CVE-2026-112304
docTR through 1.1.0 contains an unsafe deserialization vulnerability in load_pretrained_params() that loads checkpoints with torch.load without weights_only=True.
Does this matter?
High impact if exploited, but EPSS currently rates exploitation as unlikely (0.37%). Schedule it in the normal patch cycle and watch for a rise in EPSS or a public exploit.
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.
- CVSS 4.0
- 7.7 HIGHCVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/M
- EPSS
- 0.37% probability · 31th percentile
- Public exploits
- None in Exploit-DB
- CISA KEV
- Not listed
- Weakness
- CWE-502
- Source
- disclosure@vulncheck.com
EPSS moved from 0.3% on 20 October 2026 to 0.4% on 27 October 2026.
References
- https://github.com/mindee/doctr/blob/v1.1.0/doctr/models/utils/pytorch.py
- https://github.com/mindee/doctr/commit/687503dd15592483c4699ee51280b41938579a9e
- https://github.com/mindee/doctr/issues/2175
- https://www.vulncheck.com/advisories/doctr-through-1.1.0-unsafe-deserialization-rce-via-load-pretrained-params
- https://github.com/mindee/doctr/issues/2175
Source: NVD record, EPSS from FIRST.org, KEV from CISA, exploits from Exploit-DB. Refreshed daily. Download this record as JSON.