GSD-2006-2024
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Multiple vulnerabilities in libtiff before 3.8.1 allow context-dependent attackers to cause a denial of service via a TIFF image that triggers errors in (1) the TIFFFetchAnyArray function in (a) tif_dirread.c; (2) certain "codec cleanup methods" in (b) tif_lzw.c, (c) tif_pixarlog.c, and (d) tif_zip.c; (3) and improper restoration of setfield and getfield methods in cleanup functions within (e) tif_jpeg.c, tif_pixarlog.c, (f) tif_fax3.c, and tif_zip.c.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2006-2024",
"description": "Multiple vulnerabilities in libtiff before 3.8.1 allow context-dependent attackers to cause a denial of service via a TIFF image that triggers errors in (1) the TIFFFetchAnyArray function in (a) tif_dirread.c; (2) certain \"codec cleanup methods\" in (b) tif_lzw.c, (c) tif_pixarlog.c, and (d) tif_zip.c; (3) and improper restoration of setfield and getfield methods in cleanup functions within (e) tif_jpeg.c, tif_pixarlog.c, (f) tif_fax3.c, and tif_zip.c.",
"id": "GSD-2006-2024",
"references": [
"https://www.suse.com/security/cve/CVE-2006-2024.html",
"https://www.debian.org/security/2006/dsa-1054",
"https://access.redhat.com/errata/RHSA-2006:0648",
"https://access.redhat.com/errata/RHSA-2006:0425"
]
},
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"modified": "2023-12-13T01:19:53.001518Z",
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"impact": {
"baseMetricV2": {
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "SINGLE",
"availabilityImpact": "PARTIAL",
"baseScore": 4.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:S/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
}
},
"lastModifiedDate": "2018-10-03T21:40Z",
"publishedDate": "2006-04-25T23:02Z"
}
}
}
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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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