CVE-2026-84963 in C Driver
Summary
by MITRE • 09/03/2026
An incorrect numeric conversion in the JSON parsing component of the MongoDB C Driver's BSON library may cause an unusually large text value to be silently shortened, or the corresponding field to be omitted, while the parsing operation still reports success and returns no error. An unauthenticated party who can supply the input processed by an application that uses this component may cause that application to hold data that does not match what was submitted, which may result in unintended alteration of data.
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Analysis
by VulDB Data Team • 09/03/2026
The vulnerability identified within the MongoDB C Driver's BSON library stems from a critical flaw in its JSON parsing logic, specifically involving incorrect numeric conversions during the processing of text values. This issue manifests when the parser encounters unusually large or malformed numeric representations embedded within string fields. Instead of raising an error to alert the application developer or user that the input data is invalid or exceeds expected bounds, the library silently truncates the value or omits the corresponding field entirely from the resulting BSON document. Crucially, this silent failure occurs while the parsing operation reports success and returns no error code, creating a deceptive state where the application believes it has successfully processed valid data when in fact the integrity of that data has been compromised without any indication to the calling process.
From a technical perspective, this flaw represents a classic case of improper input validation leading to silent data corruption. The BSON specification allows for various string representations, but the driver's internal logic fails to correctly handle edge cases involving numeric strings that exceed standard integer or floating-point limits during conversion attempts. When such values are encountered, rather than triggering an exception or returning a specific error code indicating overflow or truncation, the parser applies heuristic shortcuts that result in data loss. This behavior violates the principle of fail-safe defaults and robust input handling, as it allows malformed inputs to pass through the validation layer undetected. The absence of explicit error signaling means that downstream components relying on this parsed data will operate under false assumptions about the content's accuracy, leading to potential logic errors or incorrect state management within the application architecture.
The operational impact of this vulnerability is significant for any system utilizing the MongoDB C Driver as a dependency for database interactions. An unauthenticated attacker who can supply input processed by an application using this component may cause that application to hold data that does not match what was originally submitted. This discrepancy results in unintended alteration of persistent or transient state, which can have severe consequences depending on the context. For instance, if financial transactions, user credentials, or configuration settings are affected, silent truncation could lead to unauthorized access, incorrect billing calculations, or system misconfiguration. Because the error is not reported, debugging such issues becomes exceedingly difficult, as logs will show successful operations despite data inconsistencies appearing in the database. This lack of observability exacerbates the risk, allowing malicious actors to exploit these discrepancies for privilege escalation, data integrity attacks, or denial-of-service conditions where applications behave unpredictably due to corrupted internal states.
This vulnerability aligns with CWE-20 Improper Input Validation and CWE-681 Incorrect Conversion between Numeric Types, as it involves a failure to properly validate the range and format of input data before processing. Furthermore, in the context of attack patterns, this behavior facilitates CWE-94 Improper Control of Generation of Code (Code Injection) or more broadly CWE-770 Allocation of Resources Without Limits or Throttling if the truncation leads to resource exhaustion scenarios, though primarily it falls under integrity violations akin to ATT&CK technique T1562 Impair Defenses by disabling security monitoring features. The silent nature of the failure effectively impairs defensive mechanisms that rely on accurate audit logs and error reporting, making detection and response more challenging for security operations teams.
To mitigate this risk, developers must ensure they are using a patched version of the MongoDB C Driver where these numeric conversion flaws have been addressed with stricter validation rules. It is essential to implement comprehensive input sanitization at the application layer before data reaches the driver, ensuring that expected formats and ranges are enforced explicitly rather than relying solely on library defaults. Additionally, applications should be configured to treat any parsing operation as potentially risky if it involves untrusted external inputs, implementing strict error handling routines that do not assume success based solely on return codes but also validate the structural integrity of the resulting BSON documents against known schemas or expected data patterns. Regular security audits and static analysis tools focused on numeric overflow and conversion errors should be integrated into the development lifecycle to catch such issues early.