common.py in Paramiko 1.7.1 and earlier, when using threads or forked processes, does not properly use RandomPool, which allows one session to obtain sensitive information from another session by predicting the state of the pool.

There are packages installed that are affected by a vulnerability referenced in the following CVE:

  - common.py in Paramiko 1.7.1 and earlier, when using threads or forked processes, does not properly use
    RandomPool, which allows one session to obtain sensitive information from another session by predicting
    the state of the pool. (CVE-2008-0299)

The remote host is affected by the vulnerability described in GLSA-200803-07 (Paramiko: Information disclosure)

    Dwayne C. Litzenberger reported that the file 'common.py' does not     properly use RandomPool when using threads or forked processes.
  Impact :

    A remote attacker could predict the values generated by applications     using Paramiko for encryption purposes, potentially gaining access to     sensitive information.
  Workaround :

    There is no known workaround at this time.

Apply patch to fix recently discovered security problem.

Note that Tenable Network Security has extracted the preceding description block directly from the Fedora security advisory. Tenable has attempted to automatically clean and format it as much as possible without introducing additional issues.

ID	Name	Product	Family	Type	Severity
433661	SCA: security update for paramiko (GHSA-wqmm-q65g-2hqr)	Tenable Cloud Security	SCA Checks	Local	high
433661	SCA: security update for paramiko (GHSA-wqmm-q65g-2hqr)	Tenable Self-Hosted Container Security	SCA Checks	Local	high
31382	GLSA-200803-07 : Paramiko: Information disclosure	Nessus	Gentoo Local Security Checks	Local	medium
29989	Fedora 7 : python-paramiko-1.7.1-3.fc7 (2008-0722)	Nessus	Fedora Local Security Checks	Local	medium
29987	Fedora 8 : python-paramiko-1.7.1-3.fc8 (2008-0644)	Nessus	Fedora Local Security Checks	Local	medium

Detections

Analytics

CVE-2008-0299

high

Tenable Plugins

high

high

medium

medium

medium