CVE-2022-36844 in Smart Phone
Summary
by MITRE • 09/09/2022
A heap-based overflow vulnerability in HWR::EngJudgeModel::Construct() in libSDKRecognitionText.spensdk.samsung.so library prior to SMR Sep-2022 Release 1 allows attacker to cause memory access fault.
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Analysis
by VulDB Data Team • 09/10/2022
The heap-based buffer overflow vulnerability identified as CVE-2022-36844 resides within the HWR::EngJudgeModel::Construct() function of the libSDKRecognitionText.spensdk.samsung.so library, affecting Samsung devices prior to the SMR September 2022 security release. This vulnerability represents a critical memory corruption flaw that manifests during the text recognition processing within Samsung's handwriting recognition SDK. The affected library is part of Samsung's broader software ecosystem designed for handwriting recognition and input processing, commonly utilized in tablet devices and smartphones running Samsung's operating systems. The vulnerability specifically impacts the heap memory management during object construction, where insufficient bounds checking allows attackers to manipulate memory layout through crafted input data.
The technical flaw occurs when the Construct() function processes input parameters without adequate validation of buffer sizes or input lengths, creating a condition where heap memory can be overwritten beyond its allocated boundaries. This heap-based overflow presents significant operational risks as it enables attackers to corrupt adjacent heap memory regions, potentially leading to arbitrary code execution or system instability. The vulnerability is particularly concerning because it operates within a core recognition library that handles user input data, making it accessible through normal application usage patterns. The flaw is categorized under CWE-122 Heap-based Buffer Overflow, which specifically addresses buffer overflows that occur in heap-allocated memory regions. Attackers can exploit this vulnerability by crafting malicious input data that triggers the buffer overflow condition during text recognition processing, potentially allowing for privilege escalation or denial of service attacks.
The operational impact of CVE-2022-36844 extends beyond simple memory corruption as it represents a potential entry point for more sophisticated attacks within the Samsung ecosystem. Mobile devices running affected software versions become vulnerable to remote code execution scenarios where attackers can manipulate the recognition engine to execute malicious code with the privileges of the affected application. This vulnerability aligns with ATT&CK technique T1059.007 for command and scripting interpreter, as the overflow could enable attackers to inject malicious payloads through text input processing. The attack surface is particularly broad given that handwriting recognition is a fundamental feature across multiple Samsung applications and services, including note-taking applications, input methods, and document processing tools. Additionally, the vulnerability affects the stability of the entire device as memory corruption can lead to system crashes or unpredictable behavior during normal operation.
Mitigation strategies for CVE-2022-36844 primarily focus on applying the Samsung SMR September 2022 security patches that address the heap overflow condition through proper input validation and buffer size checking. Organizations should implement immediate patch management protocols to ensure all affected Samsung devices receive the security updates. System administrators should monitor for potential exploitation attempts through unusual memory access patterns or application crashes during text recognition processing. Additional defensive measures include implementing application sandboxing for handwriting recognition features, monitoring for abnormal heap memory usage patterns, and deploying intrusion detection systems that can identify exploitation attempts targeting heap-based vulnerabilities. The vulnerability demonstrates the importance of proper memory management practices in mobile SDKs and highlights the need for comprehensive security testing of input validation mechanisms within recognition and processing libraries. Security teams should also consider implementing runtime protections such as heap canaries or address space layout randomization to reduce the exploitability of similar vulnerabilities in the future.