Python CVE database

Wazuh is a free and open source platform used for threat prevention, detection, and response. Starting in version 4.4.0 and prior to version 4.9.1, an unsafe deserialization vulnerability allows for remote code execution on Wazuh servers. DistributedAPI parameters are a serialized as JSON and deserialized using `as_wazuh_object` (in `framework/wazuh/core/cluster/common.py`). If an attacker manages to inject an unsanitized dictionary in DAPI request/response, they can forge an unhandled exception (`__unhandled_exc__`) to evaluate arbitrary python code. The vulnerability can be triggered by anybody with API access (compromised dashboard or Wazuh servers in the cluster) or, in certain configurations, even by a compromised agent. Version 4.9.1 contains a fix.

Fixed in 4.9.1

Langflow is a tool for building and deploying AI-powered agents and workflows. In versions prior to 1.9.0, the POST /api/v1/build_public_tmp/{flow_id}/flow endpoint allows building public flows without requiring authentication. When the optional data parameter is supplied, the endpoint uses attacker-controlled flow data (containing arbitrary Python code in node definitions) instead of the stored flow data from the database. This code is passed to exec() with zero sandboxing, resulting in unauthenticated remote code execution. This is distinct from CVE-2025-3248, which fixed /api/v1/validate/code by adding authentication. The build_public_tmp endpoint is designed to be unauthenticated (for public flows) but incorrectly accepts attacker-supplied flow data containing arbitrary executable code. This issue has been fixed in version 1.9.0.

Fixed in 1.8.2

marimo is a reactive Python notebook. Prior to 0.23.0, Marimo has a Pre-Auth RCE vulnerability. The terminal WebSocket endpoint /terminal/ws lacks authentication validation, allowing an unauthenticated attacker to obtain a full PTY shell and execute arbitrary system commands. Unlike other WebSocket endpoints (e.g., /ws) that correctly call validate_auth() for authentication, the /terminal/ws endpoint only checks the running mode and platform support before accepting connections, completely skipping authentication verification. This vulnerability is fixed in 0.23.0.

Fixed in 0.23.0

EPyT-Flow is a Python package designed for the easy generation of hydraulic and water quality scenario data of water distribution networks. Prior to 0.16.1, EPyT-Flow’s REST API parses attacker-controlled JSON request bodies using a custom deserializer (my_load_from_json) that supports a type field. When type is present, the deserializer dynamically imports an attacker-specified module/class and instantiates it with attacker-supplied arguments. This allows invoking dangerous classes such as subprocess.Popen, which can lead to OS command execution during JSON parsing. This also affects the loading of JSON files. This vulnerability is fixed in 0.16.1.

Fixed in 0.16.1

Mesop is a Python-based UI framework that allows users to build web applications. Versions 1.2.2 and below contain a Path Traversal vulnerability that allows any user supplying an untrusted state_token through the UI stream payload to arbitrarily target files on the disk under the standard file-based runtime backend. This can result in application denial of service (via crash loops when reading non-msgpack target files as configurations), or arbitrary file manipulation. This vulnerability heavily exposes systems hosted utilizing FileStateSessionBackend. Unauthorized malicious actors could interact with arbitrary payloads overwriting or explicitly removing underlying service resources natively outside the application bounds. This issue has been fixed in version 1.2.3.

Fixed in 1.2.3

Tautulli is a Python based monitoring and tracking tool for Plex Media Server. Prior to version 2.17.0, the str_eval() function in notification_handler.py implements a sandboxed eval() for notification text templates. The sandbox attempts to restrict callable names by inspecting code.co_names of the compiled code object. However, co_names only contains names from the outer code object. When a lambda expression is used, it creates a nested code object whose attribute accesses are stored in code.co_consts, NOT in code.co_names. The sandbox never inspects nested code objects. This issue has been patched in version 2.17.0.

Fixed in 2.17.0

FastMCP is a Pythonic way to build MCP servers and clients. Prior to version 3.2.0, the OpenAPIProvider in FastMCP exposes internal APIs to MCP clients by parsing OpenAPI specifications. The RequestDirector class is responsible for constructing HTTP requests to the backend service. A vulnerability exists in the _build_url() method. When an OpenAPI operation defines path parameters (e.g., /api/v1/users/{user_id}), the system directly substitutes parameter values into the URL template string without URL-encoding. Subsequently, urllib.parse.urljoin() resolves the final URL. Since urljoin() interprets ../ sequences as directory traversal, an attacker controlling a path parameter can perform path traversal attacks to escape the intended API prefix and access arbitrary backend endpoints. This results in authenticated SSRF, as requests are sent with the authorization headers configured in the MCP provider. This issue has been patched in version 3.2.0.

