Python CVE database

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Conda-build contains commands and tools to build conda packages. Prior to version 25.3.0, the pyproject.toml lists conda-index as a Python dependency. This package is not published in PyPI. An attacker could claim this namespace and upload arbitrary (malicious) code to the package, and then exploit pip install commands by injecting the malicious dependency in the solve. This issue has been fixed in version 25.3.0. A workaround involves using --no-deps for pip install-ing the project from the repository.

Fixed in 25.3.0

Langroid is a Python framework to build large language model (LLM)-powered applications. Prior to version 0.53.15, `LanceDocChatAgent` uses pandas eval() through `compute_from_docs()`. As a result, an attacker may be able to make the agent run malicious commands through `QueryPlan.dataframe_calc]`) compromising the host system. Langroid 0.53.15 sanitizes input to the affected function by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation.

Fixed in 0.53.15

Langroid is a Python framework to build large language model (LLM)-powered applications. Prior to version 0.53.15, `TableChatAgent` uses `pandas eval()`. If fed by untrusted user input, like the case of a public-facing LLM application, it may be vulnerable to code injection. Langroid 0.53.15 sanitizes input to `TableChatAgent` by default to tackle the most common attack vectors, and added several warnings about the risky behavior in the project documentation.

Fixed in 0.53.15

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

PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.

Fixed in 2.6.0

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 specific headers and parameters in the POST request, it is possible to execute any unauthorized arbitrary code on the server, which will grant the attackers to have the initial access and information disclosure on the server. This vulnerability is fixed in 1.4.8.

Fixed in 1.4.8

A maliciously crafted QPY file can potential execute arbitrary-code embedded in the payload without privilege escalation when deserialising QPY formats < 13. A python process calling Qiskit 0.18.0 through 1.4.1's `qiskit.qpy.load()` function could potentially execute any arbitrary Python code embedded in the correct place in the binary file as part of specially constructed payload.

Fixed in 1.4.2

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

A vulnerability, that could result in Remote Code Execution (RCE), has been found in PlotAI. Lack of validation of LLM-generated output allows attacker to execute arbitrary Python code. Vendor commented out vulnerable line, further usage of the software requires uncommenting it and thus accepting the risk. The vendor does not plan to release a patch to fix this vulnerability.

Fixed in 0.0.7

Spotipy is a lightweight Python library for the Spotify Web API. The `CacheHandler` class creates a cache file to store the auth token. Prior to version 2.25.1, the file created has `rw-r--r--` (644) permissions by default, when it could be locked down to `rw-------` (600) permissions. This leads to overly broad exposure of the spotify auth token. If this token can be read by an attacker (another user on the machine, or a process running as another user), it can be used to perform administrative actions on the Spotify account, depending on the scope granted to the token. Version 2.25.1 tightens the cache file permissions.

Fixed in 2.25.1

Deserialization of untrusted data in IPC and Parquet readers in the Apache Arrow R package versions 4.0.0 through 16.1.0 allows arbitrary code execution. An application is vulnerable if it reads Arrow IPC, Feather or Parquet data from untrusted sources (for example, user-supplied input files). This vulnerability only affects the arrow R package, not other Apache Arrow implementations or bindings unless those bindings are specifically used via the R package (for example, an R application that embeds a Python interpreter and uses PyArrow to read files from untrusted sources is still vulnerable if the arrow R package is an affected version). It is recommended that users of the arrow R package upgrade to 17.0.0 or later. Similarly, it is recommended that downstream libraries upgrade their dependency requirements to arrow 17.0.0 or later. If using an affected version of the package, untrusted data can read into a Table and its internal to_data_frame() method can be used as a workaround (e.g., read_parquet(..., as_data_frame = FALSE)$to_data_frame()). This issue affects the Apache Arrow R package: from 4.0.0 through 16.1.0. Users are recommended to upgrade to version 17.0.0, which fixes the issue.

