ZDI-25-1013 - NVIDIA AIStore hard-coded credentials flaw

ZDI-25-1013 describes a critical authentication bypass vulnerability in NVIDIA AIStore where hard-coded credentials in the AuthN mechanism allow remote attackers to access the system without valid user accounts. Because authentication is not required to exploit the flaw, a network-adjacent attacker can leverage the embedded credentials to impersonate trusted services or administrative users, effectively bypassing access controls around sensitive AI data stores. This behavior aligns with MITRE ATT&CK technique T1078 (Valid Accounts) and T1190 (Exploit Public-Facing Application) when AIStore is exposed through web APIs or management endpoints. Once an attacker gains access via the hard-coded AuthN channel, they can interact with AIStore as an authorized client or administrator, potentially enumerating buckets, exfiltrating stored models and datasets, or modifying configuration used by downstream AI workloads. In environments where AIStore underpins training pipelines or inference services, such access can be abused to poison training data, swap models with trojanized variants or stage data for lateral movement into adjacent storage systems, intersecting with T1039 (Data from Network Shared Drive) and T1041 (Exfiltration Over C2 Channel). The fact that credentials are compiled into the software rather than managed through a directory or secret store makes them difficult for defenders to rotate or revoke. For enterprises experimenting with or deploying NVIDIA AI infrastructure, compromise of AIStore threatens both intellectual property and operational reliability. Stolen models and proprietary datasets can undermine competitive advantage, while subtle manipulation of training corpora or parameters can degrade model outputs without obvious signs of tampering. In regulated industries, data exfiltration from AIStore may involve personal or financial information, triggering GDPR, HIPAA or PCI-DSS obligations if training data contains customer records or transaction histories. Organizations should treat ZDI-25-1013 as a design-level security issue and prioritize vendor patches or configuration changes that remove or disable the hard-coded credential path. Until a fixed release is deployed, security teams should restrict network access to AIStore through segmentation and zero trust controls, enforce mutual TLS where possible and instrument logging around all AIStore API activity to detect anomalous access patterns. Longer term, buyers should pressure vendors to adopt secure credential management practices, including integration with enterprise identity providers and secrets vaults rather than embedding static credentials into AI infrastructure components.