CVE-2026-49269
Published: 24 June 2026
Summary
CVE-2026-49269 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability. Its CVSS base score is 8.6 (High).
Operationally, ranked at the 22.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-38809
Vulnerability details
Apple M1 GPUs retain register file data between compute shader dispatches from different processes. A sandboxed Metal attacker app can run a GPU reader shader that reads stale register values left by a separate sandboxed victim app. In the proof…
more
of concept, GPUVictim.app generates a fresh random 128-bit secret using SecRandomCopyBytes and loads it into GPU registers. GPUAttacker.app, a separate sandboxed app, recovers the exact secret from stale GPU register state. NOTE: The vendor stated that this behavior affects only legacy hardware and has already been addressed at the hardware level in current-generation Apple Silicon.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Insufficient information to map techniques.Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.