GCVE-1988-2026-0270
Vulnerability from gna-1988 – Published: 2026-09-08 08:13 – Updated: 2026-09-11 11:21
VLAI
EPSS
VEX
Title
APPLE-SA-03-24-2026-10 Xcode 26.4
Summary
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256
APPLE-SA-03-24-2026-10 Xcode 26.4
Xcode 26.4 addresses the following issues.
Information about the security content is also available at
https://support.apple.com/126801.
Apple maintains a Security Releases page at
https://support.apple.com/100100 which lists recent
software updates with security advisories.
otool
Available for: macOS Tahoe 26.2 and later
Impact: An app may be able to cause unexpected system termination
Description: An out-of-bounds read was addressed with improved bounds
checking.
CVE-2026-28890: Nathaniel Oh (@calysteon)
Simulator
Available for: macOS Tahoe 26.2 and later
Impact: An app may be able to read arbitrary files as root
Description: A permissions issue was addressed with additional
restrictions.
CVE-2026-28889: Mihai Marin
Additional recognition
Dev Tools
We would like to acknowledge Nathaniel Oh (@calysteon) for their
assistance.
otool
We would like to acknowledge Eddy T for their assistance.
Swift
We would like to acknowledge Banavath Aravind for their assistance.
Xcode 26.4 may be obtained from:
https://developer.apple.com/xcode/downloads/
To check that the Xcode has been updated:
* Select Xcode in the menu bar
* Select About Xcode
* The version after applying this update will be "Xcode 26.4".
All information is also posted on the Apple Security Releases
web site: https://support.apple.com/100100.
This message is signed with Apple's Product Security PGP key,
and details are available at:
https://www.apple.com/support/security/pgp/
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_______________________________________________
Sent through the Full Disclosure mailing list
https://nmap.org/mailman/listinfo/fulldisclosure
Web Archives & RSS: https://seclists.org/fulldisclosure/
Severity
No CVSS data available.
Assigner
References
8 references
Relationships
reference
GCVE-1988-2026-0270 (this record)
- related CVE-2026-28889
- related CVE-2026-28890
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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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