CVE-2014-0105 (GCVE-0-2014-0105)
Vulnerability from cvelistv5 – Published: 2014-04-15 14:00 – Updated: 2024-08-06 09:05
VLAI
EPSS
VEX
Summary
The auth_token middleware in the OpenStack Python client library for Keystone (aka python-keystoneclient) before 0.7.0 does not properly retrieve user tokens from memcache, which allows remote authenticated users to gain privileges in opportunistic circumstances via a large number of requests, related to an "interaction between eventlet and python-memcached."
Severity
No CVSS data available.
CWE
- n/a
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://bugs.launchpad.net/python-keystoneclient/… | x_refsource_CONFIRM |
| http://www.openwall.com/lists/oss-security/2014/03/27/4 | mailing-listx_refsource_MLIST |
| http://rhn.redhat.com/errata/RHSA-2014-0382.html | vendor-advisoryx_refsource_REDHAT |
| http://rhn.redhat.com/errata/RHSA-2014-0409.html | vendor-advisoryx_refsource_REDHAT |
Date Public
2014-03-27 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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