CVE-2021-4294 (GCVE-0-2021-4294)
Vulnerability from cvelistv5 – Published: 2022-12-28 16:51 – Updated: 2024-08-03 17:23
VLAI
EPSS
VEX
Title
OpenShift OSIN CheckClientSecret timing discrepancy
Summary
A vulnerability was found in OpenShift OSIN. It has been classified as problematic. This affects the function ClientSecretMatches/CheckClientSecret. The manipulation of the argument secret leads to observable timing discrepancy. The name of the patch is 8612686d6dda34ae9ef6b5a974e4b7accb4fea29. It is recommended to apply a patch to fix this issue. The associated identifier of this vulnerability is VDB-216987.
Severity
CWE
- CWE-208 - Observable Timing Discrepancy
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.216987 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.216987 | signaturepermissions-required |
| https://github.com/openshift/osin/pull/200 | issue-tracking |
| https://github.com/openshift/osin/commit/8612686d… | patch |
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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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