n8n Python Code node sandbox escape allows for RCE and file exfiltration.
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.
XSS in NiceGUI APIs via crafted method names leading to JavaScript `eval()`.
NiceGUI is a Python-based UI framework. Prior to version 3.8.0, several NiceGUI APIs that execute methods on client-side elements (`Element.run_method()`, `AgGrid.run_grid_method()`, `EChart.run_chart_method()`, and others) use an `eval()` fallback in the JavaScript-side `runMethod()` function. When user-controlled input is passed as the method name, an attacker can inject arbitrary JavaScript that executes in the victim's browser. Additionally, `Element.run_method()` and `Element.get_computed_prop()` used string interpolation instead of `json.dumps()` for the method/property name, allowing quote injection to break out of the intended string context. Version 3.8.0 contains a fix.
yt-dlp --netrc-cmd vulnerable to command injection via malicious URL.
yt-dlp is a command-line audio/video downloader. Starting in version 2023.06.21 and prior to version 2026.02.21, when yt-dlp's `--netrc-cmd` command-line option (or `netrc_cmd` Python API parameter) is used, an attacker could achieve arbitrary command injection on the user's system with a maliciously crafted URL. yt-dlp maintainers assume the impact of this vulnerability to be high for anyone who uses `--netrc-cmd` in their command/configuration or `netrc_cmd` in their Python scripts. Even though the maliciously crafted URL itself will look very suspicious to many users, it would be trivial for a maliciously crafted webpage with an inconspicuous URL to covertly exploit this vulnerability via HTTP redirect. Users without `--netrc-cmd` in their arguments or `netrc_cmd` in their scripts are unaffected. No evidence has been found of this exploit being used in the wild. yt-dlp version 2026.02.21 fixes this issue by validating all netrc "machine" values and raising an error upon unexpected input. As a workaround, users who are unable to upgrade should avoid using the `--netrc-cmd` command-line option (or `netrc_cmd` Python API parameter), or they should at least not pass a placeholder (`{}`) in their `--netrc-cmd` argument.
SQL injection in Ormar's min/max methods allows database exfiltration.
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.
Infinite loop in pypdf allows for Denial of Service via a crafted PDF.
pypdf is a free and open-source pure-python PDF library. Prior to 6.7.1, an attacker who uses this vulnerability can craft a PDF which leads to an infinite loop. This requires accessing the children of a TreeObject, for example as part of outlines. This vulnerability is fixed in 6.7.1.
A crafted PDF's /ToUnicode entry can cause a Denial of Service in pypdf.
pypdf is a free and open-source pure-python PDF library. Prior to 6.7.1, an attacker who uses this vulnerability can craft a PDF which leads to long runtimes and large memory consumption. This requires parsing the /ToUnicode entry of a font with unusually large values, for example during text extraction. This vulnerability is fixed in 6.7.1.
pypdf Denial of Service from malformed /FlateDecode PDF stream.
pypdf is a free and open-source pure-python PDF library. Prior to 6.7.1, an attacker who uses this vulnerability can craft a PDF which leads to long runtimes. This requires a malformed /FlateDecode stream, where the byte-by-byte decompression is used. This vulnerability is fixed in 6.7.1.
SSRF vulnerability in smolagents 1.24.0's LocalPythonExecutor component.
A weakness has been identified in huggingface smolagents 1.24.0. Impacted is the function requests.get/requests.post of the component LocalPythonExecutor. Executing a manipulation can lead to server-side request forgery. It is possible to launch the attack remotely. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
Isso is vulnerable to stored XSS in comment fields via improper escaping.
Isso is a lightweight commenting server written in Python and JavaScript. In commits before 0afbfe0691ee237963e8fb0b2ee01c9e55ca2144, there is a stored Cross-Site Scripting (XSS) vulnerability affecting the website and author comment fields. The website field was HTML-escaped using quote=False, which left single and double quotes unescaped. Since the frontend inserts the website value directly into a single-quoted href attribute via string concatenation, a single quote in the URL breaks out of the attribute context, allowing injection of arbitrary event handlers (e.g. onmouseover, onclick). The same escaping is missing entirely from the user-facing comment edit endpoint (PUT /id/) and the moderation edit endpoint (POST /id//edit/). This issue has been patched in commit 0afbfe0691ee237963e8fb0b2ee01c9e55ca2144. To workaround, nabling comment moderation (moderation = enabled = true in isso.cfg) prevents unauthenticated users from publishing comments, raising the bar for exploitation, but it does not fully mitigate the issue since a moderator activating a malicious comment would still expose visitors.
Flask fails to set the Vary: Cookie header, risking sensitive info cache.
Flask is a web server gateway interface (WSGI) web application framework. In versions 3.1.2 and below, when the session object is accessed, Flask should set the Vary: Cookie header., resulting in a Use of Cache Containing Sensitive Information vulnerability. The logic instructs caches not to cache the response, as it may contain information specific to a logged in user. This is handled in most cases, but some forms of access such as the Python in operator were overlooked. The severity and risk depend on the application being hosted behind a caching proxy that doesn't ignore responses with cookies, not setting a Cache-Control header to mark pages as private or non-cacheable, and accessing the session in a way that only touches keys without reading values or mutating the session. The issue has been fixed in version 3.1.3.
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.
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