CVE-2026-5241 (GCVE-0-2026-5241)
Vulnerability from cvelistv5 – Published: 2026-06-03 12:33 – Updated: 2026-09-01 12:04
VLAI
EPSS
VEX
Title
Policy Bypass in LightGlue Nested Config Resolution in huggingface/transformers
Summary
A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-03 15:45 UTC
CWE
- CWE-829 - Inclusion of Functionality from Untrusted Control Sphere
Assigner
References
9 references
| URL | Tags |
|---|---|
| https://huntr.com/bounties/ceb3ce1a-4c45-497a-b25… | |
| https://github.com/huggingface/transformers/commi… | |
| https://access.redhat.com/security/cve/CVE-2026-5241 | vdb-entryx_refsource_REDHAT |
| https://bugzilla.redhat.com/show_bug.cgi?id=2484384 | issue-trackingx_refsource_REDHAT |
| https://security.access.redhat.com/data/csaf/v2/v… | x_sadp-csaf-vex |
| https://access.redhat.com/errata/RHSA-2026:42644 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:37275 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:34456 | vendor-advisoryx_refsource_REDHAT |
| https://access.redhat.com/errata/RHSA-2026:60520 | vendor-advisoryx_refsource_REDHAT |
Impacted products
28 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| huggingface | huggingface/transformers |
Affected:
unspecified , < 5.5.0
(custom)
|
guessed | |
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1783082430 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1783998418 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 2.25 |
Unaffected:
1782475830 , < *
(rpm)
cpe:/a:redhat:openshift_ai:2.25::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1782471555 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1782471579 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1783073038 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1782991170 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1782471656 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1782471663 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1783069204 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.3 |
Unaffected:
1782471606 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.3::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782135464 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782136276 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782135346 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782132167 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782132207 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782132240 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782132286 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782132236 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1782132163 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1786611822 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | Red Hat OpenShift AI 3.4 |
Unaffected:
1786611435 , < *
(rpm)
cpe:/a:redhat:openshift_ai:3.4::el9 |
||
| Red Hat | OpenShift Lightspeed |
cpe:/a:redhat:openshift_lightspeed
|
||
| Red Hat | Red Hat AI Inference Server |
cpe:/a:redhat:ai_inference_server:3
|
||
| Red Hat | Red Hat Ansible Automation Platform 2 |
cpe:/a:redhat:ansible_automation_platform:2
|
||
| Red Hat | Red Hat Enterprise Linux AI (RHEL AI) 3 |
cpe:/a:redhat:enterprise_linux_ai:3
|
||
| Red Hat | Red Hat OpenShift AI (RHOAI) |
cpe:/a:redhat:openshift_ai
|
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"datePublic": "2026-06-03T12:33:10.227Z",
"descriptions": [
{
"lang": "en",
"value": "A flaw was found in python-transformers. An attacker can exploit this vulnerability by providing a malicious model repository. During model initialization, the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted configuration data. This allows the attacker to execute arbitrary code, potentially leading to credential theft, unauthorized access, or the deployment of backdoors."
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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