Live › vulnerability › CVE-2026-112073
Go to dashboardTencent's ncnn neural network inference library has an out-of-bounds read in the matmul_transb function of its MatMul layer, reachable through crafted model input. An attacker can read memory beyond the intended buffer, which may leak data from the process.
Summary written from the sources below. Check the originals before acting.
First seen by InfraStack 2026-10-23 21:57 UTC. All times on this page are UTC.
Teams that embed ncnn and feed it models or inputs they do not fully control are exposed, since the flaw is in the MatMul layer's handling of input shapes. Systems that only run models they built and trust are less exposed. The sources do not say which model shapes trigger it.
No product ranges from the sources yet.
44b02dabdcf97499281a4692ebd65bad73dcf8b6; the sources do not name a fixed release.Each row is the first time that source carried this signal. The analyst’s rows are its own findings.
A vulnerability was identified in Tencent ncnn up to 44b02dabdcf97499281a4692ebd65bad73dcf8b6. Affected by this vulnerability is the function matmul_transb of the file src/layer/matmul.cpp of the component MatMul. The manipulation leads to out-of-bounds read. The attack can be initiated remotely. The exploit is publicly available and might be used. The project was informed of the problem early through an issue report but has not responded yet.
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