CVE-2025-33183: NVIDIA Isaac-GR00T RCE Vulnerability

CVE-2025-33183 is a remote code execution flaw in NVIDIA Isaac-GR00T's Python component that enables code injection attacks. Successful exploitation may result in privilege escalation and data tampering. This article covers technical details, affected versions, impact assessment, and mitigation strategies.

CVE-2025-33183 Overview

CVE-2025-33183 affects NVIDIA Isaac-GR00T across all supported platforms. The vulnerability resides in a Python component and allows an authenticated local attacker to trigger a code injection condition [CWE-94]. Successful exploitation can lead to arbitrary code execution, privilege escalation, information disclosure, and data tampering within the affected robotics development environment.

The flaw requires local access with low privileges and no user interaction. Because Isaac-GR00T is used to build and train humanoid robot foundation models, exploitation can compromise research data, model integrity, and downstream robotic systems that consume artifacts produced by the platform.

Critical Impact
An attacker with local access can inject and execute arbitrary Python code, resulting in full compromise of confidentiality, integrity, and availability of the Isaac-GR00T environment.

Affected Products

NVIDIA Isaac-GR00T (all platforms)
Python component shipped within the Isaac-GR00T distribution
Environments running unpatched versions prior to the fix referenced in NVIDIA advisory ID 5725

Discovery Timeline

2025-11-18 - CVE-2025-33183 published to the National Vulnerability Database
2026-06-17 - Last updated in NVD database

Technical Details for CVE-2025-33183

Vulnerability Analysis

CVE-2025-33183 is a code injection vulnerability classified under CWE-94: Improper Control of Generation of Code. The defect exists in a Python component within Isaac-GR00T that processes attacker-influenced input without adequate sanitization before evaluation or execution.

When the vulnerable component parses crafted input, the payload is interpreted as executable Python code rather than data. This allows the attacker's code to run inside the process context of Isaac-GR00T. The attack surface is local, meaning the adversary must already possess valid low-privilege access to the host running the platform.

Root Cause

The root cause is unsafe handling of untrusted input by a Python routine that constructs or evaluates code at runtime. Common patterns leading to this class of defect include the use of eval(), exec(), pickle.loads(), or unsafe deserialization of configuration and model artifacts. NVIDIA has not published implementation-level details beyond the advisory referenced below.

Attack Vector

Exploitation requires local access and low privileges on the machine running Isaac-GR00T. The attacker supplies crafted input to the vulnerable Python component through a file, configuration artifact, or interface reachable from the local user context. When Isaac-GR00T processes the input, the injected code executes with the privileges of the running process.

Successful exploitation enables the attacker to read sensitive training data and credentials, tamper with robot foundation models, and pivot to escalate privileges within the host. Refer to the NVIDIA Support Response for vendor guidance and the NVD CVE-2025-33183 Details for the authoritative record.

Detection Methods for CVE-2025-33183

Indicators of Compromise

Unexpected Python child processes spawned by Isaac-GR00T runtime binaries or Jupyter kernels.
Unusual outbound network connections originating from the Isaac-GR00T process context.
Modifications to model files, training datasets, or configuration artifacts outside of planned workflows.
New or altered files in Isaac-GR00T working directories containing serialized Python objects.

Detection Strategies

Monitor for Python exec, eval, or pickle invocations against user-supplied artifacts within Isaac-GR00T processes.
Alert on process lineage where Isaac-GR00T components launch shells, interpreters, or system utilities.
Baseline expected Isaac-GR00T behavior and flag deviations in file, registry, and network activity.

Monitoring Recommendations

Enable command-line auditing on Linux hosts running Isaac-GR00T and forward events to a centralized SIEM.
Track integrity of model checkpoints and configuration files with file integrity monitoring.
Review authentication logs for unexpected local logons preceding Isaac-GR00T activity.

How to Mitigate CVE-2025-33183

Immediate Actions Required

Apply the fixed Isaac-GR00T release identified in the NVIDIA Support Response as soon as it is available in your environment.
Restrict local access to systems running Isaac-GR00T to trusted operators only.
Audit existing training artifacts and configuration files for suspicious Python payloads.

Patch Information

NVIDIA has published guidance and remediation information in advisory ID 5725. Consult the NVIDIA Support Response for the specific fixed version applicable to your deployment. Verify integrity of downloaded packages before installation and follow the vendor upgrade instructions.

Workarounds

Run Isaac-GR00T under a dedicated, least-privileged service account with no interactive login rights.
Isolate Isaac-GR00T workloads in containers or virtual machines with restricted filesystem and network access.
Reject untrusted model, dataset, and configuration files from external sources until the patch is deployed.
Enforce mandatory code review for scripts and notebooks executed within the Isaac-GR00T environment.