GSD-2022-29242
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
GOST engine is a reference implementation of the Russian GOST crypto algorithms for OpenSSL. TLS clients using GOST engine when ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is agreed and the server uses 512 bit GOST secret keys are vulnerable to buffer overflow. GOST engine version 3.0.1 contains a patch for this issue. Disabling ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is a possible workaround.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-29242",
"description": "GOST engine is a reference implementation of the Russian GOST crypto algorithms for OpenSSL. TLS clients using GOST engine when ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is agreed and the server uses 512 bit GOST secret keys are vulnerable to buffer overflow. GOST engine version 3.0.1 contains a patch for this issue. Disabling ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is a possible workaround.",
"id": "GSD-2022-29242"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
"details": "GOST engine is a reference implementation of the Russian GOST crypto algorithms for OpenSSL. TLS clients using GOST engine when ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is agreed and the server uses 512 bit GOST secret keys are vulnerable to buffer overflow. GOST engine version 3.0.1 contains a patch for this issue. Disabling ciphersuite `TLS_GOSTR341112_256_WITH_KUZNYECHIK_CTR_OMAC` is a possible workaround.",
"id": "GSD-2022-29242",
"modified": "2023-12-13T01:19:42.132384Z",
"schema_version": "1.4.0"
}
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"TITLE": "Buffer Overflow on creating key transport blob in GOST Engine"
},
"affects": {
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}
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"baseScore": 5.9,
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"discovery": "UNKNOWN"
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"impact": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
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"exploitabilityScore": 10.0,
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"severity": "MEDIUM",
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},
"lastModifiedDate": "2022-06-07T16:54Z",
"publishedDate": "2022-05-24T15:15Z"
}
}
}
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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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