CVE-2026-100647 in vLLM
Summary
by MITRE • 09/26/2026
vLLM versions before 0.29.0 contain a denial-of-service vulnerability in the cache_salt parameter accepted on OpenAI-compatible and Anthropic API endpoints, which lacks maximum length validation and is processed on the single EngineCore scheduler thread. Unauthenticated attackers can send HTTP requests with multi-hundred-megabyte salt values that trigger expensive pickle serialization and SHA-256 hashing, stalling the scheduler thread and denying service to all concurrent requests.
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Analysis
by VulDB Data Team • 09/26/2026
The vulnerability identified in vLLM versions prior to 0.29.0 represents a critical denial-of-service flaw rooted in insufficient input validation within the cache_salt parameter handling logic. This security issue affects both OpenAI-compatible and Anthropic API endpoints, which are commonly used for integrating large language model inference services into broader applications. The core technical deficiency lies in the absence of maximum length constraints on the salt value provided by clients during request initialization. Because this parameter is processed directly without size limitations, it allows unauthenticated attackers to inject excessively large payloads, specifically multi-hundred-megabyte strings, into the system's processing pipeline.
From an operational perspective, the impact of this vulnerability is severe due to the architectural design of vLLM’s scheduling mechanism. The cache_salt value undergoes expensive computational operations, including pickle serialization and SHA-256 hashing, which are resource-intensive tasks. Crucially, these operations are executed on a single EngineCore scheduler thread that manages request dispatching for all concurrent inference jobs. When an attacker submits a request with a massive salt value, the CPU cycles required to serialize and hash this data monopolize the scheduler thread. This creates a blocking condition where the thread becomes unresponsive, effectively halting the processing of any other pending or incoming requests.
The consequence is a complete denial of service for all users interacting with the vLLM instance. Legitimate clients experience significant latency increases or total request failures because the scheduler cannot dispatch new inference tasks while it is stuck processing the malicious payload. This vulnerability exploits the single-threaded nature of critical scheduling components, turning a standard input validation oversight into a systemic availability failure. It aligns with CWE-20 Improper Input Validation and CWE-400 Uncontrolled Resource Consumption, as the system fails to restrict resource usage based on untrusted input size. Furthermore, this attack vector is consistent with ATT&CK technique T1496 Resource Hijacking, where an adversary consumes computational resources to degrade service availability for legitimate users.
Mitigation strategies must focus on enforcing strict limits on incoming request parameters and implementing robust validation layers before data reaches the core processing engine. Upgrading to vLLM version 0.29.0 or later is the primary remediation step, as these versions address the lack of maximum length validation in the cache_salt parameter. In environments where immediate upgrading is not feasible, deploying a reverse proxy or API gateway with request size limits can provide an additional layer of defense by truncating or rejecting payloads that exceed defined thresholds before they reach the vLLM service. Additionally, implementing rate limiting and monitoring for unusually large header values or body sizes can help detect and block such attempts proactively.