CVE-2024-4812 (GCVE-0-2024-4812)
Vulnerability from cvelistv5 – Published: 2024-06-05 15:06 – Updated: 2025-11-20 19:15
VLAI
EPSS
VEX
Title
Katello: potential cross-site scripting exploit in ui
Summary
A flaw was found in the Katello plugin for Foreman, where it is possible to store malicious JavaScript code in the "Description" field of a user. This code can be executed when opening certain pages, for example, Host Collections.
Severity
4.8 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-13 20:16 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://access.redhat.com/security/cve/CVE-2024-4812 | vdb-entryx_refsource_REDHAT |
| https://bugzilla.redhat.com/show_bug.cgi?id=2280187 | issue-trackingx_refsource_REDHAT |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Red Hat | Red Hat Satellite 6 |
cpe:/a:redhat:satellite:6
|
Date Public
2024-06-05 00:00
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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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
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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.
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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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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.