VAITP Dataset

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Total vulnerabilities in the dataset (not showing ignored and non-python related vulnerabilties): 1787
1932
LangSmith SDKs may execute arbitrary code via untrusted public prompts.

LangSmith Client SDKs provide SDK's for interacting with the LangSmith platform. Prior to LangSmith SDK Python 0.8.0 and JS/TS 0.6.0, the LangSmith SDK's prompt pull methods (pull_prompt / pull_prompt_commit in Python, pullPrompt / pullPromptCommit in JS/TS) fetch and deserialize prompt manifests from the LangSmith Hub. These manifests may contain serialized LangChain objects and model configuration that affect runtime behavior. When pulling a public prompt by owner/name identifier, the manifest content is controlled by an external party, but prior versions of the SDK did not distinguish this from pulling a prompt within the caller's own organization. This vulnerability is fixed in LangSmith SDK Python 0.8.0 and JS/TS 0.6.0.

Checking
Input Validation and Sanitization
Insecure Parsing or Deserialization
Remote
1931
Pi.Alert unauthenticated RCE via code injection in config file settings.

Pi.Alert is a WIFI / LAN intruder detector with web service monitoring. Prior to 2026-05-07, Pi.Alert's SaveConfigFile() endpoint writes user-supplied numeric config values (e.g., SMTP_PORT) directly into pialert.conf without validation. Since pialert.conf is loaded via Python's exec() every 3โ€“5 minutes by the background cron process, an attacker can inject arbitrary Python code and achieve unauthenticated OS-level RCE. On default installations (PIALERT_WEB_PROTECTION = False), no credentials are required. This vulnerability is fixed in 2026-05-07.

Checking
Input Validation and Sanitization
Command Injection
Remote
1930
Pi.Alert unauthenticated RCE via code injection in the config editor.

Pi.Alert is a WIFI / LAN intruder detector with web service monitoring. Prior to 2026-05-07, Pi.Alert's web-based configuration editor allows arbitrary Python code to be injected into pialert.conf. Since the background scan daemon loads this file via Python's exec(), injected code executes as the daemon process. With web protection disabled (the default configuration), no authentication is required, making this an unauthenticated Remote Code Execution vulnerability. This vulnerability is fixed in 2026-05-07.

Checking
Input Validation and Sanitization
Command Injection
Remote
1929
Open redirect in Authlib OpenID grants when omitting the 'openid' scope.

Authlib is a Python library which builds OAuth and OpenID Connect servers. Prior to 1.6.12 and 1.7.1, an unauthenticated open redirect in Authlib's OpenIDImplicitGrant and OpenIDHybridGrant authorization endpoint lets a remote attacker cause the authorization server to issue an HTTP 302 to an attacker-chosen URL by submitting an authorization request that omits the openid scope. This vulnerability is fixed in 1.6.12 and 1.7.1.

Checking
Input Validation and Sanitization
Open Redirects
Remote
1928
Stored XSS in RELATE's user profile allows for admin account takeover.

RELATE is a web-based courseware package. Versions prior to commit 555f0efb1c5bd7531c07cd73724d7e566a81f620 have a stored cross-site scripting vulnerability that allows any enrolled student to execute arbitrary JavaScript in an administrator's browser session, potentially leading to full admin account takeover. The `get_user()` method in `ParticipationAdmin` renders user-controlled input using `mark_safe` combined with Python's % string formatting. This bypasses Django\'s automatic HTML escaping entirely. The value returned by `get_full_name` is derived directly from the `first_name` and `last_name` fields of the User model. These fields are freely editable by any authenticated user through the profile page (`/profile/`) with no sanitization applied. When an admin views the Participation list in the Django admin panel, the unsanitized value is rendered directly into the HTML response, causing the injected script to execute in the admin's browser. Commit 555f0efb1c5bd7531c07cd73724d7e566a81f620 fixes the issue.

Checking
Input Validation and Sanitization
Cross-Site Scripting (XSS)
Remote
1927
BentoML command injection via bentofile.yaml allows host code execution.

BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.39, a malicious bentofile.yaml containing a newline-injected value in envs[*].name produces unquoted RUN directives in the BentoML-generated Dockerfile. When the victim runs bentoml containerize on the imported bento, those RUN directives execute on the host during docker build. This vulnerability is fixed in 1.4.39.

Checking
Input Validation and Sanitization
Command Injection
Local
1926
Dockerfile injection in BentoML via `bento.yaml` allows code execution.

BentoML is a Python library for building online serving systems optimized for AI apps and model inference. Prior to 1.4.39, src/bentoml/_internal/container/frontend/dockerfile/templates/base_v2.j2 interpolates docker.base_image raw with no escaping, newline filtering, or validation. A malicious bento.yaml with a multi-line docker.base_image value smuggles arbitrary Dockerfile directives into the generated Dockerfile, and bentoml containerize then runs docker build which executes the injected RUN directives on the victim host. This vulnerability is fixed in 1.4.39.

Checking
Input Validation and Sanitization
Command Injection
Local
1925
Mistune Image directive allows CSS injection via width/height options.

Mistune is a Python Markdown parser with renderers and plugins. Prior to 3.2.1, the Image directive plugin validates the :width: and :height: options with a regex compiled as _num_re = re.compile(r"^\d+(?:\.\d*)?"). When the validated value is not a plain integer, render_block_image() inserts it directly into a style="width:...;" or style="height:...;" attribute. Because the value was accepted by the prefix-only regex, any CSS after the leading digits reaches the style= attribute verbatim and without escaping. This vulnerability is fixed in 3.2.1.

Checking
Input Validation and Sanitization
Cross-Site Scripting (XSS)
Remote
1924
Mistune vulnerable to XSS in TOC rendering via unescaped heading text.

Mistune is a Python Markdown parser with renderers and plugins. Prior to 3.2.1, render_toc_ul() builds a <ul> table-of-contents tree from a list of (level, id, text) tuples. Both the id value (used as href="#<id>") and the text value (used as the visible link label) are inserted into <a> tags via a plain Python format string โ€” with no HTML escaping applied to either value. When heading IDs are derived from user-supplied heading text (the standard use-case for readable slug anchors), an attacker can craft a heading whose text breaks out of the href="#..." attribute context, injecting arbitrary HTML tags including <script> blocks directly into the rendered TOC. This vulnerability is fixed in 3.2.1.

Checking
Input Validation and Sanitization
Cross-Site Scripting (XSS)
Remote
1923
Mistune is vulnerable to XSS via unsanitized HTML heading IDs.

Mistune is a Python Markdown parser with renderers and plugins. Prior to 3.2.1, HTMLRenderer.heading() builds the opening <hN> tag by string-concatenating the id attribute value directly into the HTML โ€” with no call to escape(), safe_entity(), or any other sanitisation function. A double-quote character " in the id value terminates the attribute, allowing an attacker to inject arbitrary additional attributes (event handlers, src=, href=, etc.) into the heading element. This vulnerability is fixed in 3.2.1.

Checking
Input Validation and Sanitization
Cross-Site Scripting (XSS)
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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