threat-modeling.md

Threat Model Analysis for ankane/searchkick

Threat: Elasticsearch Query Injection

• Threat: Elasticsearch Query Injection
• Description: An attacker crafts malicious search queries by injecting Elasticsearch Query DSL commands through user input fields that are used by Searchkick to build search queries. They might manipulate search parameters to bypass intended search logic, access unauthorized data, or cause errors in Elasticsearch. For example, an attacker could inject a match_all query within a seemingly innocuous search term to retrieve all indexed documents regardless of the intended search criteria, effectively bypassing intended search filters implemented using Searchkick.
• Impact:
  • Unauthorized data access: Attackers can retrieve sensitive data they are not supposed to access through the application's search functionality powered by Searchkick.
  • Data exfiltration: Attackers can extract large amounts of data from the Elasticsearch index using Searchkick's search interface.
  • Denial of Service (DoS): Malicious queries crafted via Searchkick can overload Elasticsearch, causing performance degradation or crashes, impacting the application's search feature.
  • Potential data modification or deletion (in misconfigured setups): In rare cases, if Elasticsearch is improperly configured and Searchkick's Elasticsearch user has excessive permissions, attackers might be able to modify or delete data through crafted queries injected via Searchkick.
• Affected Searchkick Component:
  • Searchkick.search function
  • Query building logic within application code that uses user input to construct search queries via Searchkick.
• Risk Severity: High
• Mitigation Strategies:
  • Input Validation and Sanitization: Thoroughly validate and sanitize all user inputs before using them in Searchkick search queries.
  • Use Searchkick's Query Builders: Utilize Searchkick's built-in query builder methods (e.g., where, match, aggs) instead of directly constructing raw Elasticsearch Query DSL strings from user input within Searchkick.
  • Parameterized Queries: Treat user input as parameters and let Searchkick handle the safe construction of the Elasticsearch query. Avoid directly embedding user input strings into raw queries processed by Searchkick.
  • Principle of Least Privilege (Elasticsearch User): Ensure the Elasticsearch user configured for Searchkick has minimal necessary permissions, specifically restricting write or delete access if not explicitly required for search operations performed through Searchkick.
  • Regular Security Audits: Regularly review the application code where Searchkick is used to construct search queries and ensure proper input handling and query construction techniques are employed to prevent injection vulnerabilities.

Threat: Searchkick Integration with an Unsecured Elasticsearch Cluster

• Threat: Searchkick Integration with an Unsecured Elasticsearch Cluster
• Description: Searchkick is configured to connect to an Elasticsearch cluster that is not properly secured. This allows unauthorized access to the Elasticsearch cluster, potentially from external networks, directly impacting any application using Searchkick with this cluster. This lack of security in the Elasticsearch dependency directly undermines the security of applications relying on Searchkick for search functionality. An attacker could exploit the unsecured Elasticsearch cluster to access, modify, or delete data indexed by Searchkick.
• Impact:
  • Complete data breach via Searchkick's indexed data: Full exposure of all data indexed in Elasticsearch by Searchkick, accessible to unauthorized parties.
  • Data manipulation affecting Searchkick's search results: Attackers can modify, delete, or corrupt indexed data within Elasticsearch, leading to corrupted or manipulated search results presented by applications using Searchkick.
  • Denial of Service (DoS) impacting Searchkick functionality: Attackers can overload or crash the Elasticsearch cluster, rendering Searchkick's search functionality unavailable in dependent applications.
  • Cluster takeover, compromising Searchkick's data backend: In severe cases, attackers could gain control of the Elasticsearch cluster itself, potentially compromising all data managed by Searchkick and impacting all applications relying on it.
• Affected Searchkick Component:
  • Elasticsearch client configuration within Searchkick (Searchkick.client).
  • The overall Searchkick integration relies on the security of the underlying Elasticsearch cluster.
• Risk Severity: Critical
• Mitigation Strategies:
  • Enable Elasticsearch Authentication and Authorization: Implement Elasticsearch security features like X-Pack Security (now Elastic Security) or Open Distro for Elasticsearch Security to enforce authentication and role-based access control for all connections, including those from Searchkick.
  • Network Segmentation for Elasticsearch: Isolate the Elasticsearch cluster within a private network, ensuring it is accessible only from trusted application servers running Searchkick. Use firewalls to strictly control network access to the Elasticsearch cluster used by Searchkick.
  • Principle of Least Privilege (Elasticsearch Users for Searchkick): Create dedicated Elasticsearch users with minimal necessary permissions specifically for Searchkick to connect and operate. Limit these users to only the permissions required for indexing and searching, and restrict administrative or data modification permissions unless absolutely necessary for Searchkick's intended function.
  • Secure Elasticsearch Configuration: Follow Elasticsearch security best practices meticulously, including disabling default ports if not needed externally, enforcing HTTPS for all communication between Searchkick and Elasticsearch, and regularly updating Elasticsearch to patch known vulnerabilities.
  • Regular Security Audits of Elasticsearch Infrastructure: Periodically audit Elasticsearch security configurations, access logs, and network security surrounding the Elasticsearch cluster used by Searchkick to ensure ongoing security and identify any potential misconfigurations or vulnerabilities.

