Vulnerability · Published Oct 19, 2026 · Assigned by VulnCheck

CVE-2026-112304docTR through 1.1.0 Unsafe Deserialization RCE via load_pretrained_params()

High 7.5

In plain English

A high-severity unsafe deserialization in docTR from Mindee. Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.4% (higher than 31% of all known vulnerabilities).

Severity (CVSS 3.1)7.5High

Exploit odds (30 days)0.4%top 69.1% of all CVEs

Exploited in the wildNo reportsCISA SSVC: poc

Attack toolingNoneno public tooling known

Official description

docTR through 1.1.0 contains an unsafe deserialization vulnerability in load_pretrained_params() that loads checkpoints with torch.load without weights_only=True. Attackers who control a local or URL-supplied checkpoint can embed a malicious pickle payload to execute Python code with the loading process's privileges on torch releases before 2.6.

Affected products (as reported)

Vendor	Product	Versions
Mindee	docTR	0 – through 1.1.0

Weakness: CWE-502 · Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H

References

https://github.com/mindee/doctr/issues/2175 issue-tracking
https://github.com/mindee/doctr/commit/687503dd15592483c4699ee51280b41938579a9e patch
https://github.com/mindee/doctr/blob/v1.1.0/doctr/models/utils/pytorch.py technical-description
VulnCheck Advisory: docTR through 1.1.0 Unsafe Deserialization RCE via load_pretrained_params() third-party-advisory