CVE-2026-24180: NVIDIA DALI Buffer Overflow Vulnerability

CVE-2026-24180 Overview

CVE-2026-24180 is a heap-based buffer overflow vulnerability affecting NVIDIA Data Loading Library (DALI). The flaw resides in a component that mishandles memory allocation boundaries on the heap. An attacker with local access and low privileges can trigger the overflow when a user interacts with crafted input. Successful exploitation can lead to arbitrary code execution, data tampering, denial of service, and information disclosure. The vulnerability is categorized under [CWE-122] Heap-based Buffer Overflow.

Critical Impact
Exploitation can grant attackers code execution within the DALI process context, enabling tampering with machine learning data pipelines and disclosure of sensitive training or inference data.

Affected Products

NVIDIA DALI (Data Loading Library)
Specific affected versions are listed in the NVIDIA Support Answer
GPU-accelerated machine learning workloads using DALI for data preprocessing

Discovery Timeline

2026-06-09 - CVE-2026-24180 published to NVD
2026-06-09 - Last updated in NVD database

Technical Details for CVE-2026-24180

Vulnerability Analysis

NVIDIA DALI is a GPU-accelerated library for data loading and preprocessing used in deep learning training and inference pipelines. The library handles parsing and decoding of inputs such as images, video frames, and tensors. CVE-2026-24180 stems from improper bounds enforcement when writing data into a heap-allocated buffer. When DALI processes attacker-controlled input, the affected component writes beyond the allocated region, corrupting adjacent heap metadata or data structures.

Heap corruption of this kind frequently enables attackers to overwrite function pointers, virtual table entries, or allocator control structures. The combination of high confidentiality, integrity, and availability impacts indicates that memory corruption is reachable from input parsing paths used by DALI workloads.

Root Cause

The root cause is a missing or insufficient length validation prior to a heap write operation in a DALI component, consistent with [CWE-122]. The buffer size assumptions do not match the size of attacker-supplied data, producing the overflow.

Attack Vector

The attack vector is local and requires both low-privileged access and user interaction. An attacker delivers a crafted input file or data stream that a victim processes through a DALI-based pipeline. Once the affected component parses the input, the overflow occurs in the user's process context, providing the attacker the ability to execute code or disrupt the workload.

No verified public proof-of-concept exists in the provided data. Refer to the NVIDIA Support Answer for vendor-supplied technical specifics.

Detection Methods for CVE-2026-24180

Indicators of Compromise

Unexpected crashes, segmentation faults, or heap corruption errors in processes that load libdali or invoke DALI pipelines.
Anomalous child processes or shell spawns originating from Python or training processes that import DALI.
Unusual file reads or network connections from machine learning workload hosts shortly after processing untrusted input files.

Detection Strategies

Monitor process telemetry on GPU compute hosts for DALI-linked binaries terminating abnormally or producing core dumps.
Hunt for execution chains where a data preprocessing process spawns interactive shells, scripting interpreters, or networking utilities.
Inspect ingestion pipelines for input files originating from untrusted sources before they reach DALI processing stages.

Monitoring Recommendations

Enable verbose logging of DALI pipeline failures and capture stack traces from crash artifacts for forensic review.
Forward host process and file access telemetry from ML training nodes into a centralized analytics platform for behavioral baselining.
Alert on privilege transitions or persistence mechanisms created by accounts running training and inference workloads.

How to Mitigate CVE-2026-24180

Immediate Actions Required

Apply the security update referenced in the NVIDIA Support Answer for CVE-2026-24180.
Inventory all hosts, containers, and ML workflow images that bundle NVIDIA DALI and prioritize patching of multi-tenant or shared systems.
Restrict which users can submit input files into DALI-based pipelines until updates are deployed.

Patch Information

NVIDIA has published fixed versions through its security bulletin process. Consult the NVIDIA Support Answer for affected releases and the corresponding patched DALI versions. Update DALI through your standard package manager, container base image rebuild, or Conda environment refresh, and validate that downstream training and inference jobs still function after upgrade.

Workarounds

Process only trusted, internally generated inputs through DALI pipelines until patched builds are installed.
Run DALI workloads under least-privileged service accounts inside sandboxed containers with seccomp and read-only filesystem constraints.
Disable or replace DALI components used for parsing untrusted media when an immediate patch is not feasible.

bash

# Configuration example: upgrade DALI in a Python environment after the vendor patch is released
pip install --upgrade nvidia-dali-cuda120
python -c "import nvidia.dali as dali; print(dali.__version__)"