CVE-2021-37404 (GCVE-0-2021-37404)
Vulnerability from cvelistv5 – Published: 2022-06-13 07:00 – Updated: 2024-08-04 01:16
VLAI
EPSS
VEX
Title
Heap buffer overflow in libhdfs native library
Summary
There is a potential heap buffer overflow in Apache Hadoop libhdfs native code. Opening a file path provided by user without validation may result in a denial of service or arbitrary code execution. Users should upgrade to Apache Hadoop 2.10.2, 3.2.3, 3.3.2 or higher.
Severity
No CVSS data available.
CWE
- CWE-787 - Out-of-bounds Write
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://lists.apache.org/thread/2h56ztcj3ojc66qzf… | x_refsource_MISC |
| https://security.netapp.com/advisory/ntap-2022071… | x_refsource_CONFIRM |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Apache Software Foundation | Apache Hadoop |
Affected:
2.9.0 to 2.10.1
Affected: 3.0.0 to 3.1.4 Affected: 3.2.0 to 3.2.2 Affected: 3.3.0 to 3.3.1 |
guessed |
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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.
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.
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