Preface: The attached diagram illustrates how an attacker could trigger the CVE-2026-24180 and CVE-2026-24181 vulnerabilities. This diagram serves as a visual aid for threat modeling, dividing the attack vector into two main paths within the NVIDIA Data Load Library (DALI) data processing pipeline.
Background: As shown in the figure, the following detailed information explains how this vulnerability occurred.
1. The Deserialization Vector (The “Pickle Bomb”)
Sections 4 and 5 of the diagram map out how an attacker executes arbitrary code using insecure data parsing:
•The Vulnerability Layer: When DALI processes batches or training checkpoints, it relies on Python’s built-in pickle.loads() function to reconstruct data objects.
•The Exploit Execution: An attacker supplies a maliciously crafted dataset or checkpoint file containing a specialized payload. As shown in the code snippet, when pickle.loads() evaluates the serialized byte stream, it invokes the native Python __reduce__ method. This allows the attacker to step outside the memory sandbox and automatically run system commands with the host program’s privileges.
2. The Memory Boundary Vector (Heap Buffer Overflow)
Sections 2 and 3 explain how memory corruption occurs on the backend during media loading:
•The Vulnerability Layer: DALI leverages CPU/GPU-accelerated multimedia codecs (like libjpeg-turbo and nvJPEG) to pre-parse incoming audio tracks and JPEG image segments.
•The Exploit Execution: The software lacks strict bounds validation for input structures. An attacker passes a specialized file containing mutated headers, altered dimensions, or oversized network packets. Because the system does not verify these bounds, the file metadata triggers an integer or buffer mismatch, forcing data to overrun the allocated limits of the heap memory sector. This results in an out-of-bounds write or read sequence, compromising the stability of downstream frameworks like PyTorch, TensorFlow, or MXNet.
Furthermore, a heap-based buffer overflow in a data loading library is almost always caused by improper data validation. It occurs when the library fails to check input bounds—such as when processing image files, network packets, or file headers—allowing crafted data to exceed the allocated heap buffer’s capacity and overwrite adjacent memory.
Vulnerability details:
CVE-2026-24180 NVIDIA DALI contains a vulnerability in a component where an attacker could cause a heap-based buffer overflow. A successful exploit of this vulnerability might lead to code execution, data tampering, denial of service, and information disclosure.
CVE-2026-24181 NVIDIA DALI contains a vulnerability in a component where an attacker could cause an improper index validation. A successful exploit of this vulnerability might lead to code execution, data tampering, denial of service, and information disclosure.
Official announcement: Please refer to the link for details – https://nvidia.custhelp.com/app/answers/detail/a_id/5814