GSD-2013-3220
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
bitcoind and Bitcoin-Qt before 0.4.9rc2, 0.5.x before 0.5.8rc2, 0.6.x before 0.6.5rc2, and 0.7.x before 0.7.3rc2, and wxBitcoin, do not properly consider whether a block's size could require an excessive number of database locks, which allows remote attackers to cause a denial of service (split) and enable certain double-spending capabilities via a large block that triggers incorrect Berkeley DB locking.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2013-3220",
"description": "bitcoind and Bitcoin-Qt before 0.4.9rc2, 0.5.x before 0.5.8rc2, 0.6.x before 0.6.5rc2, and 0.7.x before 0.7.3rc2, and wxBitcoin, do not properly consider whether a block\u0027s size could require an excessive number of database locks, which allows remote attackers to cause a denial of service (split) and enable certain double-spending capabilities via a large block that triggers incorrect Berkeley DB locking.",
"id": "GSD-2013-3220"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2013-3220"
],
"details": "bitcoind and Bitcoin-Qt before 0.4.9rc2, 0.5.x before 0.5.8rc2, 0.6.x before 0.6.5rc2, and 0.7.x before 0.7.3rc2, and wxBitcoin, do not properly consider whether a block\u0027s size could require an excessive number of database locks, which allows remote attackers to cause a denial of service (split) and enable certain double-spending capabilities via a large block that triggers incorrect Berkeley DB locking.",
"id": "GSD-2013-3220",
"modified": "2023-12-13T01:22:23.077555Z",
"schema_version": "1.4.0"
}
},
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}
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"accessVector": "NETWORK",
"authentication": "NONE",
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"baseScore": 6.4,
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"vectorString": "AV:N/AC:L/Au:N/C:N/I:P/A:P",
"version": "2.0"
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"impactScore": 4.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
}
},
"lastModifiedDate": "2020-03-18T17:38Z",
"publishedDate": "2013-08-02T12:10Z"
}
}
}
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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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