VAR-201607-0303
Vulnerability from variot - Updated: 2023-12-18 11:13Audio in Apple OS X before 10.11.6 allows local users to gain privileges or cause a denial of service (memory corruption) via a crafted file. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file.The specific flaw exists within the handling of DspFuncLib. The issue lies in the failure to properly check function IDs before removing items from a function table. An attacker can leverage this vulnerability to escalate privileges and execute code under the context of the kernel. Apple Mac OS X is prone to multiple security vulnerabilities. Attackers can exploit these issues to execute arbitrary code, gain sensitive information, cause denial-of-service conditions, bypass security restrictions, and perform unauthorized actions. This may aid in other attacks. Apple Mac OS X 10.9.5, 10.10.5 and 10.11 through 10.11.5 are vulnerable. Audio is one of the audio components
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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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