CVE-2023-22942 (GCVE-0-2023-22942)
Vulnerability from cvelistv5 – Published: 2023-02-14 17:22 – Updated: 2025-02-28 11:03
VLAI
EPSS
VEX
Title
Cross-Site Request Forgery in the ‘ssg/kvstore_client’ REST Endpoint in Splunk Enterprise
Summary
In Splunk Enterprise versions below 8.1.13, 8.2.10, and 9.0.4, a cross-site request forgery in the Splunk Secure Gateway (SSG) app in the ‘kvstore_client’ REST endpoint lets a potential attacker update SSG KV store collections using an HTTP GET request.
Severity
5.4 (Medium)
CWE
- CWE-352 - The web application does not, or can not, sufficiently verify whether a well-formed, valid, consistent request was intentionally provided by the user who submitted the request.
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Splunk | Splunk Enterprise |
Affected:
8.1 , < 8.1.13
(custom)
Affected: 8.2 , < 8.2.10 (custom) Affected: 9.0 , < 9.0.4 (custom) |
guessed |
Date Public
2023-02-14 00:00
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
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.
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.
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