# PYSEC-2019-38 - ** DISPUTED ** An issue was discovered in NumPy 1.16.0 and earlier. It uses the pickle Python module…

Source: https://junglewise.ai/threats/pysec-2019-38-disputed-an-issue-was-discovered-in-numpy-1-16-0-and-92c3370e  
Publisher: Junglewise Threat Intelligence, https://junglewise.ai/threats  
Published: 2019-01-16  
License: CC BY 4.0 with a link back

Severity: info · Published 2019-01-16

** DISPUTED **   An issue was discovered in NumPy 1.16.0 and earlier. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is  a behavior that might have legitimate applications in (for example)  loading serialized Python object arrays from trusted and authenticated  sources.

Technologies: [numpy (PyPI)](https://junglewise.ai/threats/technologies/numpy). Vendors: [PyPI](https://junglewise.ai/threats/vendors/pypi).

## Quick answers

**Is This vulnerability exploited in the wild?** No. Junglewise Threat Intelligence has no report of This vulnerability being exploited in the wild.

**How severe is This vulnerability?** Informational severity, published 16 January 2019.

**Which products and versions are affected?** numpy (PyPI) ECOSYSTEM:introduced=0,fixed=1.16.1.

**Is there a fix for This vulnerability?** Yes. numpy (PyPI): upgrade to 1.16.1 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

**Am I affected?** Check whether you run numpy (PyPI) 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.

## How to fix

- numpy (PyPI): upgrade to 1.16.1 or later

  ```sh
  pip install "numpy>=1.16.1"
  ```


## Affected products

- numpy (PyPI) ECOSYSTEM:introduced=0,fixed=1.16.1

## Related threats

- [NumPy insecure deserialization in numpy.load](https://junglewise.ai/threats/cve-2019-6446-numpy-insecure-deserialization-in-numpy-load)
- [Buffer Copy without Checking Size of Input in NumPy](https://junglewise.ai/threats/cve-2021-41496-buffer-copy-without-checking-size-of-input-in-numpy)
- [NumPy NULL Pointer Dereference](https://junglewise.ai/threats/cve-2021-41495-numpy-null-pointer-dereference)
- [Incorrect Comparison in NumPy](https://junglewise.ai/threats/cve-2021-34141-incorrect-comparison-in-numpy)
- [NumPy Buffer Overflow (Disputed)](https://junglewise.ai/threats/cve-2021-33430-numpy-buffer-overflow-disputed)