CVE-2026-82797 in rlottie
Summary
by MITRE • 08/31/2026
Uncontrolled Recursion vulnerability in Samsung Open Source rlottie allows Serialized Data with Nested Payloads.
This issue affects rlottie: before 8de0d9e6ca80ffef654965505981727b9fa06a51.
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Analysis
by VulDB Data Team • 08/31/2026
The vulnerability identified in Samsung Open Source rlottie represents a critical uncontrolled recursion flaw that arises during the processing of serialized data containing nested payloads. Rlottie is a high-performance library designed to render Lottie animations, which are typically defined using JSON-based serialization formats. These files often contain complex hierarchical structures representing vector graphics, timelines, and effects. When the parser encounters deeply nested or recursively structured data within these animation definitions, it fails to enforce adequate depth limits or cycle detection mechanisms. This oversight allows an attacker to craft a maliciously constructed Lottie file that triggers infinite or excessively deep recursive function calls during the parsing phase. The issue specifically affects versions of rlottie prior to commit 8de0d9e6ca80ffef654965505981727b9fa06a51, where this logic was not properly constrained against pathological input structures.
From a technical perspective, the core flaw lies in the recursive descent parser used to interpret the JSON-like structure of Lottie animations. When the library processes nested objects or arrays without verifying structural depth limits, it consumes stack space exponentially with each level of nesting. This behavior aligns directly with Common Weakness Enumeration category CWE-675, which describes operations on data with insufficiently restricted recursion levels. The lack of a maximum depth counter means that even moderately complex but intentionally malformed inputs can exhaust the available call stack memory allocated to the application thread. In environments where rlottie is embedded within mobile applications or desktop software, this resource exhaustion manifests as a denial of service condition rather than remote code execution, although in some specific runtime configurations with unsafe pointer arithmetic nearby, it could potentially lead to further exploitation vectors such as buffer overflows if heap corruption occurs due to stack overflow side effects.
The operational impact of this vulnerability is primarily centered on application stability and availability. An attacker who can supply a crafted Lottie animation file through any input vector that feeds into the rlottie parser can cause the host application to crash or become unresponsive. This denial of service effect disrupts user experience and may lead to data loss if unsaved work is present in the affected application. For services that process user-uploaded animations, this vulnerability could be leveraged for distributed denial-of-service attacks against backend processing pipelines. Furthermore, because Lottie files are often embedded directly into mobile applications or web pages, an attacker does not necessarily need direct network access to exploit this flaw; social engineering tactics such as sending a malicious animation file via messaging apps can trigger the vulnerability on the recipient's device. This increases the attack surface significantly compared to vulnerabilities requiring specific server-side configurations.
Mitigation strategies must focus on both immediate patching and long-term defensive coding practices. The primary remediation is to upgrade rlottie to version 8de0d9e6ca80ffef654965505981727b9fa06a51 or later, where the developers have implemented safeguards against uncontrolled recursion. For applications unable to update immediately, implementing a custom parser wrapper that enforces strict depth limits on nested structures is recommended. This involves tracking the current nesting level during parsing and aborting processing if a predefined threshold is exceeded. Additionally, integrating fuzz testing into the development pipeline can help identify similar structural weaknesses before they reach production. Security teams should also monitor for new CVEs related to JSON parsers in general, as this class of vulnerability is common across many serialization libraries.
In terms of threat intelligence and industry standards, this vulnerability maps to MITRE ATT&CK technique T1496, which covers Resource Hijacking through denial-of-service methods that consume system resources like CPU or memory. By exhausting the stack space, the attacker effectively hijacks computational resources for malicious purposes. Defense-in-depth measures should include deploying input validation rules at the network perimeter if rlottie is used in server-side rendering contexts, and ensuring that mobile applications sandbox their animation processing components to limit the blast radius of a potential crash. Regular security audits focusing on recursive algorithms in parsing logic are essential to prevent recurrence of CWE-675 type issues across all software components handling untrusted serialized data.