ghsa

### Summary When Tornado receives a request with two `Transfer-Encoding: chunked` headers, it ignores them both. This enables request smuggling when Tornado is deployed behind a proxy server that emits such requests. [Pound](https://en.wikipedia.org/wiki/Pound_(networking)) does this. ### PoC 0. Install Tornado. 1. Start a simple Tornado server that echoes each received request's body: ```bash cat << EOF > server.py import asyncio import tornado class MainHandler(tornado.web.RequestHandler): def post(self): self.write(self.request.body) async def main(): tornado.web.Application([(r"/", MainHandler)]).listen(8000) await asyncio.Event().wait() asyncio.run(main()) EOF python3 server.py & ``` 2. Send a valid chunked request: ```bash printf 'POST / HTTP/1.1\r\nTransfer-Encoding: chunked\r\n\r\n1\r\nZ\r\n0\r\n\r\n' | nc localhost 8000 ``` 3. Observe that the response is as expected: ``` HTTP/1.1 200 OK Server: TornadoServer/6.3.3 Content-Type: text/html; charset=UTF-8...

### Impact TokenController get parameter formName not sanitized in returned input field leads to XSS. _What kind of vulnerability is it? Who is impacted?_ ### Patches _Has the problem been patched? What versions should users upgrade to?_ ### Workarounds _Is there a way for users to fix or remediate the vulnerability without upgrading?_ Create a custom Symfony Request listener which checks for the get value of `form` for the TokenController and if not valid stop the request dispatching and return a error status code. ### References _Are there any links users can visit to find out more?_

An SQL Injection vulnerability exists in the berriai/litellm repository, specifically within the `/global/spend/logs` endpoint. The vulnerability arises due to improper neutralization of special elements used in an SQL command. The affected code constructs an SQL query by concatenating an unvalidated `api_key` parameter directly into the query, making it susceptible to SQL Injection if the `api_key` contains malicious data. This issue affects the latest version of the repository. Successful exploitation of this vulnerability could lead to unauthorized access, data manipulation, exposure of confidential information, and denial of service (DoS).

In h2oai/h2o-3 version 3.40.0.4, an exposure of sensitive information vulnerability exists due to an arbitrary system path lookup feature. This vulnerability allows any remote user to view full paths in the entire file system where h2o-3 is hosted. Specifically, the issue resides in the Typeahead API call, which when requested with a typeahead lookup of '/', exposes the root filesystem including directories such as /home, /usr, /bin, among others. This vulnerability could allow attackers to explore the entire filesystem, and when combined with a Local File Inclusion (LFI) vulnerability, could make exploitation of the server trivial.

BerriAI's litellm, in its latest version, is vulnerable to arbitrary file deletion due to improper input validation on the `/audio/transcriptions` endpoint. An attacker can exploit this vulnerability by sending a specially crafted request that includes a file path to the server, which then deletes the specified file without proper authorization or validation. This vulnerability is present in the code where `os.remove(file.filename)` is used to delete a file, allowing any user to delete critical files on the server such as SSH keys, SQLite databases, or configuration files.

man-group/dtale version 3.10.0 is vulnerable to an authentication bypass and remote code execution (RCE) due to improper input validation. The vulnerability arises from a hardcoded `SECRET_KEY` in the flask configuration, allowing attackers to forge a session cookie if authentication is enabled. Additionally, the application fails to properly restrict custom filter queries, enabling attackers to execute arbitrary code on the server by bypassing the restriction on the `/update-settings` endpoint, even when `enable_custom_filters` is not enabled. This vulnerability allows attackers to bypass authentication mechanisms and execute remote code on the server.

A blind SQL injection vulnerability exists in the berriai/litellm application, specifically within the '/team/update' process. The vulnerability arises due to the improper handling of the 'user_id' parameter in the raw SQL query used for deleting users. An attacker can exploit this vulnerability by injecting malicious SQL commands through the 'user_id' parameter, leading to potential unauthorized access to sensitive information such as API keys, user information, and tokens stored in the database. The affected version is 1.27.14.

A race condition vulnerability exists in zenml-io/zenml versions up to and including 0.55.3, which allows for the creation of multiple users with the same username when requests are sent in parallel. This issue was fixed in version 0.55.5. The vulnerability arises due to insufficient handling of concurrent user creation requests, leading to data inconsistencies and potential authentication problems. Specifically, concurrent processes may overwrite or corrupt user data, complicating user identification and posing security risks. This issue is particularly concerning for APIs that rely on usernames as input parameters, such as PUT /api/v1/users/test_race, where it could lead to further complications.

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.

A Denial-of-Service (DoS) vulnerability exists in the `SitemapLoader` class of the `langchain-ai/langchain` repository, affecting all versions. The `parse_sitemap` method, responsible for parsing sitemaps and extracting URLs, lacks a mechanism to prevent infinite recursion when a sitemap URL refers to the current sitemap itself. This oversight allows for the possibility of an infinite loop, leading to a crash by exceeding the maximum recursion depth in Python. This vulnerability can be exploited to occupy server socket/port resources and crash the Python process, impacting the availability of services relying on this functionality.