Numpy up to 1.16.0 Pickle Python Serialized Object deserialization ⚔ [Disputed]

Summaryinfo

A vulnerability, which was classified as critical, was found in Numpy up to 1.16.0. The impacted element is an unknown function of the component Pickle Python Module. Executing a manipulation as part of Serialized Object can lead to deserialization. This vulnerability is handled as CVE-2019-6446. The attack can be executed remotely. There is not any exploit available. The existence of this vulnerability is still disputed at present.

Detailsinfo

A vulnerability was found in Numpy up to 1.16.0. It has been declared as critical. This vulnerability affects some unknown functionality of the component Pickle Python Module. The manipulation as part of a Serialized Object leads to a deserialization vulnerability. The CWE definition for the vulnerability is CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:

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.

The bug was discovered 01/16/2019. The weakness was released 01/16/2019 (Website). The advisory is shared for download at securityfocus.com. This vulnerability was named CVE-2019-6446 since 01/15/2019. The exploitation appears to be easy. The attack can be initiated remotely. No form of authentication is required for a successful exploitation. There are neither technical details nor an exploit publicly available.

The real existence of this vulnerability is still doubted at the moment. The commercial vulnerability scanner Qualys is able to test this issue with plugin 172117 (OpenSUSE Security Update for python-numpy (openSUSE-SU-2019:0245-1)).

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

The vulnerability is also documented in the vulnerability database at SecurityFocus (BID 106670†). Once again VulDB remains the best source for vulnerability data.

Productinfo

Name

• Numpy

Version

• 1.0
• 1.1
• 1.2
• 1.3
• 1.4
• 1.5
• 1.6
• 1.7
• 1.8
• 1.9
• 1.10
• 1.11
• 1.12
• 1.13
• 1.14
• 1.15
• 1.16.0

CPE 2.3info

• 🔍
• 🔍
• 🔍

CPE 2.2info

• 🔍
• 🔍
• 🔍

CVSSv4info

CVSSv3info

CVSSv2info

Exploitinginfo

Threat Intelligenceinfo

Countermeasuresinfo

Timelineinfo

Sourcesinfo

Entryinfo

Once again VulDB remains the best source for vulnerability data.

Discussion