VAITP Dataset

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Total vulnerabilities in the dataset (not showing ignored and non-python related vulnerabilties): 1612
1580
CVE-2026-23946
Insecure deserialization in Tendenci's Helpdesk allows authenticated RCE.

Tendenci is an open source content management system built for non-profits, associations and cause-based sites. Versions 15.3.11 and below include a critical deserialization vulnerability in the Helpdesk module (which is not enabled by default). This vulnerability allows Remote Code Execution (RCE) by an authenticated user with staff security level due to using Python's pickle module in helpdesk /reports/. The original CVE-2020-14942 was incompletely patched. While ticket_list() was fixed to use safe JSON deserialization, the run_report() function still uses unsafe pickle.loads(). The impact is limited to the permissions of the user running the application, typically www-data, which generally lacks write (except for upload directories) and execute permissions. This issue has been fixed in version 15.3.12.

Timing/Serialization
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
1579
CVE-2026-22807
Untrusted code execution in vLLM via malicious Hugging Face model repos.

vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.14.0, vLLM loads Hugging Face `auto_map` dynamic modules during model resolution without gating on `trust_remote_code`, allowing attacker-controlled Python code in a model repo/path to execute at server startup. An attacker who can influence the model repo/path (local directory or remote Hugging Face repo) can achieve arbitrary code execution on the vLLM host during model load. This happens before any request handling and does not require API access. Version 0.14.0 fixes the issue.

Checking
Design Defects
Remote File Inclusion (RFI)
Remote
1578
CVE-2025-12781
Python's base64 decode accepts +/ regardless of the altchars parameter.

When passing data to the b64decode(), standard_b64decode(), and urlsafe_b64decode() functions in the "base64" module the characters "+/" will always be accepted, regardless of the value of "altchars" parameter, typically used to establish an "alternative base64 alphabet" such as the URL safe alphabet. This behavior matches what is recommended in earlier base64 RFCs, but newer RFCs now recommend either dropping characters outside the specified base64 alphabet or raising an error. The old behavior has the possibility of causing data integrity issues. This behavior can only be insecure if your application uses an alternate base64 alphabet (without "+/"). If your application does not use the "altchars" parameter or the urlsafe_b64decode() function, then your application does not use an alternative base64 alphabet. The attached patches DOES NOT make the base64-decode behavior raise an error, as this would be a change in behavior and break existing programs. Instead, the patch deprecates the behavior which will be replaced with the newly recommended behavior in a future version of Python.ย Users are recommended to mitigate by verifying user-controlled inputs match the base64 alphabet they are expecting or verify that their application would not be affected if the b64decode() functions accepted "+" or "/" outside of altchars.

Checking
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
1577
CVE-2025-56005
PLY's yacc() `picklefile` param allows RCE via unsafe deserialization.

An undocumented and unsafe feature in the PLY (Python Lex-Yacc) library 3.11 allows Remote Code Execution (RCE) via the `picklefile` parameter in the `yacc()` function. This parameter accepts a `.pkl` file that is deserialized with `pickle.load()` without validation. Because `pickle` allows execution of embedded code via `__reduce__()`, an attacker can achieve code execution by passing a malicious pickle file. The parameter is not mentioned in official documentation or the GitHub repository, yet it is active in the PyPI version. This introduces a stealthy backdoor and persistence risk.

Checking
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
1576
CVE-2026-0863
n8n Python sandbox escape via the Code block allows arbitrary code execution.

Using string formatting and exception handling, an attacker may bypass n8n's python-task-executor sandbox restrictions and run arbitrary unrestricted Python code in the underlying operating system. The vulnerability can be exploited via the Code block by an authenticated user with basic permissions and can lead to a full n8n instance takeover on instances operating under "Internal" execution mode. If the instance is operating under the "External" execution mode (ex. n8n's official Docker image) - arbitrary code execution occurs inside a Sidecar container and not the main node, which significantly reduces the vulnerability impact.

Checking
Input Validation and Sanitization
Poorly Designed Access Controls
Remote
1575
CVE-2026-23490
pyasn1: DoS via memory exhaustion from a malformed RELATIVE-OID.

pyasn1 is a generic ASN.1 library for Python. Prior to 0.6.2, a Denial-of-Service issue has been found that leads to memory exhaustion from malformed RELATIVE-OID with excessive continuation octets. This vulnerability is fixed in 0.6.2.

Checking
Resource Management
Insecure Parsing or Deserialization
Remote
1574
CVE-2026-23528
Dask dashboard XSS via Jupyter proxy allows for remote code execution.

Dask distributed is a distributed task scheduler for Dask. Prior to 2026.1.0, when Jupyter Lab, jupyter-server-proxy, and Dask distributed are all run together, it is possible to craft a URL which will result in code being executed by Jupyter due to a cross-side-scripting (XSS) bug in the Dask dashboard. It is possible for attackers to craft a phishing URL that assumes Jupyter Lab and Dask may be running on localhost and using default ports. If a user clicks on the malicious link it will open an error page in the Dask Dashboard via the Jupyter Lab proxy which will cause code to be executed by the default Jupyter Python kernel. This vulnerability is fixed in 2026.1.0.

Checking
Input Validation and Sanitization
Cross-Site Scripting (XSS)
Remote
1573
CVE-2026-0897
DoS in Keras HDF5 loading via memory exhaustion from a crafted model file.

Allocation of Resources Without Limits or Throttling in the HDF5 weight loading componentย in Googleย Kerasย 3.0.0 through 3.13.0ย on all platformsย allows a remote attackerย to cause a Denial of Service (DoS) through memory exhaustion and a crash of the Python interpreterย via a crafted .keras archive containing a valid model.weights.h5 file whose dataset declares an extremely large shape.

Checking
Resource Management
Resource Exhaustion
Remote
1572
CVE-2026-22779
CRLF injection in the BlackSheep HTTP client via unsanitized headers.

BlackSheep is an asynchronous web framework to build event based web applications with Python. Prior to 2.4.6, the HTTP Client implementation in BlackSheep is vulnerable to CRLF injection. Missing headers validation makes it possible for an attacker to modify the HTTP requests (e.g. insert a new header) or even create a new HTTP request. Exploitation requires developers to pass unsanitized user input directly into headers.The server part is not affected because BlackSheep delegates to an underlying ASGI server handling of response headers. This vulnerability is fixed in 2.4.6.

Checking
Input Validation and Sanitization
Server-Side Request Forgery (SSRF)
Remote
1570
CVE-2026-21226
RCE via untrusted deserialization in Azure Core Python library.

Deserialization of untrusted data in Azure Core shared client library for Python allows an authorized attacker to execute code over a network.

Timing/Serialization
Input Validation and Sanitization
Insecure Parsing or Deserialization
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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Sun Tzu – “The Art of War”

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