CVE-2019-14130 in Snapdragon Auto
Summary
by MITRE
Memory corruption can occurs in trusted application if offset size from HLOS is more than actual mapped buffer size in Snapdragon Auto, Snapdragon Compute, Snapdragon Mobile, Snapdragon Wired Infrastructure and Networking in Kamorta, QCS404, Rennell, SC7180, SDX55, SM6150, SM7150, SM8250, SXR2130
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
Analysis
by VulDB Data Team • 11/06/2020
This vulnerability represents a critical memory corruption issue affecting multiple Qualcomm Snapdragon platform variants including automotive, mobile, and networking solutions. The flaw manifests when the hypervisor layer (HLOS) provides an offset size that exceeds the actual mapped buffer size within the trusted application environment. This discrepancy creates a dangerous condition where memory access operations can traverse beyond allocated boundaries, potentially leading to arbitrary code execution or system instability. The vulnerability impacts a wide range of Snapdragon products including Kamorta, QCS404, Rennell, SC7180, SDX55, SM6150, SM7150, SM8250, and SXR2130 platforms, indicating a fundamental architectural weakness in memory management controls across these device families.
The technical implementation of this vulnerability stems from inadequate bounds checking within the memory mapping mechanisms between the hypervisor and trusted application layers. When HLOS calculates and passes offset parameters to the trusted application, it fails to validate whether these parameters remain within the actual buffer boundaries that have been mapped in memory. This validation gap allows for buffer over-read or over-write conditions that can corrupt adjacent memory regions, potentially affecting critical system components including secure element operations, cryptographic functions, and memory protection mechanisms. The flaw operates at the intersection of virtualization and memory management, where the hypervisor's memory management decisions directly influence the trusted execution environment's memory safety.
The operational impact of this vulnerability extends beyond simple memory corruption to potentially enable sophisticated attack vectors targeting the secure execution environment. An attacker exploiting this weakness could leverage the memory corruption to escalate privileges, bypass security controls, or inject malicious code within the trusted application context. The vulnerability's presence across automotive, mobile, and networking platforms creates widespread exposure since these systems often handle sensitive data and critical operations. The potential for remote exploitation exists if the vulnerable platforms are connected to networks or exposed to untrusted inputs through communication interfaces, making this a significant concern for IoT deployments and automotive systems that rely on secure execution environments.
Mitigation strategies should focus on implementing robust bounds checking mechanisms within the memory management layers and strengthening the validation protocols between HLOS and trusted applications. System designers must ensure that all memory offset parameters are validated against actual buffer sizes before any memory access operations occur. Additionally, memory protection mechanisms including stack canaries, address space layout randomization, and memory tagging should be enhanced to detect and prevent exploitation attempts. The vulnerability aligns with CWE-129 Input Validation and CWE-787 Out-of-bounds Write categories, and maps to ATT&CK techniques including privilege escalation and defense evasion through memory corruption exploitation. Organizations should implement firmware updates, conduct thorough security assessments of affected platforms, and establish monitoring protocols to detect potential exploitation attempts. The vulnerability demonstrates the critical importance of maintaining memory safety in virtualized environments where the hypervisor's memory decisions directly impact the security of trusted execution contexts.