Vulnerability-Lookup

GSD-2021-37694

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

Details

@asyncapi/java-spring-cloud-stream-template generates a Spring Cloud Stream (SCSt) microservice. In versions prior to 0.7.0 arbitrary code injection was possible when an attacker controls the AsyncAPI document. An example is provided in GHSA-xj6r-2jpm-qvxp. There are no mitigations available and all users are advised to update.

Aliases

CVE-2021-37694

Aliases

CVE-2021-37694

JSON

To clipboard

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}

CVE-2021-37694 (GCVE-0-2021-37694)

Vulnerability from cvelistv5 – Published: 2021-08-11 17:25 – Updated: 2024-08-04 01:23

Title

Code injection issue for java-spring-cloud-stream-template

Summary

Severity

8.7 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:C/C:H/I:H/A:N

CWE

CWE-94 - Improper Control of Generation of Code ('Code Injection')

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7994 records in the last 180 days details

References

1 reference

URL	Tags
https://github.com/asyncapi/java-spring-cloud-str…	x_refsource_CONFIRM

Impacted products

1 product

Vendor	Product	Version
asyncapi	java-spring-cloud-stream-template	Affected: < 0.7.0

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.

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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.

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