CVE-2017-7521 (GCVE-0-2017-7521)
Vulnerability from cvelistv5 – Published: 2017-06-27 13:00 – Updated: 2024-08-05 16:04
VLAI
EPSS
VEX
Summary
OpenVPN versions before 2.4.3 and before 2.3.17 are vulnerable to remote denial-of-service due to memory exhaustion caused by memory leaks and double-free issue in extract_x509_extension().
Severity
5.9 (Medium)
CWE
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://community.openvpn.net/openvpn/wiki/Vulner… | x_refsource_CONFIRM |
| http://www.securitytracker.com/id/1038768 | vdb-entryx_refsource_SECTRACK |
| http://www.securityfocus.com/bid/99230 | vdb-entryx_refsource_BID |
| http://www.debian.org/security/2017/dsa-3900 | vendor-advisoryx_refsource_DEBIAN |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| OpenVPN Technologies, Inc | OpenVPN |
Affected:
before 2.4.3
Affected: before 2.3.17 |
guessed |
Date Public
2017-06-21 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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