CVE-2026-72852

Name of the Vulnerable Software and Affected Versions hank-ai/darknet (affected versions not specified)

Description The software calculates the size of weight and output heap buffers for a convolutional layer using unchecked 32-bit integer arithmetic based on fields from a .cfg file. In the file src-lib/convolutional layer.cpp, the variables l.nweights and l.outputs are computed and passed to xcalloc. If the product of the dimensions in the .cfg file exceeds INT MAX, an integer overflow occurs, resulting in an undersized buffer allocation. Subsequently, the forward convolutional layer function re-derives the GEMM (General Matrix Multiply) dimensions using a different operand order, leading to out-of-bounds read and write operations through the undersized buffer. This can be triggered by loading a specially crafted .cfg file during inference or training, without requiring a valid .weights file. This issue can lead to heap buffer overflow reads in gemm nn fast() and glibc allocator metadata corruption.

Recommendations At the moment, there is no information about a newer version that contains a fix for this vulnerability.