CVE-2017-16858 (GCVE-0-2017-16858)
Vulnerability from cvelistv5 – Published: 2018-01-31 14:00 – Updated: 2024-09-17 00:40
VLAI
EPSS
VEX
Summary
The 'crowd-application' plugin module (notably used by the Google Apps plugin) in Atlassian Crowd from version 1.5.0 before version 3.1.2 allowed an attacker to impersonate a Crowd user in REST requests by being able to authenticate to a directory bound to an application using the feature. Given the following situation: the Crowd application is bound to directory 1 and has a user called admin and the Google Apps application is bound to directory 2, which also has a user called admin, it was possible to authenticate REST requests using the credentials of the user coming from directory 2 and impersonate the user from directory 1.
Severity
No CVSS data available.
CWE
- CWE-863 - Incorrect Authorization (CWE-863)
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://jira.atlassian.com/browse/CWD-5009 | x_refsource_CONFIRM |
Impacted products
Date Public
2018-01-30 00:00
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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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