Dali
Monthly
Heap-based buffer overflow in NVIDIA DALI enables local authenticated attackers to achieve code execution, data tampering, denial of service, or information disclosure when a victim user interacts with attacker-supplied input. The flaw affects the Data Loading Library used in GPU-accelerated deep learning data pipelines and carries a CVSS 3.1 score of 7.3 (High). No public exploit identified at time of analysis and the issue is not listed in CISA KEV.
Local code execution and data tampering in NVIDIA DALI (Data Loading Library) is possible when a low-privileged user is tricked into processing attacker-controlled input through a component that performs improper index validation (CWE-129). The CVSS 7.3 vector (AV:L/AC:L/PR:L/UI:R) indicates local access, low privileges, and user interaction are required, with high impact across confidentiality, integrity, and availability. No public exploit identified at time of analysis and the issue is not listed in CISA KEV.
Arbitrary code execution in NVIDIA DALI (all versions prior to 2.0) allows local authenticated attackers with low privileges to execute malicious code by exploiting insecure deserialization of untrusted data, requiring user interaction. EPSS exploitation probability and KEV status data not available; no public exploit identified at time of analysis. The vulnerability affects NVIDIA's Data Loading Library, a critical component in AI/ML data preprocessing pipelines.
Heap-based buffer overflow in NVIDIA DALI enables local authenticated attackers to achieve code execution, data tampering, denial of service, or information disclosure when a victim user interacts with attacker-supplied input. The flaw affects the Data Loading Library used in GPU-accelerated deep learning data pipelines and carries a CVSS 3.1 score of 7.3 (High). No public exploit identified at time of analysis and the issue is not listed in CISA KEV.
Local code execution and data tampering in NVIDIA DALI (Data Loading Library) is possible when a low-privileged user is tricked into processing attacker-controlled input through a component that performs improper index validation (CWE-129). The CVSS 7.3 vector (AV:L/AC:L/PR:L/UI:R) indicates local access, low privileges, and user interaction are required, with high impact across confidentiality, integrity, and availability. No public exploit identified at time of analysis and the issue is not listed in CISA KEV.
Arbitrary code execution in NVIDIA DALI (all versions prior to 2.0) allows local authenticated attackers with low privileges to execute malicious code by exploiting insecure deserialization of untrusted data, requiring user interaction. EPSS exploitation probability and KEV status data not available; no public exploit identified at time of analysis. The vulnerability affects NVIDIA's Data Loading Library, a critical component in AI/ML data preprocessing pipelines.