CVE-2026-72852: Software Security Vulnerability Vulnerability

HIGH
Advisory Identifier: GHSA-5277-mwh4-q4cc
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CVSS 7.8
CWE-190
Published
Advisory Summary

CVE-2026-72852 is a HIGH (CVSS 7.8) security vulnerability vulnerability (CWE-190: Integer Overflow or Wraparound) affecting Software libraries in the Maven ecosystem. The weakness occurs when 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.. Remediation is available in the latest vendor maintenance releases.

CVE-2026-72852 at a Glance

CVE Identifier CVE-2026-72852
GHSA Identifier GHSA-5277-mwh4-q4cc
Severity HIGH
CVSS v3.1 Base Score 7.8
CWE Classification CWE-190: Integer Overflow or Wraparound
Affected Product Software
Package Ecosystem Maven
Published Date
Last Updated

Security Impact

CVSS: 7.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H).

Attack Vector Local (AV:L)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction Required (UI:R)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2026-72852

To remediate this vulnerability, upgrade all affected Software dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

mvn dependency:tree

How to Check if You Are Affected

To determine whether your Java application is affected by CVE-2026-72852, inspect your build dependencies using the Maven Dependency Plugin:

mvn dependency:tree

Analyze the terminal output to locate any version of Software in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than the patched release), your application is affected.

Note: The mvn dependency:tree command inspects the resolved dependency graph declared in your project's POM files; it does not perform automated security scanning or inspect runtime dynamic classpaths. Always verify runtime container classpaths and shaded JARs.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-190: Integer Overflow or Wraparound, where 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. In Software, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

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.

References

NVD — CVE-2026-72852 NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-72852
Software Source Repository REPOSITORY
https://github.com/hank-ai/darknet/issues/148
Software Source Repository REPOSITORY
https://github.com/hank-ai/darknet
Software Source Repository REPOSITORY
https://github.com/hank-ai/darknet/blob/v6.0/src-lib/convolutional_layer.cpp#L1457
Software Source Repository REPOSITORY
https://github.com/hank-ai/darknet/blob/v6.0/src-lib/convolutional_layer.cpp#L764
Software Source Repository REPOSITORY
https://github.com/hank-ai/darknet/blob/v6.0/src-lib/convolutional_layer.cpp#L811
www.vulncheck.com/advisories/darknet-... WEB
https://www.vulncheck.com/advisories/darknet-integer-overflow-in-convolutional-layer-buffer-sizing-leads-to-heap-buffer-overflow

Frequently Asked Questions

What is CVE-2026-72852?
CVE-2026-72852 is a security vulnerability in Software classified as a security vulnerability vulnerability under CWE-190: Integer Overflow or Wraparound.
Which Software versions are affected?
Affected versions include releases prior to current release patches.
What version fixes CVE-2026-72852?
Upgrading to current release patches (or the latest patched release for your respective branch) resolves the vulnerability.
What is the CVSS score of CVE-2026-72852?
CVE-2026-72852 has a CVSS v3.1 base score of 7.8 (HIGH) with vector string CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2026-72852?
CVE-2026-72852 is classified under CWE-190: Integer Overflow or Wraparound (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.).
How can I check Maven dependencies for CVE-2026-72852?
Run the dependency tree command: 'mvn dependency:tree'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-5277-mwh4-q4cc",
  "modified" : "2026-08-20T21:31:28Z",
  "published" : "2026-08-20T21:31:28Z",
  "aliases" : [ "CVE-2026-72852" ],
  "details" : "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.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X"
  } ],
  "affected" : [ ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-72852"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/hank-ai/darknet/issues/148"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/hank-ai/darknet"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/hank-ai/darknet/blob/v6.0/src-lib/convolutional_layer.cpp#L1457"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/hank-ai/darknet/blob/v6.0/src-lib/convolutional_layer.cpp#L764"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/hank-ai/darknet/blob/v6.0/src-lib/convolutional_layer.cpp#L811"
  }, {
    "type" : "WEB",
    "url" : "https://www.vulncheck.com/advisories/darknet-integer-overflow-in-convolutional-layer-buffer-sizing-leads-to-heap-buffer-overflow"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-190" ],
    "severity" : "HIGH",
    "github_reviewed" : false,
    "github_reviewed_at" : null,
    "nvd_published_at" : "2026-08-20T19:17:00Z"
  }
}