CVE-2021-45083
Python vulnerability analysis and mitigation

Overview

A security vulnerability was discovered in Cobbler before version 3.3.1, identified as CVE-2021-45083. The issue involves world-readable files in /etc/cobbler directory that contain sensitive information. Two specific files, users.digest and settings.yaml, could expose sensitive data to local users with non-privileged access to the server (CVE, OpenWall).

Technical details

The vulnerability affects two critical configuration files: users.digest, which contains SHA2-512 digests of users in a Cobbler local installation, and settings.yaml, which contains secrets such as the hashed default password. Both files were configured with world-readable permissions, making them accessible to any local user on the system. The vulnerability has been assigned a CVSS score of 8.4 (CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:N) (OpenWall).

Impact

The vulnerability could allow local users with non-privileged access to obtain sensitive information. In cases where passwords are easy to guess, attackers could potentially obtain plaintext credentials from the SHA2-512 hashes stored in users.digest. Additionally, the exposure of settings.yaml could reveal other system secrets including the hashed default password (CVE).

Mitigation and workarounds

The issue was fixed in Cobbler version 3.3.1. A temporary workaround for affected systems is to manually modify the file permissions as root: chmod go-r /etc/cobbler/users.digest and chmod go-r /etc/cobbler/settings.yaml. The permanent fix was implemented through a commit that properly restricts file permissions (OpenWall, GitHub).

Community reactions

The vulnerability was addressed in multiple Linux distributions including Fedora, which released security updates to address both CVE-2021-45083 and related vulnerability CVE-2021-45082. The fixes were included in package versions cobbler-3.2.2-10 for Fedora 34 and 35, and cobbler-3.3.1-1 for Fedora 36 (Fedora).

Additional resources


SourceThis report was generated using AI

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