CVE-2026-93761 in Mongoid
Summary
by MITRE • 09/18/2026
An inefficient regular expression complexity issue in the in-memory query evaluation component of the Mongoid library may allow an unauthenticated party to cause excessive processing within an embedding application process. Applications that place user-supplied text into a pattern-matching query condition on an embedded association may become unresponsive.
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Analysis
by VulDB Data Team • 09/18/2026
The vulnerability identified involves a Regular Expression Denial of Service, commonly referred to as ReDoS, located within the in-memory query evaluation component of the Mongoid library. This security flaw stems from inefficient regular expression complexity that can be exploited by an unauthenticated attacker to trigger catastrophic backtracking during pattern matching operations. When user-supplied text is incorporated into a regex-based query condition targeting an embedded association, the underlying engine may enter an exponential time complexity state relative to the input length. This behavior allows external actors to craft specific malicious inputs designed to maximize computational overhead, thereby consuming excessive processing resources within the embedding application process without requiring any form of authentication or prior access privileges.
From a technical perspective, this issue is classified under CWE-400: Uncontrolled Resource Consumption and specifically aligns with CWE-1325: Improper Regular Expression Validation. The core mechanism relies on ambiguous regular expressions that allow multiple paths to match the same input string, forcing the regex engine to explore all possible combinations before determining a failure or success state. In the context of Mongoid, which serves as an Object-Document Mapper for Ruby applications interacting with MongoDB, this flaw manifests when queries are constructed using dynamic user data in embedded document fields. The application process becomes unresponsive not because it crashes, but because it is trapped in a CPU-intensive loop evaluating the malformed pattern, effectively halting legitimate request processing and degrading service availability for all users connected to that instance.
The operational impact of this vulnerability is significant, primarily affecting the confidentiality, integrity, and availability of the hosted application services. By inducing excessive resource consumption, an attacker can achieve a Denial of Service condition against the specific application process hosting the vulnerable Mongoid version. This results in service unavailability for legitimate users who are unable to retrieve data or perform transactions during the attack window. Furthermore, because the vulnerability allows exploitation by unauthenticated parties, it presents a low-barrier entry point for attackers seeking to disrupt business operations without needing valid credentials. The impact extends beyond simple downtime; prolonged resource exhaustion can lead to memory leaks if garbage collection is starved of CPU cycles, potentially causing application restarts and loss of in-memory state or session data.
To mitigate this risk, developers must immediately update the Mongoid library to a version that includes patches for regular expression complexity issues within its query evaluation engine. It is critical to review all codebases where user-supplied input is directly interpolated into regex patterns used for filtering embedded associations. As a defensive coding practice, inputs should be validated against strict allow-lists rather than relying on complex matching logic when possible. If pattern matching is necessary, developers should implement timeout mechanisms or use regex engines that support atomic grouping and possessive quantifiers to prevent catastrophic backtracking. Additionally, deploying Web Application Firewalls with rules capable of detecting anomalous request lengths or patterns associated with ReDoS attacks can provide an additional layer of defense at the network perimeter while internal remediation efforts are completed. This vulnerability is also relevant to MITRE ATT&CK technique T1496: Resource Hijacking, where attackers leverage system resources for disruptive purposes rather than data exfiltration.