CVE-2026-24157: 
Python vulnerability analysis and mitigation

CVE-2026-24157 is a deserialization of untrusted data vulnerability in the NVIDIA NeMo Framework's checkpoint loading functionality that enables remote code execution. It affects all versions of NVIDIA NeMo prior to 2.6.2. The vulnerability was disclosed on March 24, 2026, with a patch released shortly after. NVD assigned a CVSS v3.1 base score of 9.8 (Critical), while NVIDIA's own CNA scoring assigned 7.8 (High) using a local attack vector (Feedly, NVIDIA Advisory).

The root cause is improper deserialization of untrusted data (CWE-502) during checkpoint loading in the NVIDIA NeMo Framework, a toolkit used for building large-scale AI and machine learning models. An attacker can supply a maliciously crafted checkpoint file that, when loaded by the framework, triggers arbitrary code execution through unsafe deserialization — a technique mapped to CAPEC-586 (Object Injection). NVD's analysis assigns a network-based attack vector with no privileges or user interaction required, though NVIDIA's own scoring reflects a local attack vector, suggesting exploitation may depend on how checkpoint files are ingested (e.g., via network-accessible model repositories or APIs) (Feedly, NVIDIA Advisory).

Successful exploitation can result in remote code execution, escalation of privileges, information disclosure, and data tampering on systems running vulnerable versions of NVIDIA NeMo Framework. Given that NeMo is commonly deployed in AI/ML training and inference pipelines — often with access to sensitive model weights, datasets, and infrastructure — a compromise could expose proprietary data and enable lateral movement within the broader environment. The vulnerability requires no user interaction and no prior privileges under NVD's assessment, making it highly impactful in exposed deployments (Feedly).

As of the time of reporting, there is no public proof-of-concept exploit and no confirmed evidence of in-the-wild exploitation (Feedly). The vulnerability is not listed in CISA's Known Exploited Vulnerabilities (KEV) catalog. The EPSS score is approximately 0.116%, indicating a currently low probability of exploitation in the near term. No threat actor attribution has been reported.

1. Reconnaissance: Identify deployments of NVIDIA NeMo Framework versions prior to 2.6.2, particularly those with network-accessible model loading endpoints, shared storage, or APIs that accept checkpoint files.
2. Craft malicious checkpoint: Create a specially crafted checkpoint file (e.g., a serialized Python pickle or similar format used by NeMo) that embeds a malicious payload designed to execute arbitrary code upon deserialization.
3. Deliver the payload: Supply the malicious checkpoint file to the target system — this could be via a shared model repository, a compromised upstream source, a network-accessible API endpoint, or social engineering to have a user load the file.
4. Trigger deserialization: When the NeMo Framework loads the checkpoint (e.g., during model restoration or fine-tuning), the unsafe deserialization routine processes the malicious payload without adequate validation.
5. Achieve code execution: The deserialized payload executes arbitrary commands in the context of the NeMo process, potentially enabling reverse shell establishment, credential theft, data exfiltration, or further lateral movement within the AI/ML infrastructure (Feedly, NVIDIA Advisory).

• File System: Unexpected or externally sourced checkpoint files (.nemo, .ckpt, .pkl) in model directories; newly created scripts or binaries in NeMo working directories.
• Process: Unusual child processes spawned by the NeMo Python process (e.g., bash, sh, curl, wget, python -c); unexpected network connections initiated by the NeMo process.
• Network: Outbound connections from NeMo host to unknown external IPs, particularly on non-standard ports; unexpected data transfers from model storage systems.
• Logs: Python deserialization errors or unexpected exceptions in NeMo application logs during checkpoint loading; anomalous access patterns to checkpoint file storage locations.

NVIDIA has released a patch in NeMo Framework version 2.6.2, and all users should upgrade immediately (NVIDIA Advisory). Organizations unable to patch immediately should restrict network access to systems running NeMo Framework, implement strict allowlisting and integrity verification (e.g., cryptographic signatures) for checkpoint files, and avoid loading checkpoints from untrusted or unverified sources. As a last resort, consider isolating affected NeMo deployments from untrusted network sources or disabling checkpoint loading functionality until patching is feasible (Feedly).

Security news outlets including GBHackers, CyberPress, and CyberSecurityNews covered the vulnerability as part of broader reporting on critical NVIDIA AI framework vulnerabilities enabling RCE and DoS attacks (GBHackers, CyberPress, CyberSecurityNews). Social media activity was noted on Bluesky and Mastodon shortly after disclosure. Red Hat also tracked the vulnerability given its relevance to AI/ML workloads running on Red Hat platforms (Red Hat).