CVE-2026-24693: Intel oneCCL PyTorch Privilege Escalation

CVE-2026-24693 Overview

CVE-2026-24693 is a protection mechanism failure [CWE-693] affecting Intel(R) oneCCL Bindings for PyTorch before version v2.8.0. The flaw resides in Ring 3 user application space and can enable escalation of privilege for a local, authenticated adversary. Exploitation requires local access, a privileged user context, and passive user interaction to succeed. When conditions align, an unprivileged attacker can elevate privileges and impact the confidentiality, integrity, and availability of the vulnerable system. Intel published the issue in security advisory Intel-SA-01464.

Critical Impact
Successful exploitation may allow escalation of privilege on systems running vulnerable versions of Intel oneCCL Bindings for PyTorch, compromising the confidentiality, integrity, and availability of the host.

Affected Products

Intel(R) oneCCL Bindings for PyTorch versions prior to v2.8.0
PyTorch environments leveraging Intel oneCCL for collective communications
Systems with Intel oneAPI Collective Communications Library components installed alongside PyTorch

Discovery Timeline

2026-08-11 - CVE-2026-24693 published to NVD
2026-08-12 - Last updated in NVD database

Technical Details for CVE-2026-24693

Vulnerability Analysis

The vulnerability is categorized as a protection mechanism failure [CWE-693] in Intel oneCCL Bindings for PyTorch. Intel oneCCL provides collective communication primitives used by distributed deep-learning workloads. The bindings expose these primitives to PyTorch code executing in Ring 3 user space. A missing or ineffective security control in the affected component allows an unprivileged local process to influence execution in a way that ultimately yields higher privileges. Because impact is scoped to the vulnerable system with no propagation to downstream components, exploitation compromises the host running the vulnerable PyTorch environment but does not directly pivot to adjacent systems.

Root Cause

The root cause is a protection mechanism that fails to enforce the intended security boundary within the oneCCL Bindings for PyTorch component. Intel's advisory attributes the defect to code paths in versions prior to v2.8.0. Because the defect resides in a library loaded into PyTorch processes, any workflow that loads the bindings inherits the weakness.

Attack Vector

Exploitation requires local access to the target system and a privileged user must interact with attacker-controlled content or workflows. The attack complexity is low, but the attacker must already hold high privileges on the process side while relying on passive interaction from a privileged user. No specialized internal knowledge of the target is required when the attack preconditions are met. Full technical details have not been released; refer to Intel Security Advisory SA-01464 for vendor-provided information.

Detection Methods for CVE-2026-24693

Indicators of Compromise

Presence of intel_extension_for_pytorch or oneCCL binding packages at versions earlier than v2.8.0 on production hosts
Unexpected child processes spawned from Python interpreters running PyTorch workloads
Elevation of local user tokens correlated with PyTorch distributed training sessions

Detection Strategies

Inventory installed Python packages and compare oneCCL binding versions against the fixed release v2.8.0
Monitor for anomalous privilege transitions from user-space Python processes to elevated contexts
Baseline the expected file, library, and network activity of PyTorch training jobs and alert on deviations

Monitoring Recommendations

Enable process-lineage and command-line logging on hosts that run distributed PyTorch training
Audit library load events for oneCCL components and flag loads from non-standard paths
Collect endpoint telemetry into a centralized data lake to correlate privilege changes with ML workload execution

How to Mitigate CVE-2026-24693

Immediate Actions Required

Upgrade Intel oneCCL Bindings for PyTorch to v2.8.0 or later on all affected systems
Identify every host, container image, and virtual environment that installs the vulnerable package
Restrict local, interactive access on machines hosting AI/ML training workloads to reduce exposure

Patch Information

Intel addressed the issue in Intel oneCCL Bindings for PyTorch v2.8.0. Administrators should follow the guidance in Intel Security Advisory SA-01464 and rebuild any container images or ML environments that pinned older versions.

Workarounds

Remove or disable Intel oneCCL Bindings for PyTorch on systems where the library is not required
Enforce least-privilege on user accounts that execute PyTorch workloads and avoid running training jobs as privileged users
Isolate ML training hosts from general-purpose user activity to limit opportunities for passive user interaction

bash

# Verify installed version and upgrade to the fixed release
pip show oneccl_bind_pt
pip install --upgrade "oneccl_bind_pt>=2.8.0"