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VulnerabilityPublished Updated

CVE-2026-44017: docling · Path Traversal

Affects doclingSource CVE Database V5

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Not known to be exploited · CVSS 7.5 High : upgrade to 2.91.0 soon.

Data as of 7 Nov 2026, 23:24 UTC

CVSS 3.1 base score
7.5High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.7% chance of exploitation in 30 days – higher than 53% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 2.91.0
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 24 Jun 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 7 Nov 2026.

What to do

Upgrade docling and docling-project/docling to 2.91.0.

Affected software

ProductAffectedFixed in
docling-projectdoclingAffected
  • <2.91.0
Fixed in
  • 2.91.0
GitHubdocling-project/doclingpkg:github/docling-project/doclingOther threatsAffected
  • <2.91.0
Fixed in
  • 2.91.0

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

A fix is available in docling version 2.91.0. Users should upgrade to version 2.91.0 or later to remediate this vulnerability. Since the vulnerability depends on the ability to compromise the model download source, ensuring the integrity and authenticity of the model source is also recommended. Patch status is confirmed by the vendor advisory. No additional mitigations are specified by the vendor.

Description

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. Prior to 2.91.0, the EasyOCR model download functionality extracted ZIP archives without validating member paths, enabling Zip Slip attacks. If an attacker could compromise the model download source (via supply chain attack, DNS spoofing, or MITM), they could write arbitrary files to any location writable by the process, potentially achieving remote code execution by overwriting Python files or system binaries, persistent backdoors by modifying startup scripts or SSH keys, and data corruption or system compromise. This vulnerability is fixed in 2.91.0.

References

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