CVE-2024-21792 (GCVE-0-2024-21792)
Vulnerability from cvelistv5 – Published: 2024-05-16 20:46 – Updated: 2024-08-01 22:27
VLAI
EPSS
VEX
Summary
Time-of-check Time-of-use race condition in Intel(R) Neural Compressor software before version 2.5.0 may allow an authenticated user to potentially enable information disclosure via local access.
Severity
4.7 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-05-20 14:49 UTC
CWE
- information disclosure
- CWE-367 - Time-of-check Time-of-use race condition
Assigner
References
1 reference
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| n/a | Intel(R) Neural Compressor software |
Affected:
before version 2.5.0
|
||
| intel | neural_compressor_software |
Affected:
- , < 2.5.0
(semver)
cpe:2.3:a:intel:neural_compressor_software:-:*:*:*:*:*:*:* |
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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
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