Vulnerabilities
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CVE Vulnerabilities

CVE-2019-14846

Improper Output Neutralization for Logs

Published: Oct 08, 2019 | Modified: Apr 22, 2022
CVSS 3.x
7.8
HIGH
Source:
NVD
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CVSS 2.x
2.1 LOW
AV:L/AC:L/Au:N/C:P/I:N/A:N
RedHat/V2
RedHat/V3
7.3 IMPORTANT
CVSS:3.0/AV:L/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:H
Ubuntu
LOW
Additional information
NVDhttps://nvd.nist.gov/vuln/detail/CVE-2019-14846
CWEhttps://cwe.mitre.org/data/definitions/117.html

In Ansible, all Ansible Engine versions up to ansible-engine 2.8.5, ansible-engine 2.7.13, ansible-engine 2.6.19, were logging at the DEBUG level which lead to a disclosure of credentials if a plugin used a library that logged credentials at the DEBUG level. This flaw does not affect Ansible modules, as those are executed in a separate process.

Weakness

The product does not neutralize or incorrectly neutralizes output that is written to logs.

Affected Software

Name Vendor Start Version End Version
Ansible_engine Redhat * 2.6.20 (excluding)
Ansible_engine Redhat 2.7.0 (including) 2.7.14 (excluding)
Ansible_engine Redhat 2.8.0 (including) 2.8.6 (excluding)
Red Hat Ansible Engine 2.6 for RHEL 7 RedHat ansible-0:2.6.20-1.el7ae *
Red Hat Ansible Engine 2.7 for RHEL 7 RedHat ansible-0:2.7.14-1.el7ae *
Red Hat Ansible Engine 2.8 for RHEL 7 RedHat ansible-0:2.8.6-1.el7ae *
Red Hat Ansible Engine 2.8 for RHEL 8 RedHat ansible-0:2.8.6-1.el8ae *
Red Hat Ansible Engine 2 for RHEL 7 RedHat ansible-0:2.8.6-1.el7ae *
Red Hat Ansible Engine 2 for RHEL 8 RedHat ansible-0:2.8.6-1.el8ae *
Red Hat OpenStack Platform 13.0 (Queens) RedHat ansible-0:2.6.20-1.el7ae *
Red Hat OpenStack Platform 13.0 (Queens) for RHEL 7.6 EUS RedHat ansible-0:2.6.20-1.el7ae *
Ansible Ubuntu bionic *
Ansible Ubuntu disco *
Ansible Ubuntu eoan *
Ansible Ubuntu trusty *
Ansible Ubuntu trusty/esm *
Ansible Ubuntu xenial *

Extended Description

This can allow an attacker to forge log entries or inject malicious content into logs. Log forging vulnerabilities occur when:

Potential Mitigations

  • Assume all input is malicious. Use an “accept known good” input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
  • When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, “boat” may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as “red” or “blue.”
  • Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code’s environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

References

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