CVE-2017-15713 (GCVE-0-2017-15713)
Vulnerability from cvelistv5 – Published: 2018-01-19 17:00 – Updated: 2024-09-17 04:08
VLAI
EPSS
VEX
Summary
Vulnerability in Apache Hadoop 0.23.x, 2.x before 2.7.5, 2.8.x before 2.8.3, and 3.0.0-alpha through 3.0.0-beta1 allows a cluster user to expose private files owned by the user running the MapReduce job history server process. The malicious user can construct a configuration file containing XML directives that reference sensitive files on the MapReduce job history server host.
Severity
6.5 (Medium)
CWE
- Information Disclosure
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://lists.apache.org/thread.html/a790a251ace7… | mailing-listx_refsource_MLIST |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Apache Software Foundation | Apache Hadoop |
Affected:
0.23.0 to 0.23.11
Affected: 2.0.0-alpha to 2.8.2 Affected: 3.0.0-alpha to 3.0.0-beta1 |
guessed |
Date Public
2018-01-19 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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