Diffusers: `trust_remote_code` bypass via `custom_pipeline` and local custom components
Summary
| CVE | CVE-2026-44513 |
|---|---|
| State | PUBLISHED |
| Assigner | GitHub_M |
| Source Priority | CVE Program / NVD first with legacy fallback |
| Published | 2026-05-14 17:16:22 UTC |
| Updated | 2026-07-15 02:21:58 UTC |
| Description | Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, a trust_remote_code bypass in DiffusionPipeline.from_pretrained allows arbitrary remote code execution despite the user passing trust_remote_code=False (or omitting it, which is the default). The vulnerability has three variants, all sharing the same root cause — the trust_remote_code gate was implemented inside DiffusionPipeline.download() rather than at the actual dynamic-module load site, so any code path that bypassed or short-circuited download() also bypassed the security check. DiffusionPipeline.from_pretrained('repoA', custom_pipeline='attacker/repoB', trust_remote_code=False) — the gate evaluated against repoA's file list rather than repoB's, so repoB's pipeline.py was loaded and executed. DiffusionPipeline.from_pretrained('/local/snapshot', custom_pipeline='attacker/repoB', trust_remote_code=False) — the local-path branch never invoked download(), so the gate was never reached and remote code from repoB executed. DiffusionPipeline.from_pretrained('/local/snapshot', trust_remote_code=False) where the snapshot contains custom component files (e.g. unet/my_unet_model.py) referenced from model_index.json — same root cause; the local path skipped download() and custom component code executed. This vulnerability is fixed in 0.38.0. |
Risk And Classification
Primary CVSS: v3.1 8.8 HIGH from ADP
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS: 0.008650000 probability, percentile 0.545590000 (date 2026-07-16)
Problem Types: CWE-94 | CWE-358 | CWE-94 CWE-94: Improper Control of Generation of Code ('Code Injection') | CWE-358 Improperly Implemented Security Check for Standard
| Version | Source | Type | Score | Severity | Vector |
|---|---|---|---|---|---|
| 3.1 | ADP | CVSS | 8.8 | HIGH | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
| 3.1 | [email protected] | Secondary | 8.8 | HIGH | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
| 3.1 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | Secondary | 8.8 | HIGH | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
| 3.1 | CNA | DECLARED | 8.8 | HIGH | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
CVSS v3.1 Breakdown
Attack Vector
NetworkAttack Complexity
LowPrivileges Required
NoneUser Interaction
RequiredScope
UnchangedConfidentiality
HighIntegrity
HighAvailability
HighCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
NVD Known Affected Configurations (CPE 2.3)
| Type | Vendor | Product | Version | Update | Edition | Language |
|---|---|---|---|---|---|---|
| Application | Huggingface | Diffusers | All | All | All | All |
Vendor Declared Affected Products
| Source | Vendor | Product | Version | Platforms |
|---|---|---|---|---|
| CNA | Huggingface | Diffusers | affected < 0.38.0 | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat AI Inference Server | Not specified | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI RHEL AI 3 | Not specified | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI RHEL AI 3 | Not specified | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI RHEL AI 3 | Not specified | Not specified |
| ADP | Red Hat | Red Hat Enterprise Linux AI RHEL AI 3 | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
| ADP | Red Hat | Red Hat OpenShift AI RHOAI | Not specified | Not specified |
References
| Reference | Source | Link | Tags |
|---|---|---|---|
| access.redhat.com/security/cve/CVE-2026-44513 | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | access.redhat.com | |
| github.com/huggingface/diffusers/security/advisories/GHSA-98h9-4798-4q5v | [email protected] | github.com | Exploit, Mitigation, Vendor Advisory |
| bugzilla.redhat.com/show_bug.cgi | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | bugzilla.redhat.com | |
| security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-44513.json | 0b0ca135-0b70-47e7-9f44-1890c2a1c46c | security.access.redhat.com | |
| CVE Program record | CVE.ORG | www.cve.org | canonical |
| NVD vulnerability detail | NVD | nvd.nist.gov | canonical, analysis |
No vendor comments have been submitted for this CVE.
Additional Advisory Data
| Source | Time | Event |
|---|---|---|
| ADP | 2026-05-14T17:02:10.040Z | Reported to Red Hat. |
| ADP | 2026-05-14T16:26:03.907Z | Made public. |
Workarounds
ADP: Use DiffusionPipeline.from_pretrained() only with model paths, custom pipelines, and local snapshots from fully trusted and audited sources. Avoid setting custom_pipeline= to a Hub repository that differs from the primary model path unless its pipeline.py has been manually reviewed. When loading a local snapshot, check for unexpected *.py files at the snapshot root and under component subdirectories (unet/, scheduler/, etc.) before calling from_pretrained. The only complete fix is upgrading to diffusers 0.38.0.
There are currently no legacy QID mappings associated with this CVE.