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Vulnerability Database/CVE-2025-14026

CVE-2025-14026: Forcepoint One DLP RCE Vulnerability

CVE-2025-14026 is a remote code execution vulnerability in Forcepoint One DLP Client that allows bypassing Python restrictions to execute arbitrary code. This article covers technical details, affected versions, and mitigations.

Updated:

CVE-2025-14026 Overview

CVE-2025-14026 affects Forcepoint One Data Loss Prevention (DLP) Client version 23.04.5642 and potentially newer releases. The product ships with a restricted build of Python 2.5.4 that blocks access to the ctypes foreign function interface (FFI). Researchers demonstrated that these restrictions can be bypassed, allowing arbitrary code execution through the embedded interpreter. Because ctypes enables direct calls to DLLs, memory allocation, and native code execution, a successful bypass gives an attacker full control over the Python runtime hosted by the DLP client.

Critical Impact

A local authenticated attacker can escape the restricted Python sandbox in the Forcepoint One DLP Client and execute arbitrary native code with the privileges of the DLP process.

Affected Products

  • Forcepoint One DLP Client version 23.04.5642
  • Potentially newer versions of the Forcepoint One DLP Client
  • Windows endpoints running the affected client build

Discovery Timeline

  • 2026-01-06 - CVE-2025-14026 published to NVD
  • 2026-06-17 - Last updated in NVD database

Technical Details for CVE-2025-14026

Vulnerability Analysis

The Forcepoint One DLP Client embeds a modified Python 2.5.4 interpreter that is intended to run vendor-supplied policy scripts in a restricted context. The vendor removed or disabled the ctypes module because ctypes provides a foreign function interface capable of loading arbitrary shared libraries, allocating memory, and invoking native functions directly. Blocking ctypes is a common hardening step for embedded Python interpreters because the module effectively grants native code execution to any script that can import it.

Researchers showed that the restrictions enforced by the client are incomplete. An attacker with local access to the endpoint can craft input that reintroduces ctypes functionality inside the embedded interpreter. Once ctypes is reachable, the sandbox model collapses and the attacker can execute arbitrary machine code in the address space of the DLP client. Refer to the CERT Vulnerability Advisory and the Forcepoint Support Article for vendor-authoritative technical detail.

Root Cause

The root cause is an incomplete restriction of the Python 2.5.4 module import surface. Blocking direct import ctypes does not remove the underlying compiled module or its transitive reachability, so alternative import paths and object graph traversal expose the FFI functionality again. This is a sandbox escape pattern well documented in restricted Python environments.

Attack Vector

Exploitation requires local access and low privileges on an endpoint running the affected client. The attacker delivers Python content that the DLP client evaluates, then uses the bypass to reach ctypes. From there the attacker loads a native library or calls Win32 APIs directly to execute code, tamper with DLP inspection, or escalate access on the host. No user interaction beyond triggering script evaluation is required.

No public proof-of-concept exploit is currently available for CVE-2025-14026. See the CERT advisory for a description of the bypass technique.

Detection Methods for CVE-2025-14026

Indicators of Compromise

  • Unexpected loading of ctypes-related DLLs, such as _ctypes.pyd or libffi, by Forcepoint One DLP Client processes.
  • Forcepoint DLP client processes spawning child processes such as cmd.exe, powershell.exe, or rundll32.exe.
  • Outbound network connections initiated directly by the embedded Python interpreter hosted in the DLP client.
  • Unsigned or unexpected DLLs mapped into the DLP client process address space.

Detection Strategies

  • Monitor process ancestry for the Forcepoint DLP client executable spawning interactive shells or scripting hosts.
  • Alert on image loads of native FFI helpers into the DLP client that do not match the vendor's known-good module list.
  • Hunt for anomalous file writes and registry modifications performed under the DLP client process context.
  • Correlate endpoint telemetry with local user session activity to identify low-privilege users triggering DLP-hosted script execution.

Monitoring Recommendations

  • Enable command-line and module-load auditing on all endpoints running the Forcepoint One DLP Client.
  • Forward endpoint process, image-load, and network telemetry to a centralized analytics platform for retrospective hunting.
  • Track versions of the Forcepoint One DLP Client deployed across the fleet and flag hosts still running 23.04.5642.

How to Mitigate CVE-2025-14026

Immediate Actions Required

  • Inventory all endpoints running the Forcepoint One DLP Client and identify hosts on version 23.04.5642 or earlier.
  • Contact Forcepoint support and review the Forcepoint Support Article for the current remediation guidance.
  • Restrict local user privileges on endpoints hosting the DLP client to reduce the population of accounts that can trigger script evaluation.
  • Apply application control policies that block unauthorized DLLs from loading into the DLP client process.

Patch Information

Refer to the Forcepoint Support Article and the CERT Vulnerability Advisory for vendor-supplied patch availability and upgrade guidance. Upgrade the Forcepoint One DLP Client to a fixed release once the vendor publishes it, and validate the deployment across all managed endpoints.

Workarounds

  • Limit interactive logon rights on endpoints running the DLP client to trusted administrators only.
  • Deploy endpoint application control to prevent the DLP client process from loading non-vendor DLLs or spawning shells.
  • Monitor the DLP client process for ctypes module loads and terminate sessions that trigger unexpected FFI activity until a patched version is installed.

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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