CVE-2026-88026 in C# Driver
Summary
by MITRE • 09/10/2026
Improper neutralization of regular-expression metacharacters in the LINQ query translation component of the MongoDB C# Driver can cause a caller-supplied character sequence to alter a regular-expression predicate generated by an affected application. An authenticated user who can influence such a value may cause the application to return records beyond those intended by the original filter.
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Analysis
by VulDB Data Team • 09/10/2026
The vulnerability described involves improper neutralization of special characters within regular expression patterns, specifically affecting the LINQ query translation component of the MongoDB C# Driver. This flaw allows an attacker who can supply input values that are subsequently used in database queries to manipulate the structure of generated regular expressions. In typical application logic, user-supplied data is often embedded into search filters or predicates without adequate sanitization against regex metacharacters such as parentheses, brackets, dots, and asterisks. When these characters are not properly escaped before being passed to the query engine, they can alter the logical structure of the regular expression predicate intended by the developer. This represents a classic instance of injection where untrusted data influences code execution logic, specifically within the context of database querying mechanisms rather than direct command execution.
From a technical perspective, this issue stems from insufficient validation or encoding of input strings before their inclusion in LINQ expressions that are translated into MongoDB query operators. The C# driver translates high-level language constructs like lambda expressions into low-level BSON queries. If the translation process fails to escape regex metacharacters present in user-controlled variables, an attacker can inject sequences that change how the pattern is interpreted by the database engine. For example, injecting a closing parenthesis or bracket could prematurely terminate the intended search scope and open up new matching criteria defined by the attacker. This manipulation enables the bypass of restrictive filters designed to limit data access based on specific attributes or conditions.
The operational impact of this vulnerability is significant for applications relying on precise data filtering through MongoDB queries using the C# driver. An authenticated user, which in many contexts includes any valid application session rather than just a system administrator, can exploit this flaw to retrieve records that were not intended to be accessible. This leads to unauthorized information disclosure and potential violation of access control policies enforced at the query level. The attacker does not need elevated privileges beyond standard authentication; they merely need the ability to provide input values that end up in filterable fields processed by LINQ-to-MongoDB translation logic. Consequently, sensitive data such as personal identifiable information, financial records, or proprietary business intelligence may be exposed to unauthorized parties, compromising confidentiality and integrity of the stored data.
This vulnerability aligns with Common Weakness Enumeration (CWE) category CWE-184, which covers improper neutralization of regular expression metacharacters. It also relates closely to CWE-77, injection vulnerabilities, as it involves manipulating query logic through input manipulation. In terms of the MITRE ATT&CK framework, this behavior corresponds to techniques involving data access and exfiltration via database queries, potentially falling under T1059 Command and Scripting Interpreter if interpreted broadly, but more accurately mapping to unauthorized access patterns associated with injection flaws in application-layer components. The attack vector is primarily local or network-based depending on the exposure of the vulnerable service, requiring authentication which limits it from being a remote unauthenticated exploit but still poses severe risks within authenticated environments.
Mitigation strategies should focus on rigorous input validation and secure coding practices for database interactions. Developers must ensure that all user-supplied data used in regular expression patterns is properly escaped or sanitized before inclusion in LINQ queries. Utilizing parameterized queries where possible, although less common with regex predicates compared to simple equality checks, can help isolate data from logic. Additionally, implementing strict allow-list validation for input fields ensures that only expected character sets are processed by the query engine. Application-level firewalls and runtime application self-protection tools may also detect anomalous patterns indicative of such injection attempts. Regular security audits focusing on database access layers and automated static code analysis tools configured to flag unsafe regex construction practices can further reduce the risk surface associated with this vulnerability type.