VAR-202208-0590
Vulnerability from variot - Updated: 2023-12-18 13:36Windows Secure Socket Tunneling Protocol (SSTP) Remote Code Execution Vulnerability. Microsoft Windows Point-to-Point Tunneling Protocol（PPTP）是美国微软（Microsoft）公司的一种网络协议，通过在基于 TCP/IP 的数据网络上创建虚拟专用网络 (VPN)，可以将数据从远程客户端安全传输到私有企业服务器. Microsoft Windows Point-to-Point Tunneling Protocol 存在安全漏洞。以下产品和版本受到影响：Windows 10 Version 1809 for 32-bit Systems,Windows 10 Version 21H2 for x64-based Systems,Windows 10 for 32-bit Systems,Windows 10 for x64-based Systems,Windows 10 Version 1607 for 32-bit Systems,Windows 10 Version 1607 for x64-based Systems,Windows Server 2016,Windows Server 2016 (Server Core installation),Windows 7 for 32-bit Systems Service Pack 1,Windows 7 for x64-based Systems Service Pack 1,Windows 8.1 for 32-bit systems,Windows 8.1 for x64-based systems,Windows RT 8.1,Windows Server 2008 for 32-bit Systems Service Pack 2,Windows Server 2008 for 32-bit Systems Service Pack 2 (Server Core installation),Windows Server 2008 for x64-based Systems Service Pack 2,Windows Server 2008 for x64-based Systems Service Pack 2 (Server Core installation),Windows Server 2008 R2 for x64-based Systems Service Pack 1,Windows Server 2008 R2 for x64-based Systems Service Pack 1 (Server Core installation),Windows Server 2012,Windows Server 2012 (Server Core installation),Windows Server 2012 R2,Windows Server 2012 R2 (Server Core installation),Windows 10 Version 1809 for x64-based Systems,Windows 10 Version 1809 for ARM64-based Systems,Windows Server 2019,Windows Server 2019 (Server Core installation),Windows 10 Version 21H1 for x64-based Systems,Windows 10 Version 21H1 for ARM64-based Systems,Windows 10 Version 21H1 for 32-bit Systems,Windows Server 2022,Windows Server 2022 (Server Core installation),Windows 10 Version 20H2 for x64-based Systems,Windows 10 Version 20H2 for 32-bit Systems,Windows 10 Version 20H2 for ARM64-based Systems,Windows Server, version 20H2 (Server Core Installation),Windows 11 for x64-based Systems,Windows 11 for ARM64-based Systems,Windows 10 Version 21H2 for 32-bit Systems,Windows 10 Version 21H2 for ARM64-based Systems
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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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