Fixed in 3.2.0

PraisonAI is a multi-agent teams system. Prior to version 1.5.90, execute_code() in praisonai-agents runs attacker-controlled Python inside a three-layer sandbox that can be fully bypassed by passing a str subclass with an overridden startswith() method to the _safe_getattr wrapper, achieving arbitrary OS command execution on the host. This issue has been patched in version 1.5.90.

Fixed in 1.5.90

Semantic Kernel, Microsoft's semantic kernel Python SDK, has a remote code execution vulnerability in versions prior to 1.39.4, specifically within the `InMemoryVectorStore` filter functionality. The problem has been fixed in version `python-1.39.4`. Users should upgrade this version or higher. As a workaround, avoid using `InMemoryVectorStore` for production scenarios.

Fixed in 1.39.4

IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the code validation API endpoint. The POST /api/v1/validate/code endpoint accepts user-supplied Python code and executes it directly using Python's built-in exec() function without sandboxing, input validation, or privilege restrictions, enabling any authenticated user to execute arbitrary system commands with the full privileges of the Langflow server process.

Fixed in 1.10.1

IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the disk-based caching mechanism. The AsyncDiskCache class uses Python's unsafe pickle.loads() function to deserialize cached objects from disk without validation, integrity verification, or authentication, enabling arbitrary code execution when malicious pickle payloads are processed. Attackers who can influence cached data through file system access, malicious workflow inputs, custom components, or API manipulation can achieve complete system compromise with the privileges of the Langflow server process.

Fixed in 1.10.1

IBM Langflow OSS 1.0.0 through 1.10.0 Langflow versions up to 1.9.2 (commit 94981c443d4918517b9e8163d70fc598dc33a32d) contain a code injection vulnerability in the Policies component's ToolGuard integration that bypasses the allow_custom_components=false security control. The vulnerability exists because the validation mechanism only checks the main component source code in node_template["code"]["value"] but fails to validate dynamic CodeInput fields that store generated ToolGuard Python files. Attackers can embed malicious Python code in these unvalidated dynamic fields, which are persisted in Flow.data and later executed server-side when a guarded tool is invoked through the ToolGuard runtime. This allows authenticated users with flow creation privileges to achieve arbitrary Python code execution on the backend despite custom component restrictions. The vulnerability can be escalated through cross-tenant flow manipulation via the agentic MCP update_flow_component_field tool, which accepts attacker-controlled user_id parameters, enabling attackers to inject malicious code into victim users' flows. When combined with publicly accessible flows and specific misconfigurations (AUTO_LOGIN=true, NEW_USER_IS_ACTIVE=true), the attack can be conducted with reduced authentication requirements.

Fixed in 1.10.1

n8n is an open source workflow automation platform. Prior to version 2.4.8, a vulnerability in the Python Code node allows authenticated users to break out of the Python sandbox environment and execute code outside the intended security boundary. This issue has been patched in version 2.4.8.

Fixed in 2.4.8

n8n is an open source workflow automation platform. From version 1.0.0 to before 2.0.0, a sandbox bypass vulnerability exists in the Python Code Node that uses Pyodide. An authenticated user with permission to create or modify workflows can exploit this vulnerability to execute arbitrary commands on the host system running n8n, using the same privileges as the n8n process. This issue has been patched in version 2.0.0. Workarounds for this issue involve disabling the Code Node by setting the environment variable NODES_EXCLUDE: "[\"n8n-nodes-base.code\"]", disabling Python support in the Code node by setting the environment variable N8N_PYTHON_ENABLED=false, which was introduced in n8n version 1.104.0, and configuring n8n to use the task runner based Python sandbox via the N8N_RUNNERS_ENABLED and N8N_NATIVE_PYTHON_RUNNER environment variables.

Fixed in 2.0.0

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 vulnerability that allows unauthenticated remote attackers to force the server to make arbitrary HTTP requests. The vulnerability stems from the multipart form data and JSON request handlers, which automatically download files from user-provided URLs without validating whether those URLs point to internal network addresses, cloud metadata endpoints, or other restricted resources. The documentation explicitly promotes this URL-based file upload feature, making it an intended design that exposes all deployed services to SSRF attacks by default. Version 1.4.19 contains a patch for the issue.

Fixed in 1.4.19

Remote Code Execution security vulnerability in pgAdmin 4 (Query Tool and Cloud Deployment modules). The vulnerability is associated with the 2 POST endpoints; /sqleditor/query_tool/download, where the query_commited parameter and /cloud/deploy endpoint, where the high_availability parameter is unsafely passed to the Python eval() function, allowing arbitrary code execution. This issue affects pgAdmin 4: before 9.2.

