GSD-2023-25564
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
GSS-NTLMSSP is a mechglue plugin for the GSSAPI library that implements NTLM authentication. Prior to version 1.2.0, memory corruption can be triggered when decoding UTF16 strings. The variable `outlen` was not initialized and could cause writing a zero to an arbitrary place in memory if `ntlm_str_convert()` were to fail, which would leave `outlen` uninitialized. This can lead to a denial of service if the write hits unmapped memory or randomly corrupts a byte in the application memory space. This vulnerability can trigger an out-of-bounds write, leading to memory corruption. This vulnerability can be triggered via the main `gss_accept_sec_context` entry point. This issue is fixed in version 1.2.0.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-25564",
"id": "GSD-2023-25564",
"references": [
"https://www.suse.com/security/cve/CVE-2023-25564.html"
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"details": "GSS-NTLMSSP is a mechglue plugin for the GSSAPI library that implements NTLM authentication. Prior to version 1.2.0, memory corruption can be triggered when decoding UTF16 strings. The variable `outlen` was not initialized and could cause writing a zero to an arbitrary place in memory if `ntlm_str_convert()` were to fail, which would leave `outlen` uninitialized. This can lead to a denial of service if the write hits unmapped memory or randomly corrupts a byte in the application memory space. This vulnerability can trigger an out-of-bounds write, leading to memory corruption. This vulnerability can be triggered via the main `gss_accept_sec_context` entry point. This issue is fixed in version 1.2.0.",
"id": "GSD-2023-25564",
"modified": "2023-12-13T01:20:40.697890Z",
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"baseScore": 6.5,
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"confidentialityImpact": "NONE",
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"lastModifiedDate": "2023-02-22T18:39Z",
"publishedDate": "2023-02-14T18:15Z"
}
}
}
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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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