BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.37, the `docker.system_packages` field in `bentofile.yaml` accepts arbitrary str
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.39, a malicious bentofile.yaml containing a newline-injected value in envs[*].na
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.39, src/bentoml/_internal/container/frontend/dockerfile/templates/base_v2.j2 int
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.38, the Dockerfile generation function generate_containerfile() in src/bentoml/_
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to version 1.4.34, BentoML's `bentofile.yaml` configuration allows path traversal attac
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. In versions 1.4.38 and prior, the build packaging workflow follows attacker-controlled symlin
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.38, the cloud deployment path in src/bentoml/_internal/cloud/deployment.py was n
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.8, there was an insecure deserialization in BentoML's runner server. By setting
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.36, the safe_extract_tarfile() function validates that each tar member's path is
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. A Remote Code Execution (RCE) vulnerability caused by insecure deserialization has been ident
BentoML is a Python library for building online serving systems optimized for AI apps and model inference. In versions 1.4.0 until 1.4.19, the file upload processing system contains an SSRF vulnerabil
A high-severity remote code execution vulnerability exists in feast-dev/feast version 0.53.0, specifically in the Kubernetes materializer job located at `feast/sdk/python/feast/infra/compute_engines/k
A deserialization vulnerability exists in BentoML's runner server in bentoml/bentoml versions <=1.3.4.post1. By setting specific parameters, an attacker can execute unauthorized arbitrary code on the
A YAML deserialization vulnerability was found in the Robot Operating System (ROS) 'dynparam', a command-line tool for getting, setting, and deleting parameters of a dynamically configurable node, aff
The MLX inference backend in Docker Model Runner on macOS uses the MLX-LM library, which unconditionally imports and executes arbitrary Python files from model directories via the model_file configura
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack through the flashinfer-jit-cache package.
Moby is an open source container framework. In versions prior to 29.5.1 and in moby/moby v2 prior to v2.0.0-beta.14, when a compressed archive is uploaded to a container via `PUT /containers/{id}/arch
BentoML version v1.3.4post1 is vulnerable to a Denial of Service (DoS) attack. The vulnerability can be exploited by appending characters, such as dashes (-), to the end of a multipart boundary in an
A command injection vulnerability in the minimal_wrapper.py component of kubectl-mcp-server v1.2.0 allows attackers to execute arbitrary commands via injecting arbitrary shell metacharacters.
In Splunk AI Toolkit versions below 5.7.4, a user who holds the "admin" Splunk role could execute arbitrary OS commands on the host running the Splunk Enterprise instance.
The vulnerability is poss
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