CVE-2026-108958
6.3MediumPublished 13 Oct 2026 · NVD status: Deferred · AI triage by gemini-3.8-flash
- Attack vector
- Network
- Complexity
- Low
- Privileges needed
- None
- User interaction
- Required
- Impact
- Limited impact
- Weakness
- CWE-20, CWE-502
Impact
Attackers can achieve arbitrary code execution or compromise system state by convincing a user or service to parse a malicious model. Exploitation requires supplying a crafted HDF5 model payload to the target application.
Root cause
Insecure deserialization occurs within load_hdf5_graph in tensorlayer/files/utils.py when processing the model_config argument.
Affected systems
TensorLayer up to and including version 2.2.4
CVSS v3.1 · CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:L
Fix & remediation
No patched version is currently available. As an interim mitigation, do not call load_hdf5_graph on untrusted files and block the ingestion of unverified HDF5 model configurations.
$ pip show tensorlayerAI-suggested. Run it in staging first and check it against the vendor advisory. Why?
NVD description
A weakness has been identified in TensorLayer up to 2.2.4. This affects the function load_hdf5_graph of the file tensorlayer/files/utils.py of the component HDF5 Loading. Executing a manipulation of the argument model_config can lead to deserialization. The attack can be executed remotely. The exploit has been made available to the public and could be used for attacks. The project was informed of the problem early through an issue report but has not responded yet.