CVE-2026-19484 in busboy
Summary
by MITRE • 08/13/2026
@fastify/busboy is a multipart form-data parser. In versions 3.1.0 through 3.2.0, a remote unauthenticated attacker can stall the Node.js event loop by sending a multipart request whose boundary is crafted to a specific length. The vendored streaming search stores its skip table in a fixed 256 entry byte array, and a boundary of exactly 252 bytes makes the search needle 256 bytes, which truncates the default skip distance to zero and turns the search into a CPU bound loop on a small body. A single small request can keep one core busy and deny service to other requests handled by the same process. The issue is fixed in @fastify/busboy 3.2.1, which widens the skip table so the skip distance is preserved. Users should upgrade to 3.2.1.
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Analysis
by VulDB Data Team • 08/13/2026
The vulnerability in @fastify/busboy versions 3.1.0 through 3.2.0 represents a sophisticated denial of service attack vector that exploits a fundamental flaw in the multipart form-data parsing implementation. This issue specifically targets the streaming search algorithm used to locate boundaries within multipart requests, creating a condition where an attacker can manipulate request parameters to trigger excessive CPU consumption. The vulnerability stems from the use of a fixed 256-entry byte array for storing skip table values, which becomes problematic when processing boundaries of precisely 252 bytes in length. This particular boundary length causes the search needle to expand to exactly 256 bytes, resulting in the truncation of the default skip distance to zero.
The technical execution of this vulnerability leverages a well-known algorithmic weakness in string searching implementations where the Boyer-Moore search algorithm's efficiency relies on proper skip table calculations. When the skip distance becomes zero due to boundary length manipulation, the algorithm degenerates into a linear search pattern that processes each character sequentially rather than skipping ahead based on character frequency analysis. This transformation from efficient O(n/m) complexity to O(nm) complexity creates an extreme computational burden where even small request bodies can consume substantial CPU cycles. The impact is particularly severe because Node.js operates on a single-threaded event loop model, meaning that when one core becomes consumed with this CPU-bound operation, it blocks other requests from being processed by the same process.
This vulnerability directly maps to CWE-400, which categorizes unchecked resource consumption as a weakness that can lead to denial of service conditions. The attack vector aligns with ATT&CK technique T1499.004, specifically targeting network denial of service through resource exhaustion mechanisms. The operational impact extends beyond simple request blocking; it represents a sophisticated attack that can be executed without authentication, making it particularly dangerous in production environments where multiple requests are handled concurrently. The vulnerability creates a scenario where an attacker needs only to craft a single malicious request with a 252-byte boundary to effectively consume one CPU core entirely, thereby denying service to legitimate users and potentially causing cascading failures in systems that rely on the affected parsing library.
The fix implemented in version 3.2.1 addresses this vulnerability by widening the skip table beyond the 256-entry limitation, ensuring that skip distances are preserved regardless of boundary length. This modification restores the algorithm's intended performance characteristics while maintaining backward compatibility. Organizations should prioritize upgrading to version 3.2.1 as an immediate remediation measure, as the vulnerability creates a persistent threat that can be exploited by any remote attacker without requiring authentication or specialized privileges. The fix demonstrates the importance of proper algorithmic design and buffer sizing in security-critical components, highlighting how seemingly minor implementation details can create significant operational risks when not properly validated against edge cases and adversarial inputs.