CVE-2026-25281 in Snapdragon Compute
Summary
by MITRE • 09/17/2026
Transient DOS when processing large or numerous request buffers without sufficient memory allocation validation.
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Analysis
by VulDB Data Team • 09/17/2026
The vulnerability described represents a transient Denial of Service condition arising from insufficient validation during the handling of input data, specifically within contexts involving large or numerous request buffers. This flaw is fundamentally rooted in CWE-400, which classifies uncontrolled resource consumption as a critical category of software weakness. When an application processes incoming network requests, it must allocate memory to store and manipulate the received data. In this scenario, the system fails to adequately verify whether the requested buffer size or the volume of concurrent buffers is within acceptable limits before proceeding with allocation. This lack of validation allows external actors to trigger excessive resource consumption by sending specially crafted payloads that demand disproportionately large amounts of system memory relative to their actual utility or intended function.
From a technical perspective, this issue often manifests when developers assume that input data will always be well-formed and reasonably sized. Instead of implementing strict size limits or validating the total memory footprint required for processing multiple buffers simultaneously, the application proceeds with dynamic allocation based on untrusted input values. If an attacker submits requests containing extremely large payloads or floods the system with a high volume of moderately sized but numerous buffer allocations, the underlying operating system may struggle to satisfy these demands. This can lead to memory exhaustion, where the process consumes all available heap space or triggers swap file thrashing, effectively freezing the application's ability to respond to legitimate traffic. The transient nature of this denial of service implies that while the impact is severe during the attack window, normal operations may resume once the malicious requests cease and garbage collection or system-level memory reclamation occurs, though repeated attacks can cause persistent instability or require manual intervention such as process restarts.
The operational impact of this vulnerability extends beyond simple unavailability. In high-throughput environments, such as web servers or API gateways, a transient DoS event caused by buffer exhaustion can lead to cascading failures across dependent services. Load balancers may mark the affected instance as unhealthy due to increased latency and timeout errors, potentially causing traffic redistribution that overwhelms remaining healthy nodes. Furthermore, if the application runs with elevated privileges or handles sensitive data during processing, the instability introduced by memory pressure could theoretically expose side-channel vulnerabilities or lead to partial data corruption in edge cases where allocation failures result in undefined behavior rather than clean error handling. This aligns with ATT&CK technique T1498, Network Denial of Service, specifically sub-techniques involving resource exhaustion through volumetric attacks or application-layer flooding that targets specific service capabilities rather than network bandwidth alone.
Mitigation strategies must focus on implementing robust input validation and resource management controls at the earliest possible stage in the request processing pipeline. Developers should enforce strict maximum size limits for individual buffer allocations, ensuring that no single request can consume an disproportionate amount of memory relative to system capacity. Additionally, rate limiting mechanisms should be deployed to restrict the number of concurrent requests or the frequency of incoming connections from a single source IP address, thereby preventing rapid accumulation of numerous small buffers that collectively exhaust resources. It is also critical to implement graceful degradation strategies where the application can detect impending resource exhaustion and reject new requests with appropriate HTTP status codes such as 413 Payload Too Large or 503 Service Unavailable before memory limits are breached. Regular stress testing using tools designed to simulate high-volume, multi-buffer scenarios will help identify these weaknesses in pre-production environments, ensuring that the application remains resilient against attempts to manipulate resource allocation logic for malicious purposes.