BIG-IP NTLM Buffer Over-Read (before 17.0.0.1, 16.1.3.1, 15.1.6.1)
CVE-2022-33968 Published on August 4, 2022

BIG-IP LTM and APM NTLM vulnerability CVE-2022-33968
In BIG-IP Versions 17.0.x before 17.0.0.1, 16.1.x before 16.1.3.1, 15.1.x before 15.1.6.1, 14.1.x before 14.1.5.1, and all versions of 13.1.x, when an LTM monitor or APM SSO is configured on a virtual server, and NTLM challenge-response is in use, undisclosed traffic can cause a buffer over-read. Note: Software versions which have reached End of Technical Support (EoTS) are not evaluated.

NVD

Vulnerability Analysis

CVE-2022-33968 is exploitable with network access, and does not require authorization privileges or user interaction. This vulnerability is consided to have a high level of attack complexity. The potential impact of an exploit of this vulnerability is considered to have a small impact on confidentiality, a small impact on integrity and availability.

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

Weakness Type

Out-of-bounds Read

The software reads data past the end, or before the beginning, of the intended buffer. Typically, this can allow attackers to read sensitive information from other memory locations or cause a crash. A crash can occur when the code reads a variable amount of data and assumes that a sentinel exists to stop the read operation, such as a NUL in a string. The expected sentinel might not be located in the out-of-bounds memory, causing excessive data to be read, leading to a segmentation fault or a buffer overflow. The software may modify an index or perform pointer arithmetic that references a memory location that is outside of the boundaries of the buffer. A subsequent read operation then produces undefined or unexpected results.


Products Associated with CVE-2022-33968

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Affected Versions

F5 BIG-IP:

Exploit Probability

EPSS
0.31%
Percentile
53.98%

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.