Apple iCloud OOB Read in iCloud Windows/Tiff, fixed 11.4/7.21
CVE-2020-36521 Published on September 23, 2022

An out-of-bounds read was addressed with improved input validation. This issue is fixed in iCloud for Windows 11.4, iOS 14.0 and iPadOS 14.0, watchOS 7.0, tvOS 14.0, iCloud for Windows 7.21, iTunes for Windows 12.10.9. Processing a maliciously crafted tiff file may lead to a denial-of-service or potentially disclose memory contents.

NVD

Vulnerability Analysis

CVE-2020-36521 can be exploited with local system access, requires user interaction. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have a high impact on confidentiality, with no impact on integrity, and a high impact on availability.

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

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-2020-36521

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Affected Versions

Apple iTunes for Windows: Apple iOS and iPadOS: Apple iCloud for Windows: Apple iCloud for Windows: Apple watchOS: Apple watchOS:

Exploit Probability

EPSS
0.14%
Percentile
34.41%

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.