Vulnerability-Lookup

GSD-2023-25504

Vulnerability from gsd - Updated: 2023-12-13 01:20

Details

A malicious actor who has been authenticated and granted specific permissions in Apache Superset may use the import dataset feature in order to conduct Server-Side Request Forgery attacks and query internal resources on behalf of the server where Superset is deployed. This vulnerability exists in Apache Superset versions up to and including 2.0.1.

Aliases

CVE-2023-25504

Aliases

CVE-2023-25504

JSON

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{
  "GSD": {
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    "id": "GSD-2023-25504"
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}

CVE-2023-25504 (GCVE-0-2023-25504)

Vulnerability from cvelistv5 – Published: 2023-04-17 16:29 – Updated: 2025-02-13 16:44

Title

Apache Superset: Possible SSRF on import datasets

Summary

Severity

4.9 (Medium)


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

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-10-21 15:07 UTC

CWE

CWE-918 - Server-Side Request Forgery (SSRF)

Assigner

apache CNA under the mitre root

CNA scorecard B 76/100 over 1178 records in the last 180 days details

References

2 references

URL	Tags
https://lists.apache.org/thread/tdnzkocfsqg2sbbor…	vendor-advisory
http://www.openwall.com/lists/oss-security/2023/04/18/8

Impacted products

1 product

Vendor	Product	Version
Apache Software Foundation	Apache Superset	Affected: 0 , ≤ 2.0.1 (semver)

Credits

Alexey Sabadash, VK

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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