CVE-2026-111865 (GCVE-0-2026-111865)
Vulnerability from cvelistv5 – Published: 2026-10-17 20:45 – Updated: 2026-10-19 15:04
VLAI
EPSS
VEX
Title
THU-MIG yoloe AutoBackend Model Loading autobackend.py eval eval injection
Summary
A security flaw has been discovered in THU-MIG yoloe up to 40cd606cabdbe2b566d6f14a6b162c89206e9a1b. This affects the function eval of the file ultralytics/nn/autobackend.py of the component AutoBackend Model Loading. The manipulation of the argument imgsz/names/kpt_shape results in improper neutralization of directives in dynamically evaluated code. The attack requires a local approach. The exploit has been released to the public and may be used for attacks. This product does not use versioning. This is why information about affected and unaffected releases are unavailable. The project was informed of the problem early through an issue report but has not responded yet.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-19 15:03 UTC
CWE
Assigner
References
6 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/421573 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/421573/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-111865 | third-party-advisory |
| https://vuldb.com/submit/1004883 | third-party-advisory |
| https://github.com/THU-MIG/yoloe/issues/148 | exploitissue-tracking |
| https://github.com/THU-MIG/yoloe/ | product |
Impacted products
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline
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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.