CVE-2025-53074 is an out-of-bounds read vulnerability identified in version 0.2 of Samsung's open-source rLottie library. rLottie is a rendering engine used to display Lottie animations, which are JSON-based vector animations commonly integrated into user interfaces and applications. The vulnerability is classified under CWE-125, indicating that the software reads data outside the bounds of allocated memory buffers. This flaw can lead to buffer overflow conditions, potentially exposing sensitive memory contents or causing application crashes. The vulnerability does not require any privileges or authentication to exploit but does require user interaction, such as opening or rendering a crafted Lottie animation file. The CVSS 4.0 base score is 5.1 (medium severity), reflecting a network attack vector with low complexity and no privileges required, but with limited impact on confidentiality, integrity, and availability. No known exploits are currently reported in the wild, and no patches have been published yet. Given that rLottie is used in Samsung products and potentially other applications that embed this library, the vulnerability could be exploited to cause denial of service or information disclosure if malicious animation files are processed.

For European organizations, the impact depends on the extent to which Samsung products or third-party applications using rLottie v0.2 are deployed within their environments. If exploited, this vulnerability could lead to application crashes or leakage of sensitive information from memory, potentially exposing confidential data. This is particularly relevant for sectors relying on Samsung smart devices or software that incorporate rLottie for UI animations, such as consumer electronics, smart TVs, and embedded systems. While the vulnerability does not allow privilege escalation or remote code execution directly, the disruption of services or exposure of sensitive data could affect business continuity and data privacy compliance, especially under GDPR regulations. Organizations in media, telecommunications, and consumer electronics sectors may face higher risks if they use affected products. The lack of known exploits reduces immediate risk, but the medium severity score indicates that timely mitigation is advisable to prevent future exploitation.

Organizations should first identify all instances of rLottie v0.2 within their software stack, including embedded devices and applications. Since no official patches are currently available, mitigation should focus on minimizing exposure: restrict the processing of untrusted or unauthenticated Lottie animation files, implement input validation and sandboxing around animation rendering components, and monitor for abnormal application behavior or crashes that could indicate exploitation attempts. Vendors and developers using rLottie should prioritize upgrading to a patched version once released or consider replacing rLottie with alternative libraries that do not have this vulnerability. Additionally, applying strict network segmentation and endpoint protection can reduce the risk of exploitation via crafted files. Regularly reviewing security advisories from Samsung and related open-source projects is essential to apply updates promptly.