CVE-2026-15531 (GCVE-0-2026-15531)
Vulnerability from cvelistv5 – Published: 2026-07-13 04:15 – Updated: 2026-07-13 15:27
VLAI
EPSS
VEX
Title
yashbhalgat HashNeRF-pytorch Checkpoint File run_nerf.py torch.load deserialization
Summary
A vulnerability has been found in yashbhalgat HashNeRF-pytorch up to 82885e698295982504eb6a26d060a6b2473e3706. Affected by this issue is the function torch.load of the file run_nerf.py of the component Checkpoint File Handler. The manipulation of the argument ckpt_path leads to deserialization. The attack must be carried out locally. The exploit has been disclosed to the public and may be used. This product uses a rolling release model to deliver continuous updates. As a result, specific version information for affected or updated releases is not available. The pull request to fix this issue awaits acceptance.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-07-13 15:27 UTC
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/377874 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/377874/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-15531 | third-party-advisory |
| https://vuldb.com/submit/854906 | third-party-advisory |
| https://github.com/yashbhalgat/HashNeRF-pytorch/i… | exploitissue-tracking |
| https://github.com/yashbhalgat/HashNeRF-pytorch/pull/50 | issue-trackingpatch |
| https://github.com/yashbhalgat/HashNeRF-pytorch/ | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| yashbhalgat | HashNeRF-pytorch |
Affected:
82885e698295982504eb6a26d060a6b2473e3706
cpe:2.3:a:yashbhalgat:hashnerf-pytorch:*:*:*:*:*:*:*:* |
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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
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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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