Fixed in 9.2

n8n is an open source workflow automation platform. Prior to versions 2.10.1, 2.9.3, and 1.123.22, an authenticated user with permission to create or modify workflows could use the Python Code node to escape the sandbox. The sandbox did not sufficiently restrict access to certain built-in Python objects, allowing an attacker to exfiltrate file contents or achieve RCE. On instances using internal Task Runners (default runner mode), this could result in full compromise of the n8n host. On instances using external Task Runners, the attacker might gain access to or impact other task executed on the Task Runner. Task Runners must be enabled using `N8N_RUNNERS_ENABLED=true`. The issue has been fixed in n8n versions 2.10.1, 2.9.3, and 1.123.22. Users should upgrade to this version or later to remediate the vulnerability. If upgrading is not immediately possible, administrators should consider the following temporary mitigations. Limit workflow creation and editing permissions to fully trusted users only., and/or disable the Code node by adding `n8n-nodes-base.code` to the `NODES_EXCLUDE` environment variable. These workarounds do not fully remediate the risk and should only be used as short-term mitigation measures.

Fixed in 2.10.1

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.9.0, the Agentic Assistant feature in Langflow executes LLM-generated Python code during its validation phase. Although this phase appears intended to validate generated component code, the implementation reaches dynamic execution sinks and instantiates the generated class server-side. In deployments where an attacker can access the Agentic Assistant feature and influence the model output, this can result in arbitrary server-side Python execution. Version 1.9.0 fixes the issue.

Fixed in 1.9.0

PraisonAI is a multi-agent teams system. Prior to 1.5.115, execute_code() in praisonaiagents.tools.python_tools defaults to sandbox_mode="sandbox", which runs user code in a subprocess wrapped with a restricted __builtins__ dict and an AST-based blocklist. The AST blocklist embedded inside the subprocess wrapper (blocked_attrs of python_tools.py) contains only 11 attribute names — a strict subset of the 30+ names blocked in the direct-execution path. The four attributes that form a frame-traversal chain out of the sandbox are all absent from the subprocess list (__traceback__, tb_frame, f_back, and f_builtins). Chaining these attributes through a caught exception exposes the real Python builtins dict of the subprocess wrapper frame, from which exec can be retrieved and called under a non-blocked variable name — bypassing every remaining security layer. This vulnerability is fixed in 1.5.115.

Fixed in 1.5.115

cryptography is a package designed to expose cryptographic primitives and recipes to Python developers. From 45.0.0 to before 46.0.7, if a non-contiguous buffer was passed to APIs which accepted Python buffers (e.g. Hash.update()), this could lead to buffer overflows. This vulnerability is fixed in 46.0.7.

Fixed in 46.0.7

Agno versions prior to 2.3.24 contain an arbitrary code execution vulnerability in the model execution component that allows attackers to execute arbitrary Python code by manipulating the field_type parameter passed to eval(). Attackers can influence the field_type value in a FunctionCall to achieve remote code execution.

Fixed in 2.3.24

Crawl4AI is an open-source LLM friendly web crawler & scraper. Prior to 0.8.7, the _safe_eval_expression() function in the computed fields feature uses an AST validator that only blocks attributes starting with underscore. Python generator and frame object attributes (gi_frame, f_back, f_builtins) do NOT start with underscore, enabling a complete sandbox escape to achieve arbitrary code execution. The attack requires no authentication (JWT disabled by default) and is triggered via POST /crawl with a crafted extraction schema. This vulnerability is fixed in 0.8.7.

Fixed in 0.8.7

InHand Networks IR912 V1.0.0.r20042 and IR915 V1.0.0.r20042 (including earlier versions) were discovered to contain a command injection vulnerability in the Python application export function. This vulnerability allows remote attackers to execute arbitrary commands as root via a crafted input.

Fixed in 1.0.0.r20044

InHand Networks IR912 V1.0.0.r20042 and IR915 V1.0.0.r20042 (including earlier versions) were discovered to contain a command injection vulnerability in the Python configuration function. This vulnerability allows remote attackers to execute arbitrary commands as root via a crafted input.

Fixed in 1.0.0.r20044

Python StateMachine versions 3.0.0 before 3.2.0 contains a remote code execution vulnerability that allows attackers to execute arbitrary code by supplying malicious SCXML documents containing crafted `<data expr="...">` attributes evaluated unsafely. The SCXMLProcessor passes attacker-controlled expression strings through a call chain ending in Python's built-in eval() without sandboxing, enabling arbitrary code execution in the context of the hosting process.

