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CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
Local-only exploitation via file path argument control with low privilege; no scope change and symmetric low C/I/A impact confined to the training process.
Primary rating from Vendor (VulDB).
CVSS VectorVendor: VulDB
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3DescriptionCVE.org
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.
AnalysisAI
Unsafe deserialization in HashNeRF-pytorch's Checkpoint File Handler allows a local low-privileged attacker to achieve arbitrary code execution by supplying a malicious file via the ckpt_path argument to torch.load() in run_nerf.py. All commits up to 82885e698295982504eb6a26d060a6b2473e3706 are affected; a fix exists as an unmerged pull request (PR #50). A public exploit has been disclosed via GitHub issue #49, though no CISA KEV listing has been identified, indicating no confirmed widespread active exploitation at time of analysis.
Technical ContextAI
HashNeRF-pytorch is a PyTorch-based research implementation of hash-encoding Neural Radiance Fields (NeRF). The vulnerability resides in run_nerf.py within the Checkpoint File Handler, which invokes Python's torch.load() to restore model state from disk. By default, torch.load() relies on Python's pickle module for deserialization, a known dangerous pattern classified under CWE-502 (Deserialization of Untrusted Data). When no weights_only=True restriction is enforced, any serialized Python object - including one embedding malicious __reduce__ hooks - can execute arbitrary code at load time. The CPE cpe:2.3:a:yashbhalgat:hashnerf-pytorch:*:*:*:*:*:*:*:* covers all releases of the project, consistent with its rolling release model and lack of versioned tags.
RemediationAI
No officially merged patch exists at time of analysis; the fix is pending as pull request PR #50 (https://github.com/yashbhalgat/HashNeRF-pytorch/pull/50), which has not yet been accepted into the main branch. Users should monitor that PR and manually apply the patch to their local installations by cherry-picking the changes from PR #50. As an immediate compensating control, modify run_nerf.py to pass weights_only=True to torch.load(), which restricts deserialization to tensor primitives and prevents arbitrary Python object execution - note that this may cause failures if checkpoints store non-tensor metadata, requiring additional code changes to re-serialize those components safely. Additionally, enforce a policy of only loading checkpoint files from trusted, write-protected sources, and restrict file system write permissions on checkpoint directories to prevent untrusted users from substituting malicious files. Reference the VulDB advisory at https://vuldb.com/cve/CVE-2026-15531 for updates.
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External POC / Exploit Code
Leaving vuln.today
EUVD-2026-43277
GHSA-9wjg-4fhr-x4rw