GSD-2009-3051
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Multiple format string vulnerabilities in lib/silcclient/client_entry.c in Secure Internet Live Conferencing (SILC) Toolkit before 1.1.10, and SILC Client before 1.1.8, allow remote attackers to execute arbitrary code via format string specifiers in a nickname field, related to the (1) silc_client_add_client, (2) silc_client_update_client, and (3) silc_client_nickname_format functions.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2009-3051",
"description": "Multiple format string vulnerabilities in lib/silcclient/client_entry.c in Secure Internet Live Conferencing (SILC) Toolkit before 1.1.10, and SILC Client before 1.1.8, allow remote attackers to execute arbitrary code via format string specifiers in a nickname field, related to the (1) silc_client_add_client, (2) silc_client_update_client, and (3) silc_client_nickname_format functions.",
"id": "GSD-2009-3051",
"references": [
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"https://www.debian.org/security/2009/dsa-1879"
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"remediation": "unknown",
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"details": "Multiple format string vulnerabilities in lib/silcclient/client_entry.c in Secure Internet Live Conferencing (SILC) Toolkit before 1.1.10, and SILC Client before 1.1.8, allow remote attackers to execute arbitrary code via format string specifiers in a nickname field, related to the (1) silc_client_add_client, (2) silc_client_update_client, and (3) silc_client_nickname_format functions.",
"id": "GSD-2009-3051",
"modified": "2023-12-13T01:19:49.195147Z",
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"impact": {
"baseMetricV2": {
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "HIGH",
"userInteractionRequired": false
}
},
"lastModifiedDate": "2012-10-23T03:10Z",
"publishedDate": "2009-09-10T18:30Z"
}
}
}
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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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