Skip to main content
CVE Vulnerability Database
Vulnerability Database/CVE-2026-19518

CVE-2026-19518: Samsung rlottie Input Validation Flaw

CVE-2026-19518 is an input validation vulnerability in Samsung Open Source rlottie that enables input data manipulation attacks. This article covers the technical details, affected versions, impact, and mitigation.

Published:

CVE-2026-19518 Overview

CVE-2026-19518 is an Improper Validation of Specified Quantity in Input vulnerability [CWE-1284] in Samsung Open Source rlottie, a library used to render Lottie animations from JSON payloads. An attacker can craft a malicious Lottie animation file that manipulates input data parsing and triggers a high-impact availability condition in the consuming application. Exploitation requires user interaction, such as opening or previewing a crafted animation, but does not require authentication. The flaw affects any product that embeds vulnerable versions of rlottie for animation rendering.

Critical Impact

A remote attacker can crash applications or services that render untrusted Lottie animations by delivering a malformed input file, causing denial of service on the host process.

Affected Products

  • Samsung Open Source rlottie (versions prior to the fix merged in GitHub Pull Request #596)
  • Downstream applications and frameworks embedding rlottie for Lottie animation rendering
  • Mobile, desktop, and embedded software distributing the vulnerable library

Discovery Timeline

  • 2026-08-11 - CVE-2026-19518 published to the National Vulnerability Database (NVD)
  • 2026-08-11 - Last updated in NVD database

Technical Details for CVE-2026-19518

Vulnerability Analysis

The vulnerability is categorized under [CWE-1284]: Improper Validation of Specified Quantity in Input. The rlottie parser accepts a quantity value from an input Lottie JSON file and uses it without verifying that the declared quantity matches the actual data supplied or fits within safe bounds. When the parser processes the crafted animation, downstream logic operates on inconsistent counts and terminates the process abnormally, producing an availability impact on the host application.

The attack is network-reachable because Lottie files are commonly delivered through web content, chat messages, application updates, and asset bundles. User interaction is required, typically by viewing or rendering the animation. Confidentiality and integrity are not affected.

Root Cause

The root cause is missing validation between a declared element count in the Lottie input and the number of elements actually present or allowed by the runtime. Without a bounds check, allocation or iteration logic in rlottie executes on attacker-controlled quantities, leading to a crash. The upstream fix is tracked in Samsung rlottie Pull Request #596.

Attack Vector

An attacker hosts or delivers a malformed Lottie JSON animation. When a victim application parses the file through a vulnerable rlottie build, the process crashes. Delivery paths include web pages, messaging attachments, in-app content feeds, and any pipeline that renders third-party animation assets.

No proof-of-concept exploit code is publicly available. Refer to the upstream patch in Samsung rlottie Pull Request #596 for the technical fix.

Detection Methods for CVE-2026-19518

Indicators of Compromise

  • Repeated crashes or unexpected termination of processes that load rlottie after opening animation content.
  • Application crash telemetry referencing rlottie parsing functions or Lottie JSON handlers.
  • Inbound Lottie JSON files from untrusted sources with abnormally large or inconsistent element counts.

Detection Strategies

  • Inventory applications and container images that link against rlottie and compare versions to the fixed commit in Pull Request #596.
  • Enable crash reporting on client and server endpoints that render Lottie content and alert on repeated faults in animation rendering modules.
  • Inspect Lottie JSON files at the gateway for structural anomalies, including declared counts that exceed reasonable rendering limits.

Monitoring Recommendations

  • Monitor process stability metrics for applications that display user-supplied animations.
  • Log and centralize crash dumps to identify clusters of failures tied to specific animation payloads.
  • Track software bill of materials (SBOM) entries for rlottie across build pipelines to catch reintroduction of vulnerable versions.

How to Mitigate CVE-2026-19518

Immediate Actions Required

  • Update rlottie to a version containing the fix from Samsung rlottie Pull Request #596.
  • Rebuild and redeploy downstream applications, mobile apps, and container images that statically or dynamically link the library.
  • Restrict rendering of Lottie animations sourced from untrusted origins until patched builds are in production.

Patch Information

The upstream fix is available in the Samsung rlottie repository via Pull Request #596. Downstream vendors that ship rlottie should incorporate the patched commit and issue updated builds. Application maintainers should confirm the linked library version during release validation.

Workarounds

  • Disable or gate features that render Lottie animations from external or user-submitted sources until the patch is deployed.
  • Validate incoming Lottie JSON files at an application gateway and reject files with unreasonable element counts or malformed structure.
  • Isolate rendering of untrusted animations in a sandboxed process so a crash does not affect the parent application.
bash
# Example: verify the rlottie version linked into a build
ldd ./your_app | grep rlottie
strings $(ldd ./your_app | awk '/rlottie/ {print $3}') | grep -i version

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

Default Legacy - Prefooter | Experience the World’s Most Advanced Cybersecurity Platform

Experience the Most Advanced Cybersecurity Platform

See how the world’s most intelligent, autonomous cybersecurity platform can protect your organization today and into the future.