CVE-2021-24112 (GCVE-0-2021-24112)
Vulnerability from cvelistv5 – Published: 2021-02-25 23:01 – Updated: 2024-08-03 19:21
VLAI
EPSS
VEX
Title
.NET Core Remote Code Execution Vulnerability
Summary
.NET Core Remote Code Execution Vulnerability
Severity
CWE
- Remote Code Execution
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://portal.msrc.microsoft.com/en-US/security-… | x_refsource_MISC |
Impacted products
5 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Microsoft | Visual Studio 2019 for Mac |
Affected:
8.0.0 , < publication
(custom)
cpe:2.3:a:microsoft:visual_studio_2019:-:*:*:*:*:macos:*:* |
||
| Microsoft | Mono 6.12.0 |
Affected:
6.12.0 , < publication
(custom)
cpe:2.3:a:microsoft:mono:*:*:*:*:*:*:*:* |
||
| Microsoft | .NET Core 2.1 |
Affected:
2.1 , < publication
(custom)
cpe:2.3:a:microsoft:.net_core:*:*:*:*:*:*:*:* |
||
| Microsoft | .NET Core 3.1 |
Affected:
3.1 , < publication
(custom)
cpe:2.3:a:microsoft:.net_core:*:*:*:*:*:*:*:* |
||
| Microsoft | .NET 5.0 |
Affected:
5.0.0 , < publication
(custom)
cpe:2.3:a:microsoft:.net:*:*:*:*:*:*:*:* |
Date Public
2021-02-09 08:00
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"lastModified": "2024-11-21T05:52:22.857",
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"redhat_vex": {
"aggregate_severity": "Important",
"current_release_date": "2025-11-21T15:30:11+00:00",
"cve": "CVE-2021-24112",
"id": "CVE-2021-24112",
"initial_release_date": "2021-02-25T00:00:00+00:00",
"product_status:known_not_affected": "35",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "dotnet: Remote Code Execution Vulnerability",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-24112.json",
"version": "3"
},
"suse_vex": {
"aggregate_severity": "critical",
"current_release_date": "2025-07-08T00:15:40Z",
"cve": "CVE-2021-24112",
"id": "CVE-2021-24112",
"initial_release_date": "2023-02-15T03:45:14Z",
"product_status:recommended": "22",
"source": "SUSE CSAF VEX",
"status": "interim",
"title": "SUSE CVE CVE-2021-24112",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2021-24112.json",
"version": "8"
}
}
}
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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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