** DISPUTED ** pandas through 1.0.3 can unserialize and execute commands from an untrusted file that is passed to the read_pickle() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the read_pickle() function is documented as unsafe and it is the user's responsibility to use the function in a secure manner.
CVE-2020-13091 - High Severity Vulnerability
Vulnerable Library - pandas-0.24.2-cp27-cp27mu-manylinux1_x86_64.whl
Powerful data structures for data analysis, time series, and statistics
Library home page: https://files.pythonhosted.org/packages/db/83/7d4008ffc2988066ff37f6a0bb6d7b60822367dcb36ba5e39aa7801fda54/pandas-0.24.2-cp27-cp27mu-manylinux1_x86_64.whl
Dependency Hierarchy: - :x: **pandas-0.24.2-cp27-cp27mu-manylinux1_x86_64.whl** (Vulnerable Library)
Vulnerability Details
** DISPUTED ** pandas through 1.0.3 can unserialize and execute commands from an untrusted file that is passed to the read_pickle() function, if __reduce__ makes an os.system call. NOTE: third parties dispute this issue because the read_pickle() function is documented as unsafe and it is the user's responsibility to use the function in a secure manner.
Publish Date: 2020-05-15
URL: CVE-2020-13091
CVSS 3 Score Details (9.8)
Base Score Metrics: - Exploitability Metrics: - Attack Vector: Network - Attack Complexity: Low - Privileges Required: None - User Interaction: None - Scope: Unchanged - Impact Metrics: - Confidentiality Impact: High - Integrity Impact: High - Availability Impact: High
For more information on CVSS3 Scores, click here.Step up your Open Source Security Game with WhiteSource here