Fixed in 3.2.0

XWiki Platform is a generic wiki platform offering runtime services for applications built on top of it. Prior to 17.4.8 and 17.10.1, an improperly protected scripting API allows any user with script right to bypass the sandboxing of the Velocity scripting API and execute, e.g., arbitrary Python scripts, allowing full access to the XWiki instance and thereby compromising the confidentiality, integrity and availability of the whole instance. Note that script right already constitutes a high level of access that we don't recommend giving to untrusted users. This vulnerability is fixed in 17.4.8 and 17.10.1.

Fixed in 17.10.1

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause a remote code execution by manipulating the model name parameter in the model control APIs. A successful exploit of this vulnerability might lead to remote code execution, denial of service, information disclosure, and data tampering.

Fixed in 25.08

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the CSV_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. An attacker can leverage this vulnerability to execute code in the context of the user running the server. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the CSV Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the Flowise server. This vulnerability is fixed in 3.1.0.

Fixed in 3.1.0

PraisonAI is a multi-agent teams system. In versions below 4.5.139 of PraisonAI and 1.5.140 of praisonaiagents, the workflow engine is vulnerable to arbitrary command and code execution through untrusted YAML files. When praisonai workflow run <file.yaml> loads a YAML file with type: job, the JobWorkflowExecutor in job_workflow.py processes steps that support run: (shell commands via subprocess.run()), script: (inline Python via exec()), and python: (arbitrary Python script execution)—all without any validation, sandboxing, or user confirmation. The affected code paths include action_run() in workflow.py and _exec_shell(), _exec_inline_python(), and _exec_python_script() in job_workflow.py. An attacker who can supply or influence a workflow YAML file (particularly in CI pipelines, shared repositories, or multi-tenant deployment environments) can achieve full arbitrary command execution on the host system, compromising the machine and any accessible data or credentials. This issue has been fixed in versions 4.5.139 of PraisonAI and 1.5.140 of praisonaiagents.

Fixed in 1.5.140

The Keras Model.load_model function permits arbitrary code execution, even with safe_mode=True, through a manually constructed, malicious .keras archive. By altering the config.json file within the archive, an attacker can specify arbitrary Python modules and functions, along with their arguments, to be loaded and executed during model loading.

Fixed in 3.8.0

Pipecat is an open-source Python framework for building real-time voice and multimodal conversational agents. Versions 0.0.41 through 0.0.93 have a vulnerability in `LivekitFrameSerializer` – an optional, non-default, undocumented frame serializer class (now deprecated) intended for LiveKit integration. The class's `deserialize()` method uses Python's `pickle.loads()` on data received from WebSocket clients without any validation or sanitization. This means that a malicious WebSocket client can send a crafted pickle payload to execute arbitrary code on the Pipecat server. The vulnerable code resides in `src/pipecat/serializers/livekit.py` (around line 73), where untrusted WebSocket message data is passed directly into `pickle.loads()` for deserialization. If a Pipecat server is configured to use LivekitFrameSerializer and is listening on an external interface (e.g. 0.0.0.0), an attacker on the network (or the internet, if the service is exposed) could achieve remote code execution (RCE) on the server by sending a malicious pickle payload. Version 0.0.94 contains a fix. Users of Pipecat should avoid or replace unsafe deserialization and improve network security configuration. The best mitigation is to stop using the vulnerable LivekitFrameSerializer altogether. Those who require LiveKit functionality should upgrade to the latest Pipecat version and switch to the recommended `LiveKitTransport` or another secure method provided by the framework. Additionally, always follow secure coding practices: never trust client-supplied data, and avoid Python pickle (or similar unsafe deserialization) in network-facing components.

Fixed in 0.0.94

A Python command injection vulnerability exists in the `SagemakerLLM` class's `complete()` method within `./private_gpt/components/llm/custom/sagemaker.py` of the imartinez/privategpt application, versions up to and including 0.3.0. The vulnerability arises due to the use of the `eval()` function to parse a string received from a remote AWS SageMaker LLM endpoint into a dictionary. This method of parsing is unsafe as it can execute arbitrary Python code contained within the response. An attacker can exploit this vulnerability by manipulating the response from the AWS SageMaker LLM endpoint to include malicious Python code, leading to potential execution of arbitrary commands on the system hosting the application. The issue is fixed in version 0.6.0.

