VAR-201203-0380
Vulnerability from variot - Updated: 2023-12-18 12:10The TAR file parser in AVG Anti-Virus 10.0.0.1190, Quick Heal (aka Cat QuickHeal) 11.00, Comodo Antivirus 7424, Emsisoft Anti-Malware 5.1.0.1, eSafe 7.0.17.0, F-Prot Antivirus 4.6.2.117, Fortinet Antivirus 4.2.254.0, Ikarus Virus Utilities T3 Command Line Scanner 1.1.97.0, Jiangmin Antivirus 13.0.900, Kaspersky Anti-Virus 7.0.0.125, McAfee Anti-Virus Scanning Engine 5.400.0.1158, McAfee Gateway (formerly Webwasher) 2010.1C, NOD32 Antivirus 5795, Norman Antivirus 6.06.12, Panda Antivirus 10.0.2.7, Rising Antivirus 22.83.00.03, Sophos Anti-Virus 4.61.0, AVEngine 20101.3.0.103 in Symantec Endpoint Protection 11, Trend Micro AntiVirus 9.120.0.1004, and Trend Micro HouseCall 9.120.0.1004 allows remote attackers to bypass malware detection via a TAR file with an appended ZIP file. NOTE: this may later be SPLIT into multiple CVEs if additional information is published showing that the error occurred independently in different TAR parser implementations. Multiple products TAR A file parser contains a vulnerability that can prevent malware detection. Different TAR If it is announced that there is also a problem with the parser implementation, this vulnerability can be CVE May be split.By a third party ZIP File attached TAR Malware detection may be avoided via files. Successful exploits will allow attackers to bypass on-demand virus scanning, possibly allowing malicious files to escape detection. The following products are affected: AVG AVG Anti-Virus 10.0.0.1190 Quick Heal Technologies CAT-QuickHeal 11.00 Comodo AntiVirus 7424 Emsisoft Antivirus 5.1.0.1 eSafe Antivirus 7.0.17.0 Frisk Software F-Prot Antivirus 4.6.2.117 Fortinet Antivirus 4.2.254.0 Ikarus Antivirus T3.1.1.97.0
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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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