CVE-2025-53074: 
NixOS vulnerability analysis and mitigation

CVE-2025-53074 is an Out-of-bounds Read vulnerability (CWE-125) in Samsung Open Source rLottie that allows buffer overflow reads when processing malicious Lottie animation files. It affects rLottie version V0.2 exclusively. The vulnerability was published on June 30, 2025, with the underlying fix merged into the upstream repository on June 11, 2025. It carries a CVSS v3.1 base score of 9.1 (Critical) and a CVSS v4.0 base score of 5.1 (Medium) (Red Hat CVE, ENISA EUVD).

The root cause is insufficient input validation during the parsing of Lottie animation files (CWE-125: Out-of-bounds Read), which can result in buffer overread conditions. Specifically, the fix addresses: missing type checks before casting CompLayer() to model::Layer, absent bounds checking in Gradient::populate(), a missing empty-check on the frames vector, and failure to reject outlier values (GitHub PR #571). An attacker can trigger the vulnerability by supplying a crafted malicious Lottie file to an application that uses the rLottie library for rendering animations. The attack vector is network-based (CVSS v3.1: AV:N), requires no privileges, and in the v3.1 scoring model requires no user interaction, though the v4.0 scoring reflects active user interaction as a precondition (Red Hat CVE).

Successful exploitation can result in unauthorized reading of memory outside intended buffer boundaries, leading to high confidentiality impact (sensitive data exposure) and high availability impact (potential crash or denial of service), with no direct integrity impact per the CVSS v3.1 assessment (Red Hat CVE). Applications embedding rLottie for Lottie animation rendering — including potentially mobile, desktop, and embedded applications — are at risk of information disclosure or crash when processing attacker-controlled animation files. The vulnerability is related to CAPEC-540 (Overread Buffers), and lateral movement potential depends on the privilege level of the host application (ENISA EUVD).

There is no public proof-of-concept exploit and no evidence of in-the-wild exploitation at this time (Red Hat CVE). The EPSS score is approximately 0.042%, indicating a low probability of exploitation in the near term. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog. It has been detected by Nessus (plugin ID 298645) and is tracked under ENISA EUVD-2025-19537 (ENISA EUVD, Tenable).

1. Craft a malicious Lottie file: Create a specially crafted .json Lottie animation file that contains malformed gradient data, invalid layer type references, an empty frames vector, or outlier values designed to bypass the (pre-patch) missing validation checks in rLottie V0.2.
2. Deliver the file to the target: Distribute the malicious Lottie file via a network channel — for example, embedding it in a web application, messaging platform, or any service that renders Lottie animations using the vulnerable rLottie library.
3. Trigger parsing: Cause the target application to load and parse the malicious Lottie file, invoking the vulnerable Gradient::populate() or CompLayer() code paths without bounds or type checking.
4. Achieve out-of-bounds read: The library reads memory beyond the intended buffer boundaries, potentially exposing sensitive in-process data or causing an application crash (denial of service) (GitHub PR #571).

• File System: Presence of unexpected or externally sourced .json Lottie animation files in application data directories; files with anomalous gradient, layer, or frame structures.
• Logs: Application crash logs or core dumps originating from the rLottie library (e.g., segmentation faults or access violations in lottiemodel, Gradient::populate, or CompLayer code paths).
• Process: Unexpected application crashes or restarts in software that embeds rLottie for animation rendering; abnormal memory access patterns reported by memory safety tools (e.g., AddressSanitizer output referencing rLottie).
• Network: Unusual inbound delivery of .json files or Lottie animation content from untrusted or external sources to services using rLottie V0.2.

The fix is available in the upstream rLottie repository via commit 507ea02, merged on June 11, 2025 (PR #571), which adds type checks for CompLayer(), bounds checking for Gradient::populate(), frames vector empty checks, and outlier rejection (GitHub PR #571). Downstream distributions including Debian (DLA-4474-1) and Ubuntu (USN-8058-1) have issued updated packages; users should upgrade to the patched versions provided by their distribution (Linux Security Debian, Linux Security Ubuntu). As a workaround prior to patching, restrict or disable the processing of externally sourced Lottie files, implement network segmentation to limit exposure, and monitor for suspicious animation file delivery.

Red Hat has acknowledged the vulnerability and published a CVE tracking page (Red Hat CVE). Debian and Ubuntu have issued security advisories and updated packages for their respective distributions. The vcpkg package manager community also tracked the fix, with a pull request to update the rlottie port to the patched commit referencing CVE-2025-53074 alongside related CVEs CVE-2025-0634 and CVE-2025-53075 (GitHub PR #571). No significant social media commentary or independent researcher write-ups have been identified at this time.