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Rack, a modular Ruby web server interface, contains a high-severity vulnerability (CVE-2025-59830) discovered in versions prior to 2.2.18. The vulnerability lies in Rack::QueryParser's parameter handling mechanism, where it enforces params_limit only for parameters separated by '&' while still splitting on both '&' and ';' characters. This implementation flaw allows attackers to bypass the parameter count limit by using semicolon separators, potentially leading to increased resource consumption (GitHub Advisory).
The vulnerability exists in the Rack::QueryParser#checkquerystring function, where it counts only '&' characters when determining the number of parameters, while the default separator regex DEFAULT_SEP = /[&;] */n splits on both '&' and ';'. This mismatch allows queries using semicolon separators to bypass the parameter count limit. The vulnerability has been assigned a CVSS v3.1 base score of 7.5 (High) with the vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H, indicating network accessibility with no required privileges or user interaction (GitHub Advisory, NVD).
Applications or middleware that directly invoke Rack::QueryParser with its default configuration (no explicit delimiter) are exposed to increased CPU and memory consumption, which can be exploited as a limited denial-of-service vector. However, Rack::Request, the primary entry point for typical Rack applications, uses QueryParser in a safe way and is not vulnerable by default. The impact is primarily limited to edge cases where QueryParser is used directly (GitHub Advisory).
The primary mitigation is to upgrade to Rack version 2.2.18 or later, where both '&' and ';' are counted consistently toward params_limit. For systems unable to upgrade immediately, a workaround is to configure QueryParser with an explicit delimiter (e.g., '&') to avoid the mismatch. Additionally, it's recommended to enforce query string and request size limits at the web server or proxy layer (e.g., Nginx, Apache, or a CDN) to mitigate excessive parsing overhead (GitHub Advisory, Miggo).
Source: This report was generated using AI
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