CVE-2026-113915 in iOS
Summary
by MITRE • 10/26/2026
A race condition was addressed with additional validation. This issue is fixed in iOS 26.7.2 and iPadOS 26.7.2, iOS 27.2 and iPadOS 27.2, macOS Golden Gate 27.2, macOS Sequoia 15.8.2, macOS Tahoe 26.7.2, tvOS 27.2, visionOS 27.2, watchOS 27.2. An app may be able to access sensitive user data.
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Analysis
by VulDB Data Team • 10/27/2026
The vulnerability described constitutes a race condition within the operating system's security architecture, specifically involving insufficient validation during concurrent operations. Race conditions occur when software behavior depends on the relative timing of events, such as the order in which threads or processes are scheduled by the operating system kernel. In this specific instance, an application was able to exploit a window of opportunity where state checks and subsequent actions were not performed atomically. This lack of atomicity allowed an app to bypass intended security controls before they could be fully enforced, leading to unauthorized access to sensitive user data. The core technical flaw lies in the failure to properly synchronize access to shared resources or critical sections of code, allowing a malicious actor to manipulate the state of the system during the brief interval between validation and execution.
From an industry standard perspective, this vulnerability aligns closely with CWE-362, which defines concurrent execution using shared resources with bad synchronization leading to race conditions. The exploitation vector typically involves an attacker crafting specific timing-based inputs or triggering multiple simultaneous requests that exploit the gap in the application's logic flow. This is further contextualized by MITRE ATT&CK technique T1059, Command and Scripting Interpreter, if the access leads to script execution, but more accurately maps to data exfiltration techniques where sensitive information is accessed without proper authorization checks due to logical flaws rather than traditional injection or buffer overflow exploits. The impact of such a flaw can be severe, as it undermines the fundamental trust model of mobile operating systems like iOS and iPadOS, which rely on strict sandboxing and permission boundaries to isolate applications from each other and from core system data.
The operational impact of this vulnerability is significant for end-users whose private information may be exposed without their knowledge or consent. Sensitive user data can include personal identifiers, location history, messages, photos, or financial details depending on the specific subsystem affected. Because race conditions are often non-deterministic and difficult to reproduce consistently, they pose a unique challenge for both detection and remediation during normal usage patterns. Attackers may use automated tools to flood the system with requests in an attempt to trigger the vulnerable code path repeatedly until successful exploitation occurs. This type of vulnerability erodes user confidence in device security and can lead to privacy breaches that have long-term consequences, including identity theft or targeted phishing attacks based on harvested personal data.
Apple has addressed this issue by implementing additional validation mechanisms designed to ensure that state checks are performed atomically with the actions they protect. By enforcing stricter synchronization primitives and reducing the window of vulnerability during critical operations, the update prevents applications from exploiting timing discrepancies to bypass security controls. Users should immediately update their devices to iOS 26.7.2, iPadOS 26.7.2, iOS 27.2, iPadOS 27.2, macOS Golden Gate 27.2, macOS Sequoia 15.8.2, macOS Tahoe 26.7.2, tvOS 27.2, visionOS 27.2, and watchOS 27.2 to mitigate this risk. Developers should also review their applications for similar patterns of non-atomic state checks and implement proper locking mechanisms or transactional integrity controls to prevent race conditions in future releases. Regular security audits and static analysis tools that detect concurrency flaws are recommended practices to maintain robust application security posture against such logical vulnerabilities.