VAITP Dataset

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Total vulnerabilities in the dataset (not showing ignored and non-python related vulnerabilties): 1438
1555
CVE-2026-21872
Cross-Site Scripting in NiceGUI ui.sub_pages via crafted link click.

NiceGUI is a Python-based UI framework. From versions 2.22.0 to 3.4.1, an unsafe implementation in the click event listener used by ui.sub_pages, combined with attacker-controlled link rendering on the page, causes XSS when the user actively clicks on the link. This issue has been patched in version 3.5.0.

Checking
Input Validation and Sanitization
Cross-Site Scripting (XSS)
Remote
1554
CVE-2026-21871
XSS in NiceGUI's ui.navigate.history allows arbitrary JavaScript execution.

NiceGUI is a Python-based UI framework. From versions 2.13.0 to 3.4.1, there is a XSS risk in NiceGUI when developers pass attacker-controlled strings into ui.navigate.history.push() or ui.navigate.history.replace(). These helpers are documented as History API wrappers for updating the browser URL without page reload. However, if the URL argument is embedded into generated JavaScript without proper escaping, a crafted payload can break out of the intended string context and execute arbitrary JavaScript in the victimโ€™s browser. Applications that do not pass untrusted input into ui.navigate.history.push/replace are not affected. This issue has been patched in version 3.5.0.

Checking
Input Validation and Sanitization
Cross-Site Scripting (XSS)
Remote
1553
CVE-2026-21883
Bokeh's flawed Origin allowlist validation allows WebSocket hijacking.

Bokeh is an interactive visualization library written in Python. In versions 3.8.1 and below, if a server is configured with an allowlist (e.g., dashboard.corp), an attacker can register a domain like dashboard.corp.attacker.com (or use a subdomain if applicable) and lure a victim to visit it. The malicious site can then initiate a WebSocket connection to the vulnerable Bokeh server. Since the Origin header (e.g., http://dashboard.corp.attacker.com/) matches the allowlist according to the flawed logic, the connection is accepted. Once connected, the attacker can interact with the Bokeh server on behalf of the victim, potentially accessing sensitive data, or modifying visualizations. This issue is fixed in version 3.8.2.

Checking
Authentication, Authorization, and Session Management
Cross-Site Request Forgery (CSRF)
Remote
1552
CVE-2025-15346
wolfssl-py fails to enforce client certificates, allowing mTLS bypass.

A vulnerability in the handling of verify_mode = CERT_REQUIRED in the wolfssl Python package (wolfssl-py) causes client certificate requirements to not be fully enforced.ย  Because the WOLFSSL_VERIFY_FAIL_IF_NO_PEER_CERT flag was not included, the behavior effectively matched CERT_OPTIONAL: a peer certificate was verified if presented, but connections were incorrectly authenticated when no client certificate was provided.ย  This results in improper authentication, allowing attackers to bypass mutual TLS (mTLS) client authentication by omitting a client certificate during the TLS handshake.ย  The issue affects versions up to and including 5.8.2.

Checking
Authentication, Authorization, and Session Management
Improper SSL/TLS Certificate Validation
Remote
1551
CVE-2026-21441
urllib3 is vulnerable to a decompression bomb DoS via streamed HTTP redirects.

urllib3 is an HTTP client library for Python. urllib3's streaming API is designed for the efficient handling of large HTTP responses by reading the content in chunks, rather than loading the entire response body into memory at once. urllib3 can perform decoding or decompression based on the HTTP `Content-Encoding` header (e.g., `gzip`, `deflate`, `br`, or `zstd`). When using the streaming API, the library decompresses only the necessary bytes, enabling partial content consumption. Starting in version 1.22 and prior to version 2.6.3, for HTTP redirect responses, the library would read the entire response body to drain the connection and decompress the content unnecessarily. This decompression occurred even before any read methods were called, and configured read limits did not restrict the amount of decompressed data. As a result, there was no safeguard against decompression bombs. A malicious server could exploit this to trigger excessive resource consumption on the client. Applications and libraries are affected when they stream content from untrusted sources by setting `preload_content=False` when they do not disable redirects. Users should upgrade to at least urllib3 v2.6.3, in which the library does not decode content of redirect responses when `preload_content=False`. If upgrading is not immediately possible, disable redirects by setting `redirect=False` for requests to untrusted source.

Checking
Resource Management
Resource Exhaustion
Remote
1549
CVE-2025-14026
Forcepoint One DLP Client ctypes restriction bypass allows code execution.

Forcepoint One DLP Client, version 23.04.5642 (and possibly newer versions), includes a restricted version of Python 2.5.4 that prevents use of the ctypes library. ctypes is a foreign function interface (FFI) for Python, enabling calls to DLLs/shared libraries, memory allocation, and direct code execution. It was demonstrated that these restrictions could be bypassed.

Checking
Design Defects
Poorly Designed Access Controls
Local
1548
CVE-2025-69230
AIOHTTP: A crafted Cookie header can cause a logging storm and potential DoS.

AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. In versions 3.13.2 and below, reading multiple invalid cookies can lead to a logging storm. If the cookies attribute is accessed in an application, then an attacker may be able to trigger a storm of warning-level logs using a specially crafted Cookie header. This issue is fixed in 3.13.3.

Checking
Resource Management
Resource Exhaustion
Remote
1547
CVE-2025-69229
AIOHTTP chunked message handling can cause high CPU usage, leading to DoS.

AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. In versions 3.13.2 and below, handling of chunked messages can result in excessive blocking CPU usage when receiving a large number of chunks. If an application makes use of the request.read() method in an endpoint, it may be possible for an attacker to cause the server to spend a moderate amount of blocking CPU time (e.g. 1 second) while processing the request. This could potentially lead to DoS as the server would be unable to handle other requests during that time. This issue is fixed in version 3.13.3.

Timing/Serialization
Resource Management
Resource Exhaustion
Remote
1546
CVE-2025-69228
AIOHTTP server vulnerable to memory exhaustion from a crafted post request.

AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Versions 3.13.2 and below allow a request to be crafted in such a way that an AIOHTTP server's memory fills up uncontrollably during processing. If an application includes a handler that uses the Request.post() method, an attacker may be able to freeze the server by exhausting the memory. This issue is fixed in version 3.13.3.

Algorithm
Resource Management
Resource Exhaustion
Remote
1545
CVE-2025-69227
AIOHTTP DoS via infinite loop on POST requests with optimizations enabled.

AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Versions 3.13.2 and below allow for an infinite loop to occur when assert statements are bypassed, resulting in a DoS attack when processing a POST body. If optimizations are enabled (-O or PYTHONOPTIMIZE=1), and the application includes a handler that uses the Request.post() method, then an attacker may be able to execute a DoS attack with a specially crafted message. This issue is fixed in version 3.13.3.

Algorithm
Resource Management
Resource Exhaustion
Remote
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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