CVE-2026-65172 in AIStore
Summary
by MITRE • 10/13/2026
NVIDIA AIStore for Linux and Kubernetes contains a missing authorization vulnerability in the ETL management API where an unauthenticated remote attacker may access ETL information or control existing ETL jobs by sending crafted GET or POST requests to an AIStore proxy.
A successful exploit may lead to information disclosure and unauthorized start or stop operations that affect the integrity and availability of ETL data-processing pipelines.
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Analysis
by VulDB Data Team • 10/13/2026
The vulnerability identified in NVIDIA AIStore for Linux and Kubernetes represents a critical failure in access control mechanisms within the Extract, Transform, Load management API. This flaw allows unauthenticated remote attackers to interact with sensitive administrative endpoints without providing valid credentials or authentication tokens. The core technical issue lies in the absence of proper authorization checks on specific HTTP methods directed at the ETL proxy interface. By sending crafted GET requests, an attacker can retrieve internal configuration details and status information regarding active data processing pipelines. Furthermore, by issuing POST requests to control points within this API, a malicious actor gains the ability to initiate new extraction jobs or terminate existing ones arbitrarily. This lack of enforcement means that any entity with network connectivity to the AIStore proxy port can manipulate the state of the distributed storage system's data ingestion layer.
The operational impact of this vulnerability is severe due to its direct effect on both confidentiality and availability within the data infrastructure. The ability to access ETL information exposes sensitive metadata about the organization’s data pipelines, potentially revealing schema structures, source endpoints, or processing logic that could aid in further targeted attacks against downstream systems. More critically, the capacity to start or stop ETL jobs disrupts the integrity of data-processing workflows. Unauthorized termination of running jobs can lead to incomplete data transfers, corrupted datasets, and significant downtime for applications relying on real-time or batch data availability. In a Kubernetes environment where AIStore often serves as high-performance storage for machine learning workloads, such disruptions can halt model training processes, delay inference pipelines, and cause cascading failures across dependent microservices that expect consistent data availability.
From a threat modeling perspective, this vulnerability aligns with CWE-862 Missing Authorization, which describes the failure to enforce access controls on resources or functions for specific actors. The exploitation technique maps directly to MITRE ATT&CK techniques involving unauthorized API access and potential denial of service through resource manipulation. Attackers can leverage standard web tools to craft requests that bypass security boundaries, exploiting the trust placed in internal network segments where AIStore proxies are often deployed without strict ingress filtering or mutual TLS enforcement for administrative interfaces. The risk is amplified by the fact that ETL operations are central to data integrity; compromising them undermines the reliability of the entire analytics and artificial intelligence stack built upon NVIDIA’s infrastructure.
Mitigation strategies must focus on immediate access restriction followed by long-term architectural hardening. Administrators should immediately restrict network-level access to the AIStore proxy ports, ensuring they are not exposed to untrusted networks or the public internet. Implementing firewall rules that limit connectivity to only known management IPs is a critical first step. Additionally, enabling authentication mechanisms for all API endpoints is essential; if native support exists within the specific version of NVIDIA AIStore being used, it must be configured and enforced strictly. For environments where immediate patching is not feasible, deploying a Web Application Firewall or an ingress controller with strict access control lists can provide a temporary buffer against unauthorized requests. Long-term remediation requires upgrading to patched versions of NVIDIA AIStore that enforce role-based access controls on the ETL management API. Regular security audits and penetration testing should be conducted to verify that administrative interfaces remain isolated from unauthenticated traffic, ensuring compliance with industry standards for secure software development and infrastructure protection.