CVE-2026-79832 in NonStop SQL
Summary
by MITRE • 10/15/2026
A stack buffer overflow vulnerability in HPE NonStop SQL/MX Executor may potentially result in information disclosure or process crash.
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Analysis
by VulDB Data Team • 10/15/2026
The identified vulnerability resides within the execution engine of Hewlett-Packard Enterprise's NonStop SQL/MX database management system, specifically affecting the component responsible for processing and executing SQL queries. This software is a critical enterprise-grade relational database designed for high-availability environments, often deployed in mission-critical sectors such as finance, telecommunications, and healthcare where data integrity and continuous uptime are paramount. The vulnerability manifests during the parsing or execution phase of specific complex query structures, indicating that the flaw is triggered by malformed input rather than general system operation. This context places the issue squarely within the realm of application-layer vulnerabilities, requiring an attacker to have some level of interaction with the database interface, such as through a direct SQL connection or via an authorized API endpoint, to exploit the condition effectively.
At its core, this is a stack buffer overflow vulnerability, which corresponds directly to CWE-121 in the Common Weakness Enumeration standard. The technical flaw arises when the executor component fails to adequately validate the length of input data before copying it into a fixed-size memory buffer allocated on the call stack. When an attacker supplies a payload that exceeds the expected bounds of this buffer, the excess data overwrites adjacent memory locations on the stack. This overwrite can corrupt critical control flow data, such as return addresses or saved frame pointers, leading to unpredictable program behavior. In many cases involving database engines, attackers may leverage this overflow not only for arbitrary code execution but more commonly for information disclosure by reading sensitive memory contents that were previously inaccessible due to standard access controls.
The operational impact of this vulnerability is significant given the nature of SQL/MX deployments. If exploited successfully, an attacker could achieve unauthorized information disclosure, potentially exposing internal database structures, cached query plans, or even credentials stored in memory during authentication processes. This aligns with the ATT&CK technique T1005, which covers Data from Local System. Furthermore, if the overflow allows for control of instruction pointers without successful code execution, it can lead to a denial-of-service condition by causing the database process to crash unexpectedly. For enterprise systems relying on NonStop SQL/MX for continuous availability, such crashes disrupt service levels and require manual intervention or automatic failover mechanisms to restore functionality, thereby impacting business continuity. The severity is compounded if the database engine runs with elevated privileges, as this increases the potential blast radius of any successful exploitation attempt.
Mitigation strategies must address both immediate remediation and long-term architectural resilience. The primary defense involves applying vendor-provided patches or updates that correct the buffer boundary checks within the executor module. Organizations should prioritize updating to versions where input validation is strictly enforced for all query parameters, particularly those involving large text blobs or complex nested structures. In addition to patching, defensive measures include implementing strict network segmentation to limit access to the database server from untrusted networks and enforcing least-privilege principles for user accounts connecting to SQL/MX. Application-level controls should also be reviewed to ensure that input sanitization is performed before queries reach the engine, adding a layer of defense in depth against malformed inputs. Regular vulnerability scanning focused on application-layer flaws and monitoring logs for anomalous query patterns can further aid in detecting potential exploitation attempts before they result in system compromise or disruption.