CVE-2025-27055 in Snapdragon Compute
Summary
by MITRE • 07/08/2025
Memory corruption during the image encoding process.
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Analysis
by VulDB Data Team • 06/22/2026
Memory corruption during image encoding processes represents a critical class of vulnerabilities that can lead to arbitrary code execution and system compromise. These flaws typically occur when image processing libraries fail to properly validate input data or manage memory allocation during the encoding phase, creating opportunities for attackers to manipulate memory structures through malformed image files. The vulnerability often stems from insufficient bounds checking, improper handling of variable-length data structures, or inadequate memory management during the transformation of raw image data into encoded formats such as jpeg png or gif. Such issues commonly manifest in image processing libraries, web browsers, mobile applications, and server-side image handling components where user-supplied image content is processed without adequate sanitization.
The technical implementation of these vulnerabilities typically involves buffer overflows, use-after-free conditions, or heap corruption scenarios that occur when the encoding engine attempts to store or manipulate image data beyond allocated memory boundaries. Attackers can exploit these weaknesses by crafting malicious image files that trigger specific memory access patterns during encoding operations, potentially allowing them to overwrite critical memory locations including return addresses, function pointers, or other control structures. The exploitation often requires careful crafting of input data to map the memory corruption into a controlled execution flow, leveraging techniques such as return-oriented programming or just-in-time code generation to achieve remote code execution. These vulnerabilities are particularly dangerous because they can be triggered through common user interactions such as visiting websites, opening email attachments, or viewing images in applications that automatically process and encode image content.
The operational impact of memory corruption vulnerabilities in image encoding processes can be severe and far-reaching across multiple threat vectors. Web applications that process user-uploaded images become prime targets for remote code execution attacks, allowing attackers to compromise servers and potentially gain access to entire network infrastructures. Mobile applications that handle image encoding are vulnerable to similar attacks that can lead to device compromise, data theft, or unauthorized access to sensitive information. The widespread use of image processing libraries across different platforms and applications means that a single vulnerability can affect numerous systems simultaneously, creating cascading security impacts. Additionally, these vulnerabilities often remain undetected for extended periods due to the complexity of image format specifications and the difficulty of reproducing certain memory corruption scenarios, making them particularly dangerous for long-term security operations.
Security mitigations for image encoding memory corruption vulnerabilities should focus on comprehensive input validation, robust memory management practices, and defensive programming techniques. Implementing proper bounds checking and validation of image parameters before encoding operations can prevent many buffer overflow scenarios. Using memory-safe programming languages or employing compiler-based protections such as stack canaries, address space layout randomization, and data execution prevention can significantly reduce exploitation success rates. Regular updates and patches to image processing libraries, combined with proper sandboxing of image processing operations, help contain potential impacts. Organizations should also implement network monitoring to detect unusual image processing activities and establish secure coding practices that align with established security standards including those defined in the common weakness enumeration framework and attack technique catalog. The mitigation strategies must account for the complexity of modern image formats and ensure that all input validation occurs before any encoding operations are initiated, preventing attackers from leveraging the encoding process as an attack vector.