HighVulnerability

CVE-2026-44017: Docling zip slip in EasyOCR model download extraction

Source: NVD(opens in a new tab)
Identifier: CVE-2026-44017
Published: June 24, 2026
Record updated: October 9, 2026

Affected: docling < 2.91.0
Fixed in: 2.91.0
released April 23, 2026, 62 days before disclosure
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.7%

Summary

CVE-2026-44017 affects Docling before 2.91.0. Its EasyOCR model download functionality extracted ZIP archives without validating member paths, enabling Zip Slip. An attacker who could compromise the model download source via supply chain attack, DNS spoofing, or MITM could write arbitrary files anywhere the process can write, potentially achieving remote code execution, persistent backdoors, or data corruption.

Mitigation

Fixed in 2.91.0.

Details

Scores and exploitation

CVSS score: 7.5(high)
Patch available: Yes
CVSS vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
Attack vector: network
Attack complexity: high
Privileges required: none
User interaction: required
EPSS: 0.7%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 9, 2026.
Disclosure date: June 24, 2026

Weaknesses and techniques

Weakness (CWE): CWE-22
Attack pattern (CAPEC): CAPEC-126
AI threat technique (MITRE ATLAS): AML.T0010

Affected

Packages: docling@< 2.91.0 (fixed: 2.91.0)

Classification

Attack type: Supply chain
Attack sophistication: Advanced
AI component targeted: Framework
Impact: Integrity,
Confidentiality,
Availability
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-44017

First tracked: June 25, 2026 at 08:22 AM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 85% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

doclingPyPINo LLM dependency detected · 9 tracked dependents

Summary

Mitigation

Affected packages in the Exposure Registry

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