CVE-2024-27367 in Exynos 980
Summary
by MITRE • 09/09/2024
An issue was discovered in Samsung Mobile Processor Exynos Wearable Processor Exynos 980, Exynos 850, Exynos 1080, Exynos 1280, Exynos 1380, Exynos 1330, Exynos 1480, Exynos W920, Exynos W930. In the function slsi_rx_scan_ind(), there is no input validation check on a length coming from userspace, which can lead to integer overflow and a potential heap over-read.
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Analysis
by VulDB Data Team • 06/13/2025
The vulnerability identified as CVE-2024-27367 affects Samsung wearable processors including Exynos 980, 850, 1080, 1280, 1380, 1330, 1480, W920, and W930 models. This issue resides within the slsi_rx_scan_ind() function where insufficient input validation occurs on length parameters sourced from userspace. The absence of proper validation creates a critical security weakness that can be exploited through malicious input manipulation. The vulnerability manifests as an integer overflow condition that subsequently leads to a heap over-read scenario, potentially allowing attackers to access unauthorized memory regions and extract sensitive information.
The technical flaw represents a classic integer overflow vulnerability that falls under CWE-190, which specifically addresses integer overflow conditions. When the function processes length values from userspace, it fails to validate whether these values exceed the maximum representable integer limits. This oversight enables attackers to craft inputs that cause the length parameter to wrap around and become negative or excessively large, ultimately resulting in buffer over-read conditions. The heap over-read aspect of this vulnerability is particularly concerning as it can expose sensitive data stored in memory, potentially including cryptographic keys, user credentials, or proprietary information.
The operational impact of CVE-2024-27367 extends beyond simple data exposure to encompass potential system compromise and information leakage across Samsung wearable devices. Attackers exploiting this vulnerability could gain access to memory contents that should remain protected, potentially leading to credential theft, data exfiltration, or even privilege escalation within the affected systems. The vulnerability affects devices running on Exynos wearable processors, which are commonly found in smartwatches and other wearable IoT devices that handle sensitive personal data. This weakness creates a persistent threat vector that could be leveraged in various attack scenarios, particularly in environments where these devices are used for health monitoring, financial transactions, or personal communication.
Mitigation strategies for this vulnerability should focus on implementing proper input validation and integer overflow protection mechanisms within the affected function. The most effective approach involves adding comprehensive bounds checking on all length parameters received from userspace before they are processed by the slsi_rx_scan_ind() function. Additionally, developers should implement robust integer overflow detection routines and ensure that all buffer operations are properly validated against maximum allowable sizes. The remediation process should align with ATT&CK framework techniques related to privilege escalation and credential access, as this vulnerability could potentially be leveraged to gain unauthorized system access. Organizations should also consider implementing runtime protections such as stack canaries, address space layout randomization, and memory protection mechanisms to further reduce the exploitability of similar vulnerabilities. Regular firmware updates and security patches should be deployed immediately to address this vulnerability across all affected Samsung wearable device models.