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Vulnerability record · CVE-2026-50144 · published 15 July 2026

CVE-2026-50144: Improper input validation vulnerability

ncnn is a high-performance neural network inference framework optimized for the mobile platform. In commit e54f7b1f88434e1d844ea0551b880a1cfb079ce1 and earlier, ncnn allows an out-of-bounds heap write in ncnn::ParamDict::load_param() when Net::load_param() loads a malicious .param model file because the parsed parameter id is checked only against id >= NCNN_MAX_PARAM_COUNT, allowing a negative id to index before the params[NCNN_MAX_PARAM_COUNT] array. This vulnerability is fixed by commit 5a0288f255daa6c3294f77109f67718e434ec020.

7.1 CVSS 3.1 High EPSS 0.16% · top 95.6% CWE-20 · Improper input validationCWE-129 · CWE-129 Awaiting Analysis
7.1CVSS 3.1 base score
0.16%EPSS exploitation probability, 30 days
NoNot in CISA KEV
0Affected product versions listed by NVD
3References
17 Jul 2026Last modified by NVD

Description

ncnn is a high-performance neural network inference framework optimized for the mobile platform. In commit e54f7b1f88434e1d844ea0551b880a1cfb079ce1 and earlier, ncnn allows an out-of-bounds heap write in ncnn::ParamDict::load_param() when Net::load_param() loads a malicious .param model file because the parsed parameter id is checked only against id >= NCNN_MAX_PARAM_COUNT, allowing a negative id to index before the params[NCNN_MAX_PARAM_COUNT] array. This vulnerability is fixed by commit 5a0288f255daa6c3294f77109f67718e434ec020.

CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:H

References

LinkTags
https://github.com/Tencent/ncnn/commit/5a0288f255daa6c3294f77109f67718e434ec020
https://github.com/Tencent/ncnn/security/advisories/GHSA-jxmc-3mv6-7pwr
https://github.com/Tencent/ncnn/security/advisories/GHSA-jxmc-3mv6-7pwr

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Source: NIST National Vulnerability Database (record CVE-2026-50144), CISA KEV, FIRST EPSS (scores of 2026-09-26). This page is refreshed as NVD updates the record.