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Attack Surface Analysis for ankane/searchkick

  • Description: Attackers craft queries that retrieve more data than intended, bypassing access controls.
  • Searchkick Contribution: Searchkick provides a powerful, user-friendly query interface to Elasticsearch. This ease of use, without proper application-level restrictions, directly enables attackers to construct overly broad queries. The core issue is Searchkick's capability combined with insufficient application-level safeguards.
  • Example: An attacker uses "*" in a search field intended for usernames, and the application doesn't restrict this via Searchkick's where clause, leading to retrieval of all user records. Or, an attacker leverages complex where clause combinations (e.g., many _or conditions) that the application fails to validate, bypassing intended filters.
  • Impact: Unauthorized disclosure of sensitive data, violation of privacy, potential for further attacks.
  • Risk Severity: Critical
  • Mitigation Strategies:
    • Strict Input Validation: Implement a whitelist of allowed characters and patterns for search terms. Reject any input that doesn't conform. This is essential before the input even reaches Searchkick.
    • Pre-Filtering (Crucial): Use Searchkick's where clause before applying the user's search term to restrict results based on user roles and permissions. Example: User.search(params[:q], where: { organization_id: current_user.organization_id }). This is the primary defense, leveraging Searchkick's features for security.
    • Field Control: Limit which fields are searchable and retrievable via Searchkick and Elasticsearch configuration. Don't index sensitive data that doesn't need to be searched. Use _source filtering.
    • Aggregation Control: Restrict or disable aggregations, or carefully control the fields and parameters used via Searchkick's API.
    • Pagination and Rate Limiting: Implement strict pagination limits and rate limiting (both in the application and potentially within Searchkick/Elasticsearch) to prevent exhaustive data retrieval.
  • Description: Attackers craft complex or computationally expensive queries to overload the Elasticsearch cluster, causing a denial of service.
  • Searchkick Contribution: Searchkick's simplified query building makes it easier to create (intentionally or unintentionally) resource-intensive queries if the application doesn't impose limits. The library itself doesn't inherently cause DoS, but its ease of use facilitates it without proper controls.
  • Example: An attacker submits a query with deeply nested OR conditions, excessive wildcards, or complex aggregations through Searchkick's interface, and the application doesn't limit the query's complexity. Or, a query using User.search("*", fields: [:field1, :field2, ...], where: { ... }) with a large number of fields and complex where conditions, not restricted by the application.
  • Impact: Application downtime, loss of service availability, potential financial losses.
  • Risk Severity: High
  • Mitigation Strategies:
    • Query Timeouts: Use Searchkick's timeout option to limit the execution time of individual queries. This is a direct use of Searchkick for mitigation. Set appropriate timeouts on the Elasticsearch cluster itself.
    • Resource Limits: Configure resource limits (CPU, memory) on the Elasticsearch cluster (this is outside of Searchkick, but essential).
    • Query Monitoring: Monitor Elasticsearch performance and identify slow or resource-intensive queries (partially related to Searchkick usage).
    • Rate Limiting: Implement rate limiting on search requests to prevent abuse. Limit the frequency of searches per user or IP address (can be done in conjunction with Searchkick).
    • Disable Scripting: Disable or severely restrict the use of scripting in queries accessible through Searchkick.
    • Input Validation (Again): Limit the complexity of user-provided search terms before they reach Searchkick (e.g., restrict the number of wildcards, the length of the query, the number of OR conditions).