# CVE-2026-42627: Arm ArmNN integer overflow in TensorShape::GetNumElements

Source: https://junglewise.ai/threats/cve-2026-42627-arm-armnn-integer-overflow-in-tensorshape-getnumelements  
Publisher: Junglewise Threat Intelligence, https://junglewise.ai/threats  
Published: 2026-05-22. Updated: 2026-05-26  
License: CC BY 4.0 with a link back

CVE-2026-42627 · Severity: medium · CVSS 6.2 · Published 2026-05-22

ArmNN is a software library used to accelerate machine learning on ARM-based devices. A vulnerability in how it processes certain model files could allow an attacker to crash an application or cause it to behave unexpectedly by providing a specially crafted TFLite model. This could impact the reliability and availability of services relying on machine learning inference.

Vendors: [Arm](https://junglewise.ai/threats/vendors/arm).

## Quick answers

**Is CVE-2026-42627 exploited in the wild?** No. Junglewise Threat Intelligence has no report of CVE-2026-42627 being exploited in the wild.

**How severe is CVE-2026-42627?** Medium severity, with a CVSS score of 6.2, published 22 May 2026.

**Which products and versions are affected?** ArmNN through 2026-03-27.

**Is there a fix for CVE-2026-42627?** No fixed version is recorded yet. Check the vendor's advisory in the references below. If you run it, Junglewise drafts a mitigation that fits your setup and applies it once you approve, with senior security engineers behind it.

**How is CVE-2026-42627 attacked?** It is attacked with local access, in a software library.

**Am I affected by CVE-2026-42627?** Check whether you run ArmNN at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

## Technical details

An integer overflow vulnerability exists in TensorShape::GetNumElements() within armnn/Tensor.cpp. The flaw occurs when multiplying tensor dimensions using 32-bit unsigned arithmetic without sufficient overflow detection. This causes GetNumBytes() to return an understated allocation size, leading to a heap-based buffer over-read during the model optimization phase, specifically within the BatchToSpaceNdLayer during the Optimize()->InferOutputShapes() call. An attacker can exploit this by providing a malicious TFLite model file. The vulnerability is triggered locally and can lead to a denial of service (application crash).

## Affected products

- Arm ArmNN through 2026-03-27

## Timeline

- 2026-05-22: disclosed
- 2026-05-22: advisory

## References

- [https://github.com/ARM-software/armnn/blob/main/src/armnn/Tensor.cpp](https://github.com/ARM-software/armnn/blob/main/src/armnn/Tensor.cpp)
- [https://github.com/ARM-software/armnn/blob/main/src/armnnTfLiteParser/TfLiteParser.cpp](https://github.com/ARM-software/armnn/blob/main/src/armnnTfLiteParser/TfLiteParser.cpp)