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CVE Scan for confluentinc/cp-kafka-connect:7.9.2-1-ubi8.arm64

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23 Known Vulnerabilities in this Docker Image

0
Critical
10
High
11
Medium
2
Low
0
Info/ Unspecified/ Unknown
CVE IDSeverityPackageAffected VersionFixed VersionCVSS Score
CVE-2025-66471highpkg:pypi/urllib3@2.4.0>=1.0,<2.6.02.6.08.9

Impact

urllib3's streaming API is designed for the efficient handling of large HTTP responses by reading the content in chunks, rather than loading the entire response body into memory at once.

When streaming a compressed response, urllib3 can perform decoding or decompression based on the HTTP Content-Encoding header (e.g., gzip, deflate, br, or zstd). The library must read compressed data from the network and decompress it until the requested chunk size is met. Any resulting decompressed data that exceeds the requested amount is held in an internal buffer for the next read operation.

The decompression logic could cause urllib3 to fully decode a small amount of highly compressed data in a single operation. This can result in excessive resource consumption (high CPU usage and massive memory allocation for the decompressed data; CWE-409) on the client side, even if the application only requested a small chunk of data.

Affected usages

Applications and libraries using urllib3 version 2.5.0 and earlier to stream large compressed responses or content from untrusted sources.

stream(), read(amt=256), read1(amt=256), read_chunked(amt=256), readinto(b) are examples of urllib3.HTTPResponse method calls using the affected logic unless decoding is disabled explicitly.

Remediation

Upgrade to at least urllib3 v2.6.0 in which the library avoids decompressing data that exceeds the requested amount.

If your environment contains a package facilitating the Brotli encoding, upgrade to at least Brotli 1.2.0 or brotlicffi 1.2.0.0 too. These versions are enforced by the urllib3[brotli] extra in the patched versions of urllib3.

Credits

The issue was reported by @Cycloctane. Supplemental information was provided by @stamparm during a security audit performed by 7ASecurity and facilitated by OSTIF.

Relevance:

The CVE-2025-66471 is relevant if the Kafka Connect container interacts with external systems or processes untrusted data, as it involves a vulnerability in data parsing. It becomes critical in environments where attackers could exploit this flaw to execute arbitrary code or cause a denial of service. Otherwise, its impact is limited in isolated or controlled setups. (Note: Relevance analysis is automatically generated and may require verification.)

Package URL(s):
  • pkg:pypi/urllib3@2.4.0
CVE-2025-66418highpkg:pypi/urllib3@2.4.0>=1.24,<2.6.02.6.08.9
CVE-2025-48734highcommons-beanutils>=1.0,<=1.10.11.11.08.8
CVE-2022-40897highpkg:pypi/setuptools@39.2.0<65.5.165.5.18.7
CVE-2019-20916highpkg:pypi/pip@9.0.3<19.219.28.7
CVE-2025-55163highnetty-codec-http2<=4.1.123.Final4.1.124.Final8.2
CVE-2025-5115highhttp2-common>=9.3.0,<=9.4.579.4.587.7
CVE-2025-47273highpkg:pypi/setuptools@39.2.0<78.1.178.1.17.7
CVE-2024-6345highpkg:pypi/setuptools@39.2.0<70.0.070.0.07.5
CVE-2021-3572highpkg:pypi/pip@20.2.4<21.121.17.1

Severity Levels

Exploitation could lead to severe consequences, such as system compromise or data loss. Requires immediate attention.

Vulnerability could be exploited relatively easily and lead to significant impact. Requires prompt attention.

Exploitation is possible but might require specific conditions. Impact is moderate. Should be addressed in a timely manner.

Exploitation is difficult or impact is minimal. Address when convenient or as part of regular maintenance.

Severity is not determined, informational, or negligible. Review based on context.

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