GSD-2023-5075
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
A buffer overflow was reported in the FmpSipoCapsuleDriver driver in the IdeaPad Duet 3-10IGL5 that may allow a local attacker with elevated privileges to execute arbitrary code.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-5075",
"id": "GSD-2023-5075"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
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"modified": "2023-12-13T01:20:50.627728Z",
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"value": "Lenovo thanks Zichuan Li (@Ri7erLi) from Indiana University Bloomington for reporting this vulnerability."
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"impact": {
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"attackComplexity": "LOW",
"attackVector": "LOCAL",
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"lastModifiedDate": "2023-11-16T18:01Z",
"publishedDate": "2023-11-08T22:15Z"
}
}
}
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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 |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
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- Not confirmed: The user expressed doubt about the validity of the vulnerability.
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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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