CVE-2026-4372 Arbitrary Remote Code Execution via `_attn_implementation_internal` Config Injection in huggingface/transformers

A critical remote code execution vulnerability exists in all versions of the HuggingFace transformers library prior to version 5.3.0. The vulnerability allows an attacker to craft a malicious config.json file containing the attnimplementationinternal field set to an attacker-controlled HuggingFac...

PT-2026-42614

📋 Reframing 2026-05-02: implicit unsafe remote-code path, not "supply-chain" The accurate description of this vulnerability is: "get model arch and related helpers hardcode trust remote code=True with no opt-out, creating an implicit unsafe remote-code load path on every model fetch." What this...

Time-of-check Time-of-use (TOCTOU) Race Condition

Overview diffusers is a State-of-the-art diffusion in PyTorch and JAX. Affected versions of this package are vulnerable to Time-of-check Time-of-use TOCTOU Race Condition in the frompretrained flow. An attacker can execute arbitrary code by exploiting a race condition between two repository fetch...

PT-2026-42205

Name of the Vulnerable Software and Affected Versions diffusers affected versions not specified Description A race condition exists in the DiffusionPipeline.from pretrained flow when loading pipelines from the HuggingFace Hub. The process involves two separate HTTP calls: one via hf hub download ...

PYSEC-2026-41

Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, diffusers 0.37.0 allows remote code execution without the trustremotecode=True safeguard when loading pipelines from Hugging Face Hub repositories. The resolvecustompipelineandcls function in pipelineloadingutils.py...

PYSEC-2026-40

Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, a trustremotecode bypass in DiffusionPipeline.frompretrained allows arbitrary remote code execution despite the user passing trustremotecode=False or omitting it, which is the default. The vulnerability has three variant...

CVE-2026-44513

Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, a trustremotecode bypass in DiffusionPipeline.frompretrained allows arbitrary remote code execution despite the user passing trustremotecode=False or omitting it, which is the default. The vulnerability has three variant...

CVE-2026-44827

Diffusers prior to 0.38.0 is vulnerable to silent remote code execution when loading pipelines from Hugging Face Hub without trust_remote_code. If custom_pipeline is not supplied, _resolve_custom_pipeline_and_cls formats None as None.py; a repository containing a None.py with a subclass of Diffus...

EUVD-2026-30334

Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, a trustremotecode bypass in DiffusionPipeline.frompretrained allows arbitrary remote code execution despite the user passing trustremotecode=False or omitting it, which is the default. The vulnerability has three variant...

CVE-2026-44513

Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, a trustremotecode bypass in DiffusionPipeline.frompretrained allows arbitrary remote code execution despite the user passing trustremotecode=False or omitting it, which is the default. The vulnerability has three variant...

Deserialization of Untrusted Data

Overview mamba-ssm is a Mamba state-space model Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the frompretrained process. An attacker can execute arbitrary code by publishing a malicious model repository on HuggingFace Hub and having a victim load a mode...

mamba language model framework vulnerable to insecure deserialization when loading pre-trained models from HuggingFace Hub

The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.frompretrained method uses torch.load to load the pytorchmodel.bin weight file without enabling the security-restrictive...

CVE-2026-31239

The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.frompretrained method uses torch.load to load the pytorchmodel.bin weight file without enabling the security-restrictive...

PT-2026-40126

Name of the Vulnerable Software and Affected Versions mamba versions prior to 2.2.7 Description Insecure deserialization occurs when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from pretrained function uses torch.load to load the pytorch model.bin weight file without...

CVE-2026-31239

The CVE-2026-31239 entry concerns the Mamba language model framework up to version 2.2.6. The issue is insecure deserialization (CWE-502) when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method uses torch.load() to load the pytorch_model.bin weight file...

Mamba 安全漏洞

Mamba is a state-space model for linear time series modeling, open-sourced by State-Spaces. Versions of Mamba 2.2.6 and earlier contained security vulnerabilities. These vulnerabilities stemmed from the MambaLMHeadModel.frompretrained method, which used torch.load to load weight files without...

CVE-2026-31239

The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization CWE-502 when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.frompretrained method uses torch.load to load the pytorchmodel.bin weight file without enabling the security-restrictive...

Arbitrary Code Injection

Overview diffusers is a State-of-the-art diffusion in PyTorch and JAX. Affected versions of this package are vulnerable to Arbitrary Code Injection in the frompretrained fucntion when a repository contains a None.py file and the custompipeline argument is not supplied. An attacker can execute...

Diffusers has a `trust_remote_code` bypass via `custom_pipeline` and local custom components

Background This vulnerability is found in the DiffusionPipeline.frompretrained flow, which is used to load a pipeline from the HuggingFace Hub. This function accepts an optional custompipeline keyword argument: the name of a Python file in the repo that contains a custom class inheriting from...

Automated Malware Family Classification Using Weighted Hierarchical Ensembles of Large Language Models

Malware family classification remains a challenging task in automated malware analysis, particularly in real-world settings characterized by obfuscation, packing, and rapidly evolving threats. Existing machine learning and deep learning approaches typically depend on labeled datasets, handcrafted...