library/glob.html in the Python 2 and 3 documentation before 2016 has potentially misleading information about whether sorting occurs, as demonstrated by irreproducible cancer-research results. NOTE: the effects of this documentation cross application domains, and thus it is likely that security-relevant code elsewhere is affected. This issue is not a Python implementation bug, and there are no reports that NMR researchers were specifically relying on library/glob.html. In other words, because the older documentation stated "finds all the pathnames matching a specified pattern according to the rules used by the Unix shell," one might have incorrectly inferred that the sorting that occurs in a Unix shell also occurred for glob.glob. There is a workaround in newer versions of Willoughby nmr-data_compilation-p2.py and nmr-data_compilation-p3.py, which call sort() directly.
This vulnerability carries a HIGH severity rating with a CVSS v3.1 score of 7.5, indicating it can be exploited remotely over the network with relatively low complexity without requiring user interaction and does not require pre-existing privileges . The vulnerability impacts integrity (unauthorized modifications), for affected systems. Impacting 1 product from python organizations running these solutions should prioritize assessment and patching.
First disclosed in 2019, this vulnerability was reported during a period defined by widespread IoT adoption challenges, mobile security concerns, and the emergence of advanced persistent threat (APT) techniques. Contemporary mitigation strategies focused on secure development practices and third-party component vetting.
2019-10-12T13:15:10.790
2024-11-21T04:32:25.357
Modified
CVSSv3.1: 7.5 (HIGH)
AV:N/AC:L/Au:N/C:N/I:P/A:N
10.0
2.9
| Type | Vendor | Product | Version/Range | Vulnerable? |
|---|---|---|---|---|
| Application | python | python | 3.6.0 | Yes |
| Application | python | python | 3.7.0 | Yes |
| Application | python | python | 3.8.0 | Yes |
SecUtils normalizes and enriches National Vulnerability Database (NVD) records by standardizing vendor and product identifiers, aggregating vulnerability metadata from both NVD and MITRE sources, and providing structured context for security teams. For python's affected products, we extract Common Platform Enumeration (CPE) data, Common Weakness Enumeration (CWE) classifications, CVSS severity metrics, and reference data to enable rapid vulnerability prioritization and asset correlation. This record contains no exploit code, proof-of-concept instructions, or attack methodologies—only defensive intelligence necessary for patch management, risk assessment, and security operations.