Vulnerability-Lookup

GSD-2021-41766

Vulnerability from gsd - Updated: 2023-12-13 01:23

Details

Apache Karaf allows monitoring of applications and the Java runtime by using the Java Management Extensions (JMX). JMX is a Java RMI based technology that relies on Java serialized objects for client server communication. Whereas the default JMX implementation is hardened against unauthenticated deserialization attacks, the implementation used by Apache Karaf is not protected against this kind of attack. The impact of Java deserialization vulnerabilities strongly depends on the classes that are available within the targets class path. Generally speaking, deserialization of untrusted data does always represent a high security risk and should be prevented. The risk is low as, by default, Karaf uses a limited set of classes in the JMX server class path. It depends of system scoped classes (e.g. jar in the lib folder).

Aliases

CVE-2021-41766

Aliases

CVE-2021-41766

JSON

To clipboard

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    "description": "Apache Karaf allows monitoring of applications and the Java runtime by using the Java Management Extensions (JMX). JMX is a Java RMI based technology that relies on Java serialized objects for client server communication. Whereas the default JMX implementation is hardened against unauthenticated deserialization attacks, the implementation used by Apache Karaf is not protected against this kind of attack. The impact of Java deserialization vulnerabilities strongly depends on the classes that are available within the targets class path. Generally speaking, deserialization of untrusted data does always represent a high security risk and should be prevented. The risk is low as, by default, Karaf uses a limited set of classes in the JMX server class path. It depends of system scoped classes (e.g. jar in the lib folder).",
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}

CVE-2021-41766 (GCVE-0-2021-41766)

Vulnerability from cvelistv5 – Published: 2022-01-26 11:10 – Updated: 2024-08-04 03:15

Title

Insecure Java Deserialization in Apache Karaf

Summary

Severity

No CVSS data available.

CWE

Insecure Java Deserialization

Assigner

apache CNA under the mitre root

CNA scorecard B 76/100 over 1170 records in the last 180 days details

References

1 reference

URL	Tags
https://karaf.apache.org/security/cve-2021-41766.txt	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
Apache Software Foundation	Apache Karaf	Affected: Apache Karaf , < 4.3.6 (custom)

Credits

This issue was reported by Daniel Heyne, Konstantin Samuel and Tobias Neitzel.

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

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