GSD-2024-1013
Vulnerability from gsd - Updated: 2024-01-30 06:03Details
An out-of-bounds stack write flaw was found in unixODBC on 64-bit architectures where the caller has 4 bytes and callee writes 8 bytes. This issue may go unnoticed on little-endian architectures, while big-endian architectures can be broken.
Aliases
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"value": "Se encontr\u00f3 una falla de escritura de pila fuera de los l\u00edmites en unixODBC en arquitecturas de 64 bits donde la persona que llama tiene 4 bytes y la persona que llama escribe 8 bytes. Este problema puede pasar desapercibido en las arquitecturas little-endian, mientras que las arquitecturas big-endian pueden romperse."
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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 |
|---|
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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- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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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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