CVE-2016-1847 in iOS
Summary
by MITRE
OpenGL, as used in Apple iOS before 9.3.2, OS X before 10.11.5, tvOS before 9.2.1, and watchOS before 2.2.1, allows remote attackers to execute arbitrary code or cause a denial of service (memory corruption) via a crafted web site.
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Analysis
by VulDB Data Team • 11/07/2024
This vulnerability resides in the OpenGL graphics rendering system component that Apple integrated into their mobile and desktop operating systems. The flaw manifests as a memory corruption issue within the OpenGL implementation that occurs when processing specially crafted web content. Attackers can exploit this weakness by hosting malicious websites that trigger the vulnerable OpenGL code path, potentially leading to arbitrary code execution or system crashes. The vulnerability affects multiple Apple platforms including iOS, macOS, tvOS, and watchOS, demonstrating the widespread nature of the OpenGL implementation across Apple's ecosystem. The memory corruption aspect suggests that the vulnerability likely involves buffer overflows, use-after-free conditions, or other memory management flaws that can be manipulated to overwrite critical system memory regions.
The technical exploitation of this vulnerability follows patterns consistent with graphics driver exploits and aligns with common attack vectors found in the ATT&CK framework under the category of exploit development. The vulnerability's presence in web rendering contexts indicates that it operates within the browser or webview component that leverages OpenGL for graphics acceleration. This creates a particularly dangerous scenario where a simple web visit could compromise a device, as the attack surface extends from the web browser directly into the graphics processing layer. The memory corruption aspect suggests that attackers could potentially overwrite function pointers, return addresses, or other critical memory structures to gain code execution control.
From an operational impact perspective, this vulnerability represents a significant risk to Apple device users who may encounter malicious websites through normal browsing activities or social engineering attacks. The ability to execute arbitrary code remotely means that attackers could potentially install malware, steal user data, or take complete control of affected devices. The denial of service component adds to the risk profile as it could be used to create persistent availability issues or as a stepping stone for more sophisticated attacks. The vulnerability affects versions predating the mentioned security updates, indicating that users who have not applied the patches remain exposed to potential exploitation attempts.
The remediation approach for this vulnerability centers on applying the official security updates released by Apple. These patches typically address the specific memory management issues within the OpenGL implementation and may include additional mitigations such as stack canaries, address space layout randomization, or other exploit prevention techniques. Organizations should prioritize updating all affected Apple devices to the latest security releases and consider implementing network-based protections such as web filtering or sandboxing mechanisms to reduce exposure risk. Security teams should also monitor for any reported exploitation attempts and maintain awareness of related vulnerabilities that may affect similar graphics rendering components in other software platforms.
This vulnerability demonstrates the critical importance of graphics driver security and aligns with CWE categories related to memory safety issues and buffer overflows. The cross-platform nature of the vulnerability across Apple's operating systems highlights the need for comprehensive security testing of shared components and the potential for cascading effects when core system libraries contain exploitable code. The fact that this vulnerability could be triggered through web browsing activities underscores the growing attack surface that modern operating systems present and the necessity for robust security measures throughout the entire software stack, particularly in components that handle untrusted input from web sources.