CVE-2025-33252: Nvidia Nemo Framework RCE Vulnerability

CVE-2025-33252 Overview

CVE-2025-33252 affects the NVIDIA NeMo Framework, a toolkit for building and training generative AI models. The vulnerability stems from unsafe deserialization of data [CWE-502], allowing an authenticated local attacker to trigger code execution within the framework process.

A successful exploit can lead to code execution, denial of service, information disclosure, and data tampering. NVIDIA published an advisory describing the issue and providing remediation guidance through the NVIDIA Support Answer.

Critical Impact

An attacker with local access and low privileges can execute arbitrary code in the context of the NeMo Framework, compromising confidentiality, integrity, and availability of AI workloads.

Affected Products

• NVIDIA NeMo Framework (all versions prior to the fixed release referenced in the vendor advisory)
• Deployments running nvidia:nemo components on Linux training and inference hosts
• Containerized NeMo workloads consuming untrusted model artifacts or checkpoints

Discovery Timeline

• 2026-02-18 - CVE-2025-33252 published to NVD
• 2026-02-20 - Last updated in NVD database

Technical Details for CVE-2025-33252

Vulnerability Analysis

The flaw is classified as Insecure Deserialization [CWE-502]. NeMo Framework loads serialized objects, such as model checkpoints or configuration artifacts, without sufficient validation of the embedded object graph. When the deserializer reconstructs the object, attacker-controlled gadgets execute within the Python runtime hosting NeMo.

The attack vector is local with low attack complexity and requires low privileges. No user interaction is needed, and the impact spans confidentiality, integrity, and availability. The exploit prediction (EPSS) probability is currently 0.19%, indicating limited observed exploitation activity in the wild.

NVIDIA notes the consequences include code execution, denial of service, information disclosure, and data tampering. Practical exposure is highest in multi-tenant ML platforms where users share file systems or submit external model artifacts to a NeMo training job.

Root Cause

The root cause is unsafe handling of serialized Python objects, typically through libraries such as pickle or framework-level checkpoint loaders. The deserializer trusts the source of the serialized blob and reconstructs arbitrary classes without an allowlist or signature verification.

Attack Vector

An attacker first obtains local, low-privileged access to a host running the NeMo Framework. The attacker then places a malicious checkpoint, configuration file, or dataset where NeMo will deserialize it. When the framework loads the crafted artifact, embedded callable objects execute, granting the attacker the privileges of the NeMo process.

No verified public proof-of-concept code is available. The vulnerability mechanism follows the standard deserialization gadget pattern documented in the NVD entry for CVE-2025-33252.

Detection Methods for CVE-2025-33252

Indicators of Compromise

• Unexpected child processes spawned by Python interpreters running NeMo training or inference scripts
• NeMo processes initiating outbound network connections to unknown hosts shortly after loading a checkpoint
• New or modified .ckpt, .nemo, or .pkl files in shared model directories from untrusted users
• Shell invocations (/bin/sh, /bin/bash) originating from python processes tied to NeMo workloads

Detection Strategies

• Monitor process lineage for Python interpreters spawning shells or interpreters not used by legitimate training workflows
• Audit file system access for NeMo workloads loading checkpoints from world-writable or user-controlled paths
• Apply YARA or content scanning against incoming model artifacts to flag embedded __reduce__ or os.system patterns common to pickle exploits

Monitoring Recommendations

• Enable Linux auditd rules on directories containing NeMo checkpoints and configuration files
• Forward Python application logs and host telemetry to a centralized SIEM for correlation
• Track GPU host integrity baselines and alert on deviation in installed packages or scheduled tasks

How to Mitigate CVE-2025-33252

Immediate Actions Required

• Upgrade NeMo Framework to the fixed version listed in the NVIDIA Support Answer
• Restrict local access to NeMo hosts to trusted operators and service accounts only
• Audit existing checkpoint and configuration directories for files supplied by untrusted users

Patch Information

NVIDIA has published remediation guidance and a fixed release through its security bulletin portal. Refer to the NVIDIA Support Answer for CVE-2025-33252 for affected versions, fixed versions, and upgrade instructions. Apply the vendor-supplied patch on all hosts running NeMo before resuming workloads.

Workarounds

• Load model artifacts only from trusted, signed sources and verify integrity hashes before deserialization
• Run NeMo workloads in isolated containers with read-only file systems and least-privilege service accounts
• Disable or sandbox pickle-based checkpoint loading where the framework offers safer alternatives such as safetensors

# Configuration example: restrict checkpoint loading to a trusted directory
chown -R nemo:nemo /opt/nemo/checkpoints
chmod 750 /opt/nemo/checkpoints
find /opt/nemo/checkpoints -type f -exec sha256sum {} \; > /opt/nemo/checkpoints.sha256