CVE-2026-50144: CWE-20: Improper Input Validation in Tencent ncnn
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.
AI Analysis
Technical Summary
CVE-2026-50144 describes an improper input validation vulnerability in Tencent's ncnn framework. Specifically, in commit e54f7b1f88434e1d844ea0551b880a1cfb079ce1 and earlier, the load_param() function in ncnn::ParamDict allows an out-of-bounds heap write when loading a malicious .param model file. The parameter ID is only checked against being greater than or equal to NCNN_MAX_PARAM_COUNT, but negative IDs are not properly handled, enabling indexing before the params array. This vulnerability is addressed by commit 5a0288f255daa6c3294f77109f67718e434ec020.
Potential Impact
The vulnerability allows an attacker to cause an out-of-bounds heap write, which can lead to integrity and availability impacts such as application crashes or potential code execution. The CVSS v3.1 score is 7.1 (high), with attack vector local, low attack complexity, no privileges required, user interaction required, unchanged scope, no confidentiality impact, high integrity impact, and high availability impact.
Mitigation Recommendations
A fix for this vulnerability is available as it was addressed in commit 5a0288f255daa6c3294f77109f67718e434ec020. Users should update to a version of ncnn that includes this commit to remediate the issue. Patch status is not explicitly confirmed in vendor advisories, so users should verify the presence of this fix in their version. No additional mitigations are specified.
CVE-2026-50144: CWE-20: Improper Input Validation in Tencent ncnn
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 v3.1
Score 7.1high
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-50144 describes an improper input validation vulnerability in Tencent's ncnn framework. Specifically, in commit e54f7b1f88434e1d844ea0551b880a1cfb079ce1 and earlier, the load_param() function in ncnn::ParamDict allows an out-of-bounds heap write when loading a malicious .param model file. The parameter ID is only checked against being greater than or equal to NCNN_MAX_PARAM_COUNT, but negative IDs are not properly handled, enabling indexing before the params array. This vulnerability is addressed by commit 5a0288f255daa6c3294f77109f67718e434ec020.
Potential Impact
The vulnerability allows an attacker to cause an out-of-bounds heap write, which can lead to integrity and availability impacts such as application crashes or potential code execution. The CVSS v3.1 score is 7.1 (high), with attack vector local, low attack complexity, no privileges required, user interaction required, unchanged scope, no confidentiality impact, high integrity impact, and high availability impact.
Mitigation Recommendations
A fix for this vulnerability is available as it was addressed in commit 5a0288f255daa6c3294f77109f67718e434ec020. Users should update to a version of ncnn that includes this commit to remediate the issue. Patch status is not explicitly confirmed in vendor advisories, so users should verify the presence of this fix in their version. No additional mitigations are specified.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-06-03T18:49:32.275Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a57eb0b68715ace4363c88d
Added to database: 07/15/2026, 20:18:19 UTC
Last enriched: 07/22/2026, 22:54:50 UTC
Last updated: 08/29/2026, 22:52:12 UTC
Views: 75
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