---
id: CVE-2026-66007
title: >-
  datasets: Datasets: Information disclosure via path traversal vulnerability
  (CVE-2026-66007)
summary: >-
  A flaw was found in datasets. This path traversal vulnerability allows a
  remote attacker to read arbitrary local files. By providing specially crafted
  file names in the metadata, an attacker can trick the system into including
  sensitive lo…
severity: medium
cvss: 6.5
cvssVector: 'CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N'
cvssSource: vendor
cwe: CWE-22
vendor: Red Hat
product: Red Hat OpenShift AI 3.4
affected:
  - exploit_intelligence
  - lightspeed_core
  - enterprise_linux_ai_rhel_ai 3
  - openshift_ai_rhoai
  - ai_inference_server 3.5
  - openshift_ai 3.4
patched:
  - ai_inference_server 3.5
  - openshift_ai 3.4
published: '2026-07-24'
updated: '2026-10-19'
sourceUpdated: '2026-10-19T11:47:29+00:00'
source: CSAF
sourceUrl: 'https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-66007.json'
references:
  - url: >-
      https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-66007.json
  - url: 'https://access.redhat.com/security/cve/CVE-2026-66007'
  - url: 'https://bugzilla.redhat.com/show_bug.cgi?id=2506794'
  - url: 'https://www.cve.org/CVERecord?id=CVE-2026-66007'
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2026-66007'
  - url: >-
      https://github.com/huggingface/datasets/commit/f989ef9b4cc6c0039a7a82458eebca49e2b58b4b
  - url: 'https://github.com/huggingface/datasets/issues/8324'
  - url: 'https://github.com/huggingface/datasets/pull/8325'
  - url: >-
      https://www.vulncheck.com/advisories/datasets-path-traversal-via-unsanitized-file-name-metadata
  - url: 'https://access.redhat.com/errata/RHSA-2026:82371'
  - url: 'https://access.redhat.com/errata/RHSA-2026:84734'
  - url: 'https://github.com/advisories/GHSA-379c-qx7v-6h59'
  - url: 'https://github.com/huggingface/datasets'
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/datasets/PYSEC-2026-3716.yaml
tags:
  - csaf
  - vex
  - red-hat
  - osv
  - pip
  - ghsa
  - cve.org
  - exploit-available
epss: 0.0055
epssPercentile: 0.45797
aliases:
  - PYSEC-2026-3716
  - GHSA-379c-qx7v-6h59
ecosystem: pip
exploitAvailable: true
ssvc:
  exploitation: poc
  automatable: 'no'
  technicalImpact: partial
  timestamp: '2026-07-24T15:18:39.129173Z'
ingestedAt: '2026-08-19T19:22:21.705Z'
---

## Overview

A flaw was found in datasets. This path traversal vulnerability allows a remote attacker to read arbitrary local files. By providing specially crafted file names in the metadata, an attacker can trick the system into including sensitive local files when datasets are saved or published, leading to information disclosure.

## Vendor advisories

- **RHSA-2026:82371** · Red Hat · fixed in: Red Hat AI Inference Server 3.5 · released 2026-10-13 · [advisory](https://access.redhat.com/errata/RHSA-2026:82371)
- **RHSA-2026:84734** · Red Hat · fixed in: Red Hat OpenShift AI 3.4 · released 2026-10-19 · [advisory](https://access.redhat.com/errata/RHSA-2026:84734)
- **Red Hat VEX** · Moderate · affected: Exploit Intelligence, Lightspeed Core, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI) · no fix planned: Exploit Intelligence, Lightspeed Core, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI) · updated 2026-10-19 · [vex](https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-66007.json)

**datasets: Datasets: Information disclosure via path traversal vulnerability** — rated Moderate by Red Hat. Released 2026-07-24, updated 2026-10-19.

Affected:

- Exploit Intelligence
- Lightspeed Core
- Red Hat Enterprise Linux AI (RHEL AI) 3
- Red Hat OpenShift AI (RHOAI)

Fixed:

- Red Hat AI Inference Server 3.5
- Red Hat OpenShift AI 3.4

No fix planned:

- Exploit Intelligence
- Lightspeed Core
- Red Hat Enterprise Linux AI (RHEL AI) 3
- Red Hat OpenShift AI (RHOAI)

Not affected:

- Red Hat OpenShift AI 3.4
- Exploit Intelligence
- Red Hat AI Inference Server
- Red Hat Enterprise Linux AI (RHEL AI) 3
- Red Hat OpenShift AI (RHOAI)

## Remediation

For more information visit https://access.redhat.com/errata/RHSA-2026:82371 https://access.redhat.com/errata/RHSA-2026:82371
For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update:

https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ https://access.redhat.com/errata/RHSA-2026:84734

Workarounds / mitigations:

- To mitigate this issue, ensure that all `file_name` metadata processed by the `datasets` library, especially within folder-based dataset builders, is thoroughly validated and sanitized. Avoid processing `file_name` values from untrusted sources without strict input validation to prevent directory traversal sequences. This will prevent the embedding of arbitrary local files during `save_to_disk` or `push_to_hub` operations.

## Package advisory (CVE-2026-66007)

Affected packages:

- `datasets < 5.0.1`

Patched in:

- `datasets 5.0.1`

Source: https://osv.dev/vulnerability/PYSEC-2026-3716