GSD-2021-3600
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
It was discovered that the eBPF implementation in the Linux kernel did not properly track bounds information for 32 bit registers when performing div and mod operations. A local attacker could use this to possibly execute arbitrary code.
Aliases
Aliases
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"https://access.redhat.com/errata/RHSA-2021:4356",
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"value": "Se descubri\u00f3 que la implementaci\u00f3n de eBPF en el kernel de Linux no rastreaba adecuadamente la informaci\u00f3n de l\u00edmites para registros de 32 bits al realizar operaciones div y mod. Un atacante local podr\u00eda usar esto para posiblemente ejecutar c\u00f3digo arbitrario."
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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
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- 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.
- 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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