Malicious code in zod-pino434 (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 599a5d533bf699156b78f5296f643227bf3e43d8e46f2adabfe250205a05bd26 Package name zod-pino434 and package.json description Node.js integration layer for Autodesk Forge do not match the shipped code. On npm install, the...

PYSEC-2026-406 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...

MAL-2026-6279 Malicious code in forge-jsx4 (npm)

forge-jsx4 is a remote access trojan RAT published to the public npm registry by the account rafaelsilva [email protected]. Versions 1.0.122 and 1.0.123 were published on June 21-22, 2026 as a reconstitution of the forge-jsx / forge-jsxy campaign, reusing the same command-and-control...

Malicious code in forge-jsx4 (npm)

forge-jsx4 is a remote access trojan RAT published to the public npm registry by the account rafaelsilva [email protected]. Versions 1.0.122 and 1.0.123 were published on June 21-22, 2026 as a reconstitution of the forge-jsx / forge-jsxy campaign, reusing the same command-and-control...

CVE-2026-48797 Backpropagate: backprop ui --auth and backprop ui --share do not enforce authentication

Backpropagate is a Python library for fine-tuning large language models on a single GPU. In versions 1.1.0 and 1.1.1, the optional Reflex web UI exposes a training control plane without authentication: dataset upload, model load, training start/stop, multi-run orchestration, GGUF export, and...

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...

EUVD-2026-29562

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...

GHSA-PQ2F-X424-6FJM 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...

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...

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 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...

GHSA-J7W6-VPVQ-J3GM 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...

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...

PT-2026-39298

Name of the Vulnerable Software and Affected Versions Diffusers versions prior to 0.38.0 Description An issue exists in the DiffusionPipeline.from pretrained flow when loading pipelines from Hugging Face Hub repositories. The resolve custom pipeline and cls function in pipeline loading utils.py...

InstructLab Includes Functionality from Untrusted Control Sphere

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...

CVE-2026-6859

CVE-2026-6859 is a Red Hat advisory about a flaw in InstructLab where linux_train.py hardcodes trust_remote_code=True when loading models from HuggingFace. This enables arbitrary Python code execution if a user runs ilab train/download/generate with a malicious HuggingFace model, potentially lead...

CVE-2026-6859 Instructlab: instructlab: arbitrary code execution due to hardcoded `trust_remote_code=true`

A flaw was found in InstructLab. The linuxtrain.py script hardcodes trustremotecode=True when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run ilab train/download/generate with a specially crafted malicious model...