Fixed in 17.0.0

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

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

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

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

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

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

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

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

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

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

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

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

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

SciTokens is a reference library for generating and using SciTokens. Prior to version 1.9.6, the KeyCache class in scitokens was vulnerable to SQL Injection because it used Python's str.format() to construct SQL queries with user-supplied data (such as issuer and key_id). This allowed an attacker to execute arbitrary SQL commands against the local SQLite database. This issue has been patched in version 1.9.6.

Fixed in 1.9.6

pyLoad is a free and open-source download manager written in Python. From version 0.4.20 to before version 0.5.0b3.dev97, the local_check decorator in pyLoad's ClickNLoad feature can be bypassed by any remote attacker through HTTP Host header spoofing. This allows unauthenticated remote users to access localhost-restricted endpoints, enabling them to inject arbitrary downloads, write files to the storage directory, and execute JavaScript code. This issue has been patched in version 0.5.0b3.dev97.

Fixed in 0.5.0b3.dev97

Mesop is a Python-based UI framework that allows users to build web applications. In versions 1.2.2 and below, an explicit web endpoint inside the ai/ testing module infrastructure directly ingests untrusted Python code strings unconditionally without authentication measures, yielding standard Unrestricted Remote Code Execution. Any individual capable of routing HTTP logic to this server block will gain explicit host-machine command rights. The AI codebase package includes a lightweight debugging Flask server inside ai/sandbox/wsgi_app.py. The /exec-py route accepts base_64 encoded raw string payloads inside the code parameter natively evaluated by a basic POST web request. It saves it rapidly to the operating system logic path and injects it recursively using execute_module(module_path...). This issue has been fixed in version 1.2.3.

Fixed in 1.2.3

Authlib is a Python library which builds OAuth and OpenID Connect servers. From version 1.6.5 to before version 1.6.7, previous tests involving passing a malicious JWT containing alg: none and an empty signature was passing the signature verification step without any changes to the application code when a failure was expected.. This issue has been patched in version 1.6.7.

Fixed in 1.6.7

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.8.0, the CSV Agent node in Langflow hardcodes `allow_dangerous_code=True`, which automatically exposes LangChain’s Python REPL tool (`python_repl_ast`). As a result, an attacker can execute arbitrary Python and OS commands on the server via prompt injection, leading to full Remote Code Execution (RCE). Version 1.8.0 fixes the issue.

Fixed in 1.8.0

Black is the uncompromising Python code formatter. Black provides a GitHub action for formatting code. This action supports an option, use_pyproject: true, for reading the version of Black to use from the repository pyproject.toml. A malicious pull request could edit pyproject.toml to use a direct URL reference to a malicious repository. This could lead to arbitrary code execution in the context of the GitHub Action. Attackers could then gain access to secrets or permissions available in the context of the action. Version 26.3.0 fixes this vulnerability.

Fixed in 26.3.0

pyOpenSSL is a Python wrapper around the OpenSSL library. Starting in version 22.0.0 and prior to version 26.0.0, if a user provided callback to `set_cookie_generate_callback` returned a cookie value greater than 256 bytes, pyOpenSSL would overflow an OpenSSL provided buffer. Starting in version 26.0.0, cookie values that are too long are now rejected.

Fixed in 26.0.0

Ormar is a async mini ORM for Python. In versions 0.9.9 through 0.22.0, when performing aggregate queries, Ormar ORM constructs SQL expressions by passing user-supplied column names directly into `sqlalchemy.text()` without any validation or sanitization. The `min()` and `max()` methods in the `QuerySet` class accept arbitrary string input as the column parameter. While `sum()` and `avg()` are partially protected by an `is_numeric` type check that rejects non-existent fields, `min()` and `max()` skip this validation entirely. As a result, an attacker-controlled string is embedded as raw SQL inside the aggregate function call. Any unauthorized user can exploit this vulnerability to read the entire database contents, including tables unrelated to the queried model, by injecting a subquery as the column parameter. Version 0.23.0 contains a patch.

Fixed in 0.23.0