hank-ai darknet up to 6.0 Convolutional Layer convolutional_layer.cpp gemm_nn_fast heap-based overflow

Summaryinfo

A vulnerability was found in hank-ai darknet up to 6.0 and classified as critical. Impacted is the function gemm_nn_fast of the file src-lib/convolutional_layer.cpp of the component Convolutional Layer. Executing a manipulation can lead to heap-based overflow. This vulnerability appears as CVE-2026-72852. The attack may be performed from remote. There is no available exploit.

Detailsinfo

A vulnerability was found in hank-ai darknet up to 6.0. It has been declared as critical. This vulnerability affects the function gemm_nn_fast of the file src-lib/convolutional_layer.cpp of the component Convolutional Layer. The manipulation with an unknown input leads to a heap-based overflow vulnerability. The CWE definition for the vulnerability is CWE-122. A heap overflow condition is a buffer overflow, where the buffer that can be overwritten is allocated in the heap portion of memory, generally meaning that the buffer was allocated using a routine such as malloc(). As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:

hank-ai/darknet sizes a convolutional layer's weight and output heap buffers by multiplying configuration fields taken from a .cfg file in unchecked 32-bit int arithmetic. In src-lib/convolutional_layer.cpp, l.nweights is computed as (c / groups) * n * size * size and l.outputs as l.out_h * l.out_w * l.out_c, and both feed xcalloc directly. A .cfg whose true dimension product exceeds INT_MAX wraps to a small or zero value, so the allocation is undersized; for example width and height of 256 with filters of 65536 gives 2^32, which wraps to 0. forward_convolutional_layer then re-derives the GEMM dimensions with a different operand order, computing k as l.size*l.size*l.c / l.groups where the allocation divided before multiplying, and reads and writes through the undersized buffer. Loading the crafted .cfg for inference or training is sufficient and no valid .weights file is required. The reported proof of concept observed a heap buffer overflow read in gemm_nn_fast under AddressSanitizer and glibc allocator metadata corruption in a release build of the same input, indicating an out-of-bounds write.

The advisory is available at github.com. This vulnerability was named CVE-2026-72852 since 08/10/2026. The exploitation appears to be easy. The attack can be initiated remotely. Successful exploitation requires user interaction by the victim. Technical details are known, but there is no available exploit. The structure of the vulnerability defines a possible price range of USD $0-$5k at the moment (estimation calculated on 08/20/2026).

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

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Productinfo

Type

• Artificial Intelligence Software

Vendor

• hank-ai

Name

• darknet

Version

• 6.0

Website

• Product: https://github.com/hank-ai/darknet/

CPE 2.3info

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CPE 2.2info

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