Vulnerability-Lookup

GSD-2022-28157

Vulnerability from gsd - Updated: 2023-12-13 01:19

Details

Jenkins Pipeline: Phoenix AutoTest Plugin 1.3 and earlier allows attackers with Item/Configure permission to upload arbitrary files from the Jenkins controller via FTP to an attacker-specified FTP server.

Aliases

CVE-2022-28157

Aliases

CVE-2022-28157

JSON

To clipboard

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    "description": "Jenkins Pipeline: Phoenix AutoTest Plugin 1.3 and earlier allows attackers with Item/Configure permission to upload arbitrary files from the Jenkins controller via FTP to an attacker-specified FTP server.",
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CVE-2022-28157 (GCVE-0-2022-28157)

Vulnerability from cvelistv5 – Published: 2022-03-29 12:31 – Updated: 2024-08-03 05:48

Summary

Severity

No CVSS data available.

Assigner

jenkins mitre root

References

2 references

URL	Tags
https://www.jenkins.io/security/advisory/2022-03-…	x_refsource_CONFIRM
http://www.openwall.com/lists/oss-security/2022/03/29/1	mailing-listx_refsource_MLIST

Impacted products

1 product

Vendor	Product	Version
Jenkins project	Jenkins Pipeline: Phoenix AutoTest Plugin	Affected: unspecified , ≤ 1.3 (custom) Unknown: next of 1.3 , < unspecified (custom)

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.

Detection rules are retrieved from Rulezet.

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.