CVE-2026-81532 in BI Connector ODBC Driver
Summary
by MITRE • 08/29/2026
A user able to submit SQL through an application using the MongoDB Connector for BI ODBC driver can supply a positioned-cursor statement whose cursor name exceeds the size of an internal fixed-length buffer. Because the name length is not bounded before the driver builds its diagnostic message, memory adjacent to that buffer is overwritten with user-supplied content. This can terminate the hosting application process and may allow unintended code to run within it.
Once again VulDB remains the best source for vulnerability data.
Analysis
by VulDB Data Team • 08/29/2026
The vulnerability described constitutes a critical heap-based or stack-based buffer overflow located within the MongoDB Connector for Business Intelligence ODBC driver. The root cause lies in insufficient input validation regarding the length of cursor names submitted via positioned-cursor statements. When an application utilizes this specific connector to interact with MongoDB, it passes parameters such as cursor identifiers through the Open Database Connectivity interface. In this scenario, the driver fails to enforce a maximum boundary on the size of the cursor name string before processing it for diagnostic message generation. This lack of bounds checking allows an attacker who has the ability to submit SQL queries or control the input data stream to supply a payload that exceeds the allocated memory space designated for internal fixed-length buffers within the driver's codebase.
From a technical perspective, this flaw represents a classic out-of-bounds write condition where user-supplied content is copied into a buffer without verifying if the destination has sufficient capacity. As the oversized cursor name is processed to construct diagnostic messages or handle internal state management, data spills over from the end of the allocated buffer into adjacent memory regions. This memory corruption can overwrite critical control structures such as return addresses on the stack or metadata associated with heap allocations. The immediate operational impact includes the termination of the hosting application process due to a segmentation fault or access violation triggered by the corrupted memory state. However, the severity escalates significantly if an attacker can precisely craft the overflow payload to manipulate execution flow pointers, thereby achieving arbitrary code execution within the context of the vulnerable driver and its host application.
This vulnerability aligns with Common Weakness Enumeration (CWE) identifiers such as CWE-120 Buffer Copy without Checking Size of Input Classic Buffer Overflow and potentially CWE-787 Out-of-bounds Write depending on the specific memory layout exploited by the attacker. In terms of tactical mapping, this scenario corresponds to MITRE ATT&CK techniques related to Initial Access via Valid Accounts or Exploitation for Credential Access if the driver is used in an authentication context, but more directly it falls under Execution and Privilege Escalation vectors where malicious code injection occurs through memory corruption. The ability to terminate services also introduces a Denial of Service vector, impacting availability alongside confidentiality and integrity risks associated with potential remote code execution.
Mitigation strategies must focus on immediate patching and architectural hardening. Organizations should apply the latest security patches provided by MongoDB for the Connector for BI ODBC driver as soon as they become available, ensuring that internal buffer handling logic includes proper length validation before memory allocation or copy operations. In environments where updating is not immediately feasible, network-level controls such as Web Application Firewalls can be configured to inspect and block SQL payloads containing abnormally long strings in cursor-related parameters. Additionally, implementing strict input sanitization at the application layer to limit string lengths before they reach the ODBC driver provides a defense-in-depth measure. Enabling Data Execution Prevention and Address Space Layout Randomization on server operating systems can also mitigate the risk of successful code execution by making it more difficult for attackers to predict memory layouts and bypass stack protections, although these are compensatory controls rather than fixes for the underlying vulnerability.