LangChain is a framework for developing applications powered by large language models. langchain_experimental (aka LangChain Experimental) in LangChain <= 0.0.14 allows an attacker to bypass the CVE-2023-36258 fix and execute arbitrary code via __import__ in Python code, which is not prohibited by pal_chain/base.py. 

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

LangChain is a framework for developing applications powered by large language models. LangChain before 0.0.317 allows SSRF via document_loaders/recursive_url_loader.py because crawling can proceed from an external server to an internal server. 

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The remote web server hosts MLflow web application

A MLflow Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A ZenML Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A Seaborn Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A Tensorboard Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A OpenAI Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A LLama.cpp Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A LangChain Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

OpenAI ChatGPT App is installed on the remote macOS or Mac OS X host.

The version of Keras installed on the remote host is prior to 2.13. It is, therefore, affected by an arbitrary code injection vulnerability in TensorFlow's Keras framework (<2.13) which allows attackers to execute arbitrary code with the same permissions as the application using a model that allow arbitrary code irrespective of the application.

    Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The host contains Hierarchical Data Format HDF5 (.h5) files. HDF5 files are often used as Machine Learning Model Files.

Note that this plugin only detects files in commonly used installation directories or a user specified search path.
 - Enable Thorough Tests to allow more time to scan.
 - Enable Report Verbosity to show more than 250 files in plugin output.

The host contains HuggingFace repositories, which may contain AI/LLM models.

A Horovod Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A scikit-learn Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A NumPy Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

A Keras Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

The remote host contains a torchserve version that is prior to  2.2.2. It is, therefore, affected by a remote code execution vulnerability.  A vulnerability in the PyTorch's torch.distributed.rpc framework, specifically in versions prior to 2.2.2, allows for remote code execution (RCE). The framework, which is used in distributed training scenarios, does not properly verify the functions being called during RPC (Remote Procedure Call) operations. This oversight permits attackers to execute arbitrary commands by leveraging built-in Python functions such as eval during multi-cpu RPC communication. The vulnerability arises from the lack of restriction on function calls when a worker node serializes and sends a PythonUDF (User Defined Function) to the master node, which then deserializes and executes the function without validation. This flaw can be exploited to compromise master nodes initiating distributed training, potentially leading to the theft of sensitive AI-related data.

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

A PyTorch Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

Microsoft Recall, an AI helper utility, is installed on the remote Windows host.

The version of Ollama installed on the remote host is prior to 0.1.29. It is, therefore, affected by a DNS rebinding vulnerability. Ollama before 0.1.29 has a DNS rebinding vulnerability that can inadvertently allow remote access to the full API, thereby letting an unauthorized user chat with a large language model, delete a model, or cause a denial of service (resource exhaustion).

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The version of Ollama installed on the remote host is prior to 0.1.34. It is, therefore, affected by an improper input validation vulnerability. Ollama before 0.1.34 does not validate the format of the digest (sha256 with 64 hex digits) when getting the model path, and thus mishandles the TestGetBlobsPath test cases such as fewer than 64 hex digits, more than 64 hex digits, or an initial ../ substring.

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

Ollama is installed on the remote macOS host.

An Intel Neural Compressor library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

The version of Intel Neural Compressor installed on the remote host is prior to 2.5.0. It is, therefore, affected by multiple vulnerabilities as referenced in the release notes.

    Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

This plugin utilizes various Nessus detection methods and reports software identified by to Nessus and known to utilize "Artificial Intelligence" (AI) and Large Language Model (LLM) technology.

Note that this plugin uses several detection methods. The products reported by this plugin will grow as more detections and methods are added.

A TensorFlow Python library is installed on the remote host. 

Note that Nessus has relied upon on the application's self-reported version number.

The remote web server hosts ZenML web application

The remote host contains a torchserve version that is prior to 2.11.3. It is, therefore, affected by a Server Side Request Forgery vulnerability in the api/cors endpoint.

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The remote host is running an NextChat webapp.

The remote web server hosts H2O Flow web application

The remote host contains a ray dashboard which is purposely lacking authentication features.  As such, it is therefore, affected by a remote code execution vulnerability in the jobs api endpoint.

The remote web server port is a TorchServe application.

The remote host contains a torchserve version that is prior to  0.8.2. It is, therefore, affected by a Server Side Request Forgery vulnerability.  TorchServe default configuration lacks proper input validation, enabling third parties to invoke remote HTTP download requests and write files to the disk. This issue could be taken advantage of to compromise the integrity of the system and sensitive data. This issue is present in versions 0.1.0 to 0.8.1. A remote attacker can exploit this and load the malicious model of their choice from any URL.

Note that Nessus has not tested for this issue but has instead relied only on the application's self-reported version number.

The remote host contains a torchserve version that is prior to  0.8.2. It is, therefore, affected by a Server Side Request Forgery vulnerability.  TorchServe default configuration lacks proper input validation, enabling third parties to invoke remote HTTP download requests and write files to the disk. This issue could be taken advantage of to compromise the integrity of the system and sensitive data. This issue is present in versions 0.1.0 to 0.8.1. A remote attacker can exploit this and load the malicious model of their choice from any URL.

ID	Name	Severity
206977	LangChain Experimental Python Library <= 0.0.14 (CVE-2023-44467)	critical
206976	LangChain Python Library < 0.0.317 (CVE-2023-46229)	high
206881	MLflow Detection	info
206880	MLflow Detection	info
206027	ZenML Detection	info
205590	Seaborn Detection	info
205589	Tensorboard Detection	info
205586	OpenAi Detection	info
205585	LLama.cpp Python Bindings Detection	info
205584	LangChain Detection	info
205382	OpenAI ChatGPT App Installed (macOS)	info
205011	Keras < 2.13 Arbitrary Code Injection	critical
202721	Hierarchical Data Format HDF5 File Detection for Linux/UNIX	info
201924	HuggingFace Git Repo Detection for Linux/UNIX	info
201193	Ray Dashboard Detection	info
201192	Horovod Detection	info
201191	Scikit-learn Detection	info
201190	NumPy Detection	info
201189	Keras Detection	info
200978	PyTorch < 2.2.2 RCE	critical
200977	PyTorch Detection	info
200452	Windows Recall Enabled	info
200186	Ollama < 0.1.29 DNS Rebinding	medium
200185	Ollama < 0.1.34 Improper Input Validation	high
200184	Ollama Installed (macOS)	info
198067	Intel Neural Compressor Library Detection	info
198066	Intel Neural Compressor < 2.5.0 Multiple Vulnerabilities	critical
196906	AI/LLM Software Report	info
195192	TensorFlow Detection	info
194954	ZenML Detection	info
194720	NextChat < 2.11.3 SSRF	critical
194719	NextChat / ChatGPT Next Web Detection	info
194478	H2O Flow Detection	info
193561	Ray Dashboard Job RCE (CVE-2023-48022)	critical
193560	Ray Dashboard Detection	info
184082	PyTorch TorchServe API detection	info
184081	PyTorch TorchServe < 0.8.2 SSRF	critical
184080	PyTorch TorchServe SSRF (CVE-2023-43654)	critical

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