CVE-2026-19517 in rlottie
Summary
by MITRE • 08/11/2026
Improper Validation of Specified Quantity in Input and Allocation of Resources Without Limits or Throttling vulnerability in Samsung Open Source rlottie allows Excessive Allocation.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Analysis
by VulDB Data Team • 08/11/2026
The vulnerability under discussion represents a critical resource management flaw within Samsung's open source rlottie library, which is widely used for rendering vector graphics and animations in various applications. This issue manifests as an improper validation of specified quantities in input data, specifically when processing animation parameters that define the number of elements to be allocated or rendered. The weakness stems from insufficient bounds checking and resource allocation limits within the library's parsing logic, allowing malicious or malformed input to trigger excessive memory consumption and system resource exhaustion.
This vulnerability falls under the broader category of CWE-705 Improper Validation of Specified Quantity in Input and Allocation of Resources Without Limits or Throttling, which directly maps to common attack patterns found in the MITRE ATT&CK framework under TA0004 Privilege Escalation and TA0005 Defense Evasion. The flaw enables attackers to craft specially formatted animation files or data structures that cause the rlottie library to allocate excessive memory resources without proper throttling mechanisms. When an application utilizing this library processes such inputs, the system may experience significant performance degradation, denial of service conditions, or even complete system crashes due to resource exhaustion.
The operational impact of this vulnerability extends beyond simple performance issues, as it can be leveraged in various attack scenarios including remote code execution when combined with other vulnerabilities, or as a denial of service vector in applications that process untrusted animation content. Applications using rlottie for rendering user-generated content, such as mobile apps, web browsers, or media players, become particularly vulnerable to exploitation. The lack of input validation means that legitimate users or malicious actors can submit animation parameters that cause the library to allocate memory in exponentially growing patterns, potentially leading to system instability and resource exhaustion attacks that can affect entire application suites.
Mitigation strategies should focus on implementing robust input validation mechanisms within the rlottie library itself, including setting hard limits on allocation parameters and implementing proper resource throttling controls. Organizations should ensure all applications using rlottie are updated to patched versions that include bounds checking and memory allocation limits. Additionally, deploying network-level protections such as rate limiting and input sanitization at application boundaries can help prevent exploitation attempts. Security monitoring should be implemented to detect unusual memory consumption patterns or resource allocation spikes that may indicate exploitation attempts, while regular vulnerability assessments should be conducted to identify similar issues in other third-party libraries and components.