Remote Code Execution
101 entries
LangChain pickle deserialization of untrusted data
A vulnerability in the `FAISS.deserialize_from_bytes` function of langchain-ai/langchain allows for pickle deserialization of untrusted data. This can lead to the execution of arbitrary commands via t...
litellm vulnerable to remote code execution based on using eval unsafely
BerriAI/litellm version v1.35.8 contains a vulnerability where an attacker can achieve remote code execution. The vulnerability exists in the `add_deployment` function, which decodes and decrypts envi...
Server-Side Request Forgery in langchain-community.retrievers.web_research.WebResearchRetriever
A Server-Side Request Forgery (SSRF) vulnerability exists in the Web Research Retriever component in langchain-community (langchain-community.retrievers.web_research.WebResearchRetriever). The vulnera...
Remote code execution in mlflow
A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.h...
PYSEC-2024-239
A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.h...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.5.0 or newer, enabling a maliciously uploaded PyTorch model to run arbitrary code on an end user’s syst...
MLFlow improper input validation
Remote Code Execution can occur in versions of the MLflow platform running version 1.11.0 or newer, enabling a maliciously crafted MLproject to execute arbitrary code on an end user’s system when run...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.5.0 or newer, enabling a maliciously uploaded Langchain AgentExecutor model to run arbitrary code on an...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.27.0 or newer, enabling a maliciously crafted Recipe to execute arbitrary code on an end user’s system...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.24.0 or newer, enabling a maliciously uploaded pmdarima model to run arbitrary code on an end user’s sy...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user’s syste...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.23.0 or newer, enabling a maliciously uploaded LightGBM scikit-learn model to run arbitrary code on an...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s...
MLFlow unsafe deserialization
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s...
litellm passes untrusted data to `eval` function without sanitization
A remote code execution (RCE) vulnerability exists in the berriai/litellm project due to improper control of the generation of code when using the `eval` function unsafely in the `litellm.get_secret()...
RunGptLLM class in LlamaIndex has a command injection
A command injection vulnerability exists in the RunGptLLM class of the llama_index library, version 0.9.47, used by the RunGpt framework from JinaAI to connect to Language Learning Models (LLMs). The...
langchain vulnerable to path traversal
langchain-ai/langchain is vulnerable to path traversal due to improper limitation of a pathname to a restricted directory ('Path Traversal') in its LocalFileStore functionality. An attacker can levera...
Insecure deserialization in BentoML
An insecure deserialization vulnerability exists in the BentoML framework, allowing remote code execution (RCE) by sending a specially crafted POST request. By exploiting this vulnerability, attackers...
Transformers Deserialization of Untrusted Data vulnerability
The huggingface/transformers library is vulnerable to arbitrary code execution through deserialization of untrusted data within the `load_repo_checkpoint()` function of the `TFPreTrainedModel()` class...
LangChain directory traversal vulnerability
LangChain through 0.1.10 allows ../ directory traversal by an actor who is able to control the final part of the path parameter in a load_chain call. This bypasses the intended behavior of loading con...
PYSEC-2024-45
LangChain through 0.1.10 allows ../ directory traversal by an actor who is able to control the final part of the path parameter in a load_chain call. This bypasses the intended behavior of loading con...
PYSEC-2024-43
LangChain through 0.1.10 allows ../ directory traversal by an actor who is able to control the final part of the path parameter in a load_chain call. This bypasses the intended behavior of loading con...
Cross-site Scripting in MLFlow
Insufficient sanitization in MLflow leads to XSS when running an untrusted recipe. This issue leads to a client-side RCE when running an untrusted recipe in Jupyter Notebook. The vulnerability stems...
MLFlow Cross-site Scripting vulnerability leads to client-side Remote Code Execution
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. This issue leads to a client-side RCE when running the recipe in Jupyter Notebook. The vulnerabil...