more complex and
# depend on the target Ruby version and available classes.

# A simplified malicious object that might execute a command upon deserialization.
# In a real scenario, this would leverage specific Ruby features or library
# vulnerabilities to achieve code execution.
class MaliciousCommandExecutor
  def initialize(command)
    @command = command
  end

  def _load(*)
    # This method is called by Marshal.load in some contexts.
    # In a real exploit, this would be more sophisticated.
    system(@command)
  end
end

# Command to execute
command_to_run = "echo 'Vulnerable!'"

# Create an instance of the malicious object
malicious_object = MaliciousCommandExecutor.new(command_to_run)

# Marshal the object into a string
# In a real exploit, this string would be Base64 encoded and placed in the cookie.
serialized_payload = Marshal.dump(malicious_object)

# For demonstration, print the serialized payload (would be Base64 encoded in a cookie)
puts Base64.strict_encode64(serialized_payload)

This serialized string, when Base64 encoded and placed into the session cookie, would be deserialized by the vulnerable application, leading to the execution of the `echo ‘Vulnerable!’` command on the server.

Mitigation: Transitioning to a Secure Session Store

The most effective mitigation for insecure deserialization is to avoid deserializing untrusted data or to use a secure serialization format. For Rails applications, this means moving away from cookie-based sessions that rely on Marshal.

The recommended approach is to use a dedicated session store that does not rely on client-side serialization of complex objects. Common secure alternatives include:

  • Redis Session Store: Stores session data server-side in Redis, typically using a session ID stored in a secure, HTTP-only cookie.
  • Database Session Store: Stores session data server-side in a database.
  • Encrypted Cookie Store: While still cookie-based, this approach encrypts the session data, making it tamper-proof. However, it’s crucial to use strong, up-to-date encryption algorithms and proper key management.

For this specific enterprise stack, we opted for the Redis Session Store due to its performance characteristics and scalability, which aligned well with the high-traffic requirements.

Implementation Steps for Redis Session Store

1. Provision Redis: Deploy a Redis instance on GCP. For production, using Memorystore for Redis is recommended for managed availability and scalability.

# Example using gcloud to create a Memorystore for Redis instance
gcloud redis instances create my-redis-instance \
    --region=us-central1 \
    --size=1GB \
    --tier=standard \
    --network=default # Or your specific VPC network

2. Add Redis Gem: Add the redis-rails gem to the application’s Gemfile.

# Gemfile
gem 'redis-rails'

3. Configure Rails: Update config/initializers/session_store.rb to use the Redis store.

# config/initializers/session_store.rb

# Ensure you have Redis running and accessible.
# For Memorystore, use the instance's connection string.
# Example: redis://10.x.x.x:6379 or redis://redis-instance.REGION.c.PROJECT_ID.cache.googleusercontent.com:6379

redis_host = ENV.fetch('REDIS_HOST', 'localhost')
redis_port = ENV.fetch('REDIS_PORT', 6379)
redis_db = ENV.fetch('REDIS_DB', 0)
redis_password = ENV.fetch('REDIS_PASSWORD', nil) # If password protected

session_store_config = {
  key: '_your_app_session_id', # Ensure this is consistent
  redis: {
    host: redis_host,
    port: redis_port,
    db: redis_db,
    password: redis_password,
    # Other options like :timeout, :driver, etc. can be added here
  }
}

# If using Rails 5+ and redis-rails gem
Rails.application.config.session_store :redis_session_store, session_store_config

# For older Rails versions, you might use:
# ActionDispatch::Session::RedisSessionStore.new(session_store_config)
# And then configure it via ActionDispatch::Base.session_store = ...

4. Environment Variables: Configure environment variables for Redis connection details, especially when deploying to GCP. This is crucial for security and flexibility.

# Example .env file or environment variable setup
export REDIS_HOST="redis-instance.us-central1.c.your-gcp-project-id.cache.googleusercontent.com"
export REDIS_PORT="6379"
export REDIS_DB="0"
# export REDIS_PASSWORD="your_redis_password" # If applicable

5. Deploy and Test: Deploy the updated application and thoroughly test session functionality. Verify that session cookies are now simple session IDs and that the session data is correctly stored and retrieved from Redis.

Phase 4: Post-Mitigation Hardening and Ongoing Monitoring

Beyond fixing the immediate deserialization vulnerability, several hardening measures were implemented:

  • Session Cookie Security Flags: Ensured session cookies were set with HttpOnly and Secure flags.
  • Input Validation: Reinforced input validation across all API endpoints and user-facing forms to prevent other injection-style attacks.
  • Dependency Scanning: Integrated automated dependency scanning (e.g., Bundler-audit, Snyk) into the CI/CD pipeline to detect known vulnerabilities in gems.
  • GCP Security Best Practices: Reviewed and tightened GCP firewall rules, IAM policies, and enabled VPC Service Controls where appropriate to limit the blast radius of potential breaches.
  • Logging and Alerting: Enhanced application and infrastructure logging, feeding critical security events into a centralized SIEM for real-time alerting. This includes monitoring for unusual session activity or deserialization errors.

GCP Firewall Configuration Example

To restrict access to the Redis Memorystore instance, a specific firewall rule was configured in GCP:

# Allow ingress traffic from your application's network to Redis on port 6379
gcloud compute firewall-rules create allow-app-to-redis \
    --network=default \
    --allow=tcp:6379 \
    --source-ranges=10.128.0.0/20 \ # Replace with your application's subnet CIDR
    --target-tags=your-app-server-tag # Or use service accounts for more granular control

This ensures that only authorized application instances can communicate with the Redis instance, reducing the attack surface.

Conclusion

The audit successfully identified and remediated a critical insecure deserialization vulnerability in the legacy session handling of a high-traffic Ruby enterprise application. The transition to a secure, server-side session store like Redis, coupled with robust GCP security configurations and ongoing monitoring, significantly enhanced the application’s security posture. This case study underscores the importance of regularly auditing legacy components and staying abreast of common serialization vulnerabilities.