CVE-2026-44017

highPriorität · verfolgen · 0EPSS 0.007 · 53. PerzentilEUUS
grimoire priorityP2 · Scheduled
Exploitable?
—
no known exploitation
Likely / severe?
0.71% (53rd) EPSS
CVSS 7.5 · high
Is it mine?
3 products
Prüfe deine Angriffsfläche
Who says so?
4 sources
cnnvd · enisa_euvd · osv · nvd

EPSS · bewertet 2026-10-27

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.

01

cvss

Technischer Schweregrad, 0–10. Eine Zeile je Quelle.

8.3
010

Basiswert 0–10 · höher = schwerwiegender · Vektor überfahren zum Auflösen

v3.17.5highCVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:Hsecondary · ENISA EU
v3.17.5highCVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:Hsecondary · security-advisories@github.comAusnutzbarkeit 1.6 · Auswirkung 5.9
v3.18.3highCVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:C/C:H/I:H/A:HsecondaryAusnutzbarkeit 1.6 · Auswirkung 6
v3.17.5highCVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:Hsecondary · OSV
02

SSVC

Eine Handlungsentscheidung — aus Ausnutzung und Auswirkung.

Exploitation: none · Automatable: no · Technical Impact: totalcoordinatorcisa_ssvcUS
03

schwächen

Die CWE-Schwächeklassen, zu denen dies gehört.

04

betroffene Produkte (3)

Betroffene Produkte und Versionsbereiche.

05

Advisories (2)

Hersteller- und Ökosystem-Meldungen dazu.

  • GHSA-cjqg-rq2h-2fvjDocling: Unsafe Zip Extraction in EasyOCR Model Download2026-06-03ghsa · osvUS

    ### Impact In versions `< 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 - Data corruption or system compromise ### Patches Fixed in version 2.91.0. The extraction process now validates each archive member path using `os.path.realpath()` to ensure it remains within the target directory, raising a `SecurityError` for any path traversal attempts. ### Workarounds Ensure model downloads occur over secure, authenticated channels. Use integrity verification (checksums) for downloaded models. Run the application with minimal file system permissions. ### References - Fix release: [v2.91.0](https://github.com/docling-project/docling/releases/tag/v2.91.0)

  • PYSEC-2026-21432026-06-24vendor · osvUS

    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.

06

auch bekannt als (6)

Weitere Namen und Kennungen dieser Entität.

07

quellen

Welche Quellen diesen Datensatz belegen und wann.

veröffentlicht 2026-06-24geändert 2026-10-25
08

Referenzen (10)

Externe Belege — Patches, Meldungen, Analysen.

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