CVE-2026-72852
Received Received - Intake

Heap Buffer Overflow in Darknet Due to Integer Overflow

Vulnerability report for CVE-2026-72852, including description, CVSS score, EPSS score, affected products, exploitability, helpful resources, and attack-flow context.

Publication date: 2026-08-20

Last updated on: 2026-08-20

Assigner: VulnCheck

Description

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.

CVSS Scores

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Meta Information

Published
2026-08-20
Last Modified
2026-08-20
Generated
2026-08-20
AI Q&A
2026-08-20
EPSS Evaluated
N/A
NVD
EUVD

Affected Vendors & Products

Showing 2 associated CPEs
Vendor Product Version / Range
hank-ai darknet to 6.0 (inc)
hank-ai darknet *

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-787 The product writes data past the end, or before the beginning, of the intended buffer.
CWE-190 The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.

Attack-Flow Graph

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Executive Summary

This vulnerability is an integer overflow in the Darknet framework's convolutional layer buffer sizing. When a .cfg file contains excessively large dimension values (e.g., filters=65536, width=256, height=256), 32-bit integer arithmetic wraps around to zero or a small value due to exceeding INT_MAX. This causes undersized heap allocations via xcalloc. During processing, the layer recalculates dimensions differently, leading to out-of-bounds reads and writes.

Detection Guidance

To detect this vulnerability, monitor for crashes or memory corruption errors when processing crafted .cfg files in Darknet. Use AddressSanitizer (ASan) during compilation to catch heap buffer overflows. Check for segmentation faults or glibc allocator metadata corruption during inference or training with suspicious .cfg inputs.

Impact Analysis

This vulnerability can lead to heap corruption, crashes, or arbitrary code execution. Attackers can exploit it by providing a specially crafted .cfg file to trigger buffer overflows. This may cause denial-of-service, data corruption, or potential remote code execution if the vulnerable software processes untrusted input.

Compliance Impact

This vulnerability could lead to unauthorized data access or corruption, which may violate GDPR's integrity and confidentiality principles or HIPAA's security requirements for protected health information. Exploitation risks include data breaches or integrity violations due to heap buffer overflows.

Mitigation Strategies

Update Darknet to a patched version that uses larger integer types (size_t or int64_t) for buffer size calculations. Validate configuration values against INT_MAX before allocation. Standardize buffer size formulas to prevent discrepancies between allocation and forward-pass calculations.

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