Fixed in 0.6.0

Gradio is an open-source Python package designed for quick prototyping. This vulnerability relates to **Server-Side Request Forgery (SSRF)** in the `/queue/join` endpoint. Gradio’s `async_save_url_to_cache` function allows attackers to force the Gradio server to send HTTP requests to user-controlled URLs. This could enable attackers to target internal servers or services within a local network and possibly exfiltrate data or cause unwanted internal requests. Additionally, the content from these URLs is stored locally, making it easier for attackers to upload potentially malicious files to the server. This impacts users deploying Gradio servers that use components like the Video component which involve URL fetching. Users are advised to upgrade to `gradio>=5` to address this issue. As a workaround, users can disable or heavily restrict URL-based inputs in their Gradio applications to trusted domains only. Additionally, implementing stricter URL validation (such as allowinglist-based validation) and ensuring that local or internal network addresses cannot be requested via the `/queue/join` endpoint can help mitigate the risk of SSRF attacks.

Fixed in 5.0.0

MEGABOT is a fully customized Discord bot for learning and fun. The `/math` command and functionality of MEGABOT versions < 1.5.0 contains a remote code execution vulnerability due to a Python `eval()`. The vulnerability allows an attacker to inject Python code into the `expression` parameter when using `/math` in any Discord channel. This vulnerability impacts any discord guild utilizing MEGABOT. This vulnerability was fixed in release version 1.5.0.

Fixed in 1.5.0

Deserialization of untrusted data in Apache Fory PyFory. PyFory's ReduceSerializer could bypass documented DeserializationPolicy validation hooks during reduce-state restoration and global-name resolution. An application is vulnerable if it deserializes attacker-controlled data using PyFory Python-native mode with strict mode disabled and relies on DeserializationPolicy to restrict unsafe classes, functions, or module attributes. This issue affects Apache Fory: from before 1.0.0. Mitigation: Users of Apache Fory are recommended to upgrade to version 1.0.0 or later, which enforces DeserializationPolicy validation for the affected ReduceSerializer paths and thus fixes this issue.

Fixed in 1.0.0

PraisonAI is a multi-agent teams system. Prior to version 4.6.9, the fix for PraisonAI's MCP command handling does not add a command allowlist or argument validation to parse_mcp_command(), allowing arbitrary executables like bash, python, or /bin/sh with inline code execution flags to pass through to subprocess execution. This issue has been patched in version 4.6.9.

Fixed in 4.6.9

Arelle before 2.39.10 contains an unauthenticated remote code execution vulnerability in the /rest/configure REST endpoint that accepts a plugins query parameter and forwards it to the plugin manager without authentication or authorization. Attackers can supply a URL to a malicious Python file through the plugins parameter, causing the Arelle webserver to download and execute the attacker-controlled code within the Arelle process with its privileges.

Fixed in 2.39.10

Roxy-WI is a web interface for managing Haproxy, Nginx, Apache and Keepalived servers. Versions prior to 8.2.6.4 have a SQL injection vulnerability in the haproxy_section_save function in app/routes/config/routes.py. The server_ip parameter, sourced from the URL path, is passed unsanitized through multiple function calls and ultimately interpolated into a SQL query string using Python string formatting, allowing attackers to execute arbitrary SQL commands. Version 8.2.6.4 fixes the issue.

Fixed in 8.2.6.4

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the Airtable_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the Airtable Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the flowise server. This vulnerability is fixed in 3.1.0.

Fixed in 3.1.0

Python-Multipart is a streaming multipart parser for Python. Prior to version 0.0.22, a Path Traversal vulnerability exists when using non-default configuration options `UPLOAD_DIR` and `UPLOAD_KEEP_FILENAME=True`. An attacker can write uploaded files to arbitrary locations on the filesystem by crafting a malicious filename. Users should upgrade to version 0.0.22 to receive a patch or, as a workaround, avoid using `UPLOAD_KEEP_FILENAME=True` in project configurations.

Fixed in 0.0.22

NiceGUI is a Python-based UI framework. Prior to 3.7.0, NiceGUI's FileUpload.name property exposes client-supplied filename metadata without sanitization, enabling path traversal when developers use the pattern UPLOAD_DIR / file.name. Malicious filenames containing ../ sequences allow attackers to write files outside intended directories, with potential for remote code execution through application file overwrites in vulnerable deployment patterns. This design creates a prevalent security footgun affecting applications following common community patterns. Note: Exploitation requires application code incorporating file.name into filesystem paths without sanitization. Applications using fixed paths, generated filenames, or explicit sanitization are not affected. This vulnerability is fixed in 3.7.0.

Fixed in 3.7.0