GSD-2023-7104
Vulnerability from gsd - Updated: 2023-12-26 06:01Details
A vulnerability was found in SQLite SQLite3 up to 3.43.0 and classified as critical. This issue affects the function sessionReadRecord of the file ext/session/sqlite3session.c of the component make alltest Handler. The manipulation leads to heap-based buffer overflow. It is recommended to apply a patch to fix this issue. The associated identifier of this vulnerability is VDB-248999.
Aliases
{
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
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"modified": "2023-12-26T06:01:17.677729Z",
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"value": "Eine kritische Schwachstelle wurde in SQLite SQLite3 bis 3.43.0 gefunden. Hierbei geht es um die Funktion sessionReadRecord der Datei ext/session/sqlite3session.c der Komponente make alltest Handler. Durch die Manipulation mit unbekannten Daten kann eine heap-based buffer overflow-Schwachstelle ausgenutzt werden. Als bestm\u00f6gliche Massnahme wird Patching empfohlen."
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}
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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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