CVE-2025-33245: NVIDIA NeMo Framework RCE Vulnerability

CVE-2025-33245 Overview

CVE-2025-33245 is an insecure deserialization vulnerability in the NVIDIA NeMo Framework that allows attackers to achieve remote code execution through malicious data injection. The NeMo Framework is NVIDIA's conversational AI toolkit used for developing and training speech and language models. A successful exploit of this vulnerability could lead to code execution, escalation of privileges, information disclosure, and data tampering within affected environments.

Critical Impact
This vulnerability enables remote code execution through malicious data processing, potentially allowing attackers to completely compromise systems running the NVIDIA NeMo Framework with full code execution, privilege escalation, and data manipulation capabilities.

Affected Products

NVIDIA NeMo Framework (versions prior to patched release)

Discovery Timeline

2026-02-18 - CVE-2025-33245 published to NVD
2026-02-18 - Last updated in NVD database

Technical Details for CVE-2025-33245

Vulnerability Analysis

This vulnerability stems from insecure deserialization (CWE-502) within the NVIDIA NeMo Framework. Deserialization vulnerabilities occur when an application processes serialized data from untrusted sources without adequate validation. In the context of the NeMo Framework, an attacker can craft malicious serialized objects that, when deserialized by the application, execute arbitrary code on the target system.

The attack requires network access and low privileges with some user interaction, but successful exploitation results in complete compromise of confidentiality, integrity, and availability of the affected system. Given NeMo's role in AI/ML pipelines, this vulnerability could potentially compromise training data, model weights, and inference results.

Root Cause

The root cause of CVE-2025-33245 is improper handling of serialized data within the NeMo Framework. The application fails to adequately validate or sanitize serialized objects before deserialization, allowing attackers to inject malicious payloads. Python-based ML frameworks like NeMo commonly use serialization formats such as pickle for model checkpoints and data storage, which are inherently unsafe when processing untrusted input.

Attack Vector

The attack is network-based, requiring an attacker to submit specially crafted malicious data to a vulnerable NeMo Framework instance. The exploitation path involves:

Attacker identifies a NeMo Framework endpoint that accepts serialized data
Attacker crafts a malicious serialized payload containing code execution primitives
The payload is submitted to the target system via network request
The NeMo Framework deserializes the payload without proper validation
Malicious code executes with the privileges of the NeMo process

The vulnerability requires low privileges and user interaction, suggesting the attack may involve loading malicious model files or training data that an authenticated user processes.

Detection Methods for CVE-2025-33245

Indicators of Compromise

Unexpected process spawning from NeMo Framework Python processes
Unusual network connections originating from ML training or inference workloads
Suspicious file system modifications in NeMo model directories or checkpoint storage
Anomalous system calls from Python processes associated with NeMo Framework

Detection Strategies

Monitor for unusual deserialization patterns in NeMo Framework logs and application telemetry
Implement file integrity monitoring for model checkpoints and serialized data files
Deploy network monitoring to detect exfiltration attempts from NeMo-based systems
Use endpoint detection to identify suspicious child process creation from Python runtimes

Monitoring Recommendations

Enable verbose logging for NeMo Framework applications to capture deserialization events
Monitor for pickle.loads() or similar deserialization calls processing external data
Implement runtime application self-protection (RASP) for Python-based ML workloads
Track network traffic patterns for NeMo Framework services to identify anomalous data ingestion

How to Mitigate CVE-2025-33245

Immediate Actions Required

Review all NeMo Framework deployments and identify exposed instances
Restrict network access to NeMo Framework services to trusted sources only
Audit and validate all model checkpoints and serialized data files from external sources
Apply the vendor security patch as soon as available from NVIDIA

Patch Information

NVIDIA has released a security advisory addressing this vulnerability. Organizations should consult the NVIDIA Support Article for official patch information and upgrade instructions. Apply the latest NeMo Framework version that includes the security fix to remediate this vulnerability.

Workarounds

Implement network segmentation to isolate NeMo Framework instances from untrusted networks
Validate and sanitize all serialized data before processing with NeMo Framework
Avoid loading model checkpoints or training data from untrusted sources
Consider using safer serialization formats like safetensors instead of pickle where supported

bash

# Configuration example - Network isolation for NeMo Framework
# Restrict NeMo services to internal network only using iptables
iptables -A INPUT -p tcp --dport 5000 -s 10.0.0.0/8 -j ACCEPT
iptables -A INPUT -p tcp --dport 5000 -j DROP

# Alternatively, bind NeMo services to localhost only
export NEMO_HOST=127.0.0.1