3 vulnerabilities classified as CWE-1049 (大数据表中的数据查询操作过多). AI Chinese analysis included.
CWE-1049 represents a performance-related weakness where applications execute inefficient database queries involving excessive joins and sub-queries against large datasets. This flaw typically manifests when developers fail to optimize SQL statements, leading to severe latency, high CPU usage, and potential denial-of-service conditions as the database struggles to process complex operations on tables exceeding one million rows. Attackers may exploit this by triggering resource-intensive queries, effectively exhausting system resources and degrading service availability for legitimate users. To mitigate this risk, developers must implement rigorous query optimization techniques, such as indexing strategic columns, reducing join complexity, and limiting result sets. Regular performance testing and adherence to CISQ guidelines regarding query structure are essential for maintaining system stability and ensuring responsive data retrieval in high-volume environments.
| CVE ID | Title | CVSS | Severity | Published |
|---|---|---|---|---|
| CVE-2025-0190 | Denial of Service in aimhubio/aim — aimhubio/aim | 7.5 | - | 2025-03-20 |
| CVE-2023-5192 | Excessive Data Query Operations in a Large Data Table in pimcore/demo — pimcore/demo | 8.8 | - | 2023-09-26 |
| CVE-2019-8460 | OpenBSD 安全漏洞 — OpenBSD | 7.5 | - | 2019-08-26 |
Vulnerabilities classified as CWE-1049 (大数据表中的数据查询操作过多) represent 3 CVEs. The CWE taxonomy describes the weakness; review individual CVEs for product-specific impact.