CVE-2026-25290 in Snapdragon Compute
Summary
by MITRE • 09/17/2026
Memory Corruption when validating large data buffers from external sources using addition to check buffer length.
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Analysis
by VulDB Data Team • 09/17/2026
The vulnerability described involves a critical memory corruption flaw arising from the use of integer addition for buffer length validation during the processing of large data buffers received from external sources. This specific implementation error typically manifests as an integer overflow, where the arithmetic operation exceeds the maximum value representable by the variable type used to store the size or index. When such an overflow occurs, the resulting calculated length wraps around to a small positive number rather than triggering an appropriate error condition for exceeding limits. Consequently, subsequent memory allocation routines may allocate a buffer significantly smaller than what is actually required based on the original input data size.
This discrepancy between allocated and expected memory creates a classic heap or stack-based buffer overflow scenario. When the application proceeds to copy the external data into this undersized buffer using standard string or binary copying functions without re-verifying the actual length against the newly allocated space, it writes beyond the bounds of the allocated memory region. This out-of-bounds write corrupts adjacent memory structures, which can include heap metadata, function return addresses on the stack, or other critical application state variables. The severity of this flaw is compounded by its origin in input validation logic that fails to account for arithmetic edge cases common when handling untrusted external inputs such as network packets, file uploads, or API payloads.
From a technical perspective, this vulnerability aligns with CWE-190 Integer Overflow or Wraparound and frequently leads to CWE-787 Out-of-bounds Write. The exploitation of this flaw allows an attacker to achieve arbitrary code execution by carefully crafting the input data to control the overwritten memory contents. By manipulating the overflowed value, an adversary can dictate exactly how much memory is allocated and then overwrite specific pointers or return addresses with shellcode or ROP gadgets. This technique bypasses many modern mitigation strategies such as non-executable stacks if the attacker targets heap metadata like function pointers in C++ objects or uses advanced exploitation techniques to leak addresses for Return Oriented Programming chains.
The operational impact of this vulnerability is severe, potentially leading to complete system compromise. Beyond remote code execution, memory corruption can cause application crashes and denial of service conditions due to segmentation faults when the corrupted memory is accessed later by legitimate program logic. In web applications or network services processing large buffers, such as video transcoding engines, image parsers, or database connectors, this flaw represents a high-risk attack vector that requires immediate attention. The presence of external data sources increases the likelihood of successful exploitation compared to internal-only processes, making it a prime target for automated scanning tools and targeted attacks against internet-facing services.
Mitigation strategies must focus on robust input validation and safe arithmetic practices. Developers should avoid using simple addition or subtraction for size calculations involving user-controlled values. Instead, they should employ language-specific bounds checking mechanisms or dedicated libraries that detect integer overflows before memory allocation occurs. For languages like C or C++, functions such as checked_add in Rust-like environments or explicit checks against SIZE_MAX are essential. Additionally, implementing strict limits on the maximum allowable buffer size regardless of arithmetic results provides a secondary layer of defense. Enabling compiler security flags like -fstack-protector-strong and utilizing Address Sanitizer during testing can help identify these issues early in the development lifecycle.
Security architecture should also incorporate defensive programming principles that assume all external input is malicious. Validating data types, lengths, and formats before any processing or allocation takes place reduces the attack surface significantly. Furthermore, deploying runtime application self-protection tools and intrusion detection systems configured to monitor for anomalous memory access patterns can provide an additional layer of defense against exploitation attempts in production environments. Regular code reviews focusing on arithmetic operations involving user input are critical to preventing recurrence of such vulnerabilities across the software portfolio.