Python <3.9.16/3.10.9 Forkserver MP LDPE via abstract sockets
CVE-2022-42919 Published on November 7, 2022

Python 3.9.x before 3.9.16 and 3.10.x before 3.10.9 on Linux allows local privilege escalation in a non-default configuration. The Python multiprocessing library, when used with the forkserver start method on Linux, allows pickles to be deserialized from any user in the same machine local network namespace, which in many system configurations means any user on the same machine. Pickles can execute arbitrary code. Thus, this allows for local user privilege escalation to the user that any forkserver process is running as. Setting multiprocessing.util.abstract_sockets_supported to False is a workaround. The forkserver start method for multiprocessing is not the default start method. This issue is Linux specific because only Linux supports abstract namespace sockets. CPython before 3.9 does not make use of Linux abstract namespace sockets by default. Support for users manually specifying an abstract namespace socket was added as a bugfix in 3.7.8 and 3.8.3, but users would need to make specific uncommon API calls in order to do that in CPython before 3.9.

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Vulnerability Analysis

CVE-2022-42919 can be exploited with local system access, and requires small amount of user privileges. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to be very high.

Attack Vector:
LOCAL
Attack Complexity:
LOW
Privileges Required:
LOW
User Interaction:
NONE
Scope:
UNCHANGED
Confidentiality Impact:
HIGH
Integrity Impact:
HIGH
Availability Impact:
HIGH

Weakness Type

What is a Marshaling, Unmarshaling Vulnerability?

The application deserializes untrusted data without sufficiently verifying that the resulting data will be valid.

CVE-2022-42919 has been classified to as a Marshaling, Unmarshaling vulnerability or weakness.


Products Associated with CVE-2022-42919

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Exploit Probability

EPSS
0.03%
Percentile
9.98%

EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.