Threat: Unintentional Indexing of Sensitive Data via Searchkick

• Threat: Unintentional Indexing of Sensitive Data via Searchkick
• Description: Developers, when implementing Searchkick in their application, inadvertently configure Searchkick to index sensitive data that should not be searchable or publicly accessible through the application's search features. This often occurs due to misconfiguration of the searchable attributes in application models or a lack of complete understanding of what data is being passed to Searchkick for indexing. For example, a developer might mistakenly include a social_security_number field in the searchable attributes of a User model, making this sensitive information searchable.
• Impact:
  • Data exposure through Searchkick's search functionality: Sensitive information becomes searchable and potentially accessible through the application's search interface, exposing it to unauthorized users who can perform searches via Searchkick.
  • Privacy violations and compliance breaches: Breach of user privacy and potential non-compliance with data protection regulations (e.g., GDPR, CCPA, HIPAA) due to sensitive data being made searchable and accessible through Searchkick.
  • Reputational damage and loss of user trust: Public exposure of sensitive data through search features powered by Searchkick can lead to significant reputational damage and erosion of user trust in the application and organization.
• Affected Searchkick Component:
  • searchable method in application models that define what data Searchkick indexes.
  • Indexing logic within models and background jobs managed by Searchkick that control data flow to Elasticsearch.
• Risk Severity: High
• Mitigation Strategies:
  • Data Classification and Sensitivity Analysis before Searchkick Implementation: Thoroughly identify and classify sensitive data within the application before configuring Searchkick. Understand what data is truly necessary to be searchable and what data must remain protected.
  • Careful and Minimal searchable Attribute Configuration in Searchkick Models: Extremely carefully review and configure the searchable attributes in application models used with Searchkick. Ensure that only intentionally searchable data is included and that sensitive data is explicitly excluded from indexing by Searchkick.
  • Data Masking or Redaction before Searchkick Indexing: Implement data masking or redaction techniques to remove or obscure sensitive portions of data before it is passed to Searchkick for indexing. If search functionality is needed on parts of the data but not the sensitive portions, transform the data to remove sensitive elements before indexing with Searchkick.
  • Regular Data Audits of Elasticsearch Index Content: Periodically audit the Elasticsearch index created and managed by Searchkick to verify that only intended data is being indexed and that sensitive data is not inadvertently exposed through Searchkick's indexing process. Implement automated checks to detect unexpected sensitive data in the Searchkick index.
  • Code Reviews Focused on Searchkick Configuration: Implement mandatory code reviews specifically focused on Searchkick configuration, particularly the searchable attributes and indexing logic, to catch potential misconfigurations that could lead to unintentional indexing of sensitive data. Ensure reviewers are trained to identify sensitive data and verify proper Searchkick configuration to prevent its exposure.