CVE-2026-94440 in Google
Summary
by MITRE • 10/09/2026
Parsing a multipart form can bypass memory limits and read an arbitrarily long line into memory when the remaining limit at the start of a part is less than 400 bytes.
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Analysis
by VulDB Data Team • 10/09/2026
The vulnerability described involves a critical flaw in the parsing logic for HTTP multipart forms, specifically within environments that enforce strict memory consumption limits to prevent denial-of-service attacks or resource exhaustion. When an application processes a multipart form submission, it typically iterates through various parts of the request body, such as file uploads and text fields, while adhering to configured maximum size constraints. The core technical flaw arises from how the parser calculates and applies these remaining memory limits at the beginning of each part processing cycle. Specifically, if the calculated remaining limit for a specific part is less than 400 bytes, the parsing mechanism fails to correctly enforce boundaries or truncate input appropriately. This miscalculation allows an attacker to craft a multipart form where one section triggers this low-limit condition, causing the parser to allocate and read an arbitrarily long line into memory rather than rejecting it or limiting its size as intended.
This behavior constitutes a significant security risk because it effectively neutralizes the protective measures designed to limit resource usage during request processing. By exploiting this edge case, a malicious actor can force the server to consume excessive amounts of RAM by sending large payloads that bypass the expected limits. This leads directly to a denial-of-service condition where legitimate users are unable to access services due to system instability or crashes caused by memory exhaustion. The vulnerability aligns with CWE-787: Out-of-bounds Write and CWE-400: Uncontrolled Resource Consumption, as it involves improper handling of input data that results in unbounded resource allocation. Furthermore, from an offensive security perspective, this technique can be categorized under ATT&CK T1496: Resource Hijacking or more broadly within the scope of application-layer denial-of-service attacks where attackers target specific software components to degrade service availability rather than overwhelming network bandwidth.
The operational impact extends beyond simple memory exhaustion; it may also lead to secondary vulnerabilities if the improperly parsed data is subsequently processed by other parts of the application stack. For instance, if the oversized line contains malicious code or unexpected characters that are not sanitized due to the bypassed limits, there could be implications for injection attacks or buffer overflows in downstream components. However, the primary and most immediate consequence remains the destabilization of the server environment through uncontrolled memory allocation. This type of flaw is particularly dangerous because it often goes undetected by standard load testing tools that do not specifically target edge cases in parsing logic with low remaining limits.
Mitigation strategies must focus on correcting the boundary checks within the multipart parser implementation. Developers should ensure that memory limit calculations are robust and account for all overhead associated with data structures used during parsing, ensuring that no part of the input can exceed allocated resources regardless of initial conditions. It is essential to implement strict size validation before any significant allocation occurs and to use streaming parsers where possible to process data in chunks rather than loading entire lines into memory. Additionally, applying patches provided by the software vendor or upgrading to versions where this logic has been corrected is critical for immediate remediation. Security teams should also consider implementing rate limiting and request size restrictions at the web server or reverse proxy level as a defense-in-depth measure to catch malformed requests before they reach the application layer parsing routines.