#auth

After weeks of withering criticism and exposed security flaws, Microsoft has vastly scaled back its ambitions for Recall, its AI-enabled silent recording feature, and added new privacy features.

Online Pizza Ordering System version 1.0 suffers from a remote SQL injection vulnerability.

### Impact All users are impacted. The zsa application transfers the parse error stack from the server to the client in production build mode. This can potentially reveal sensitive information about the server environment, such as the machine username and directory paths. An attacker could exploit this vulnerability to gain unauthorized access to sensitive server information. This information could be used to plan further attacks or gain a deeper understanding of the server infrastructure. ### Patches Yes, this has been pathed on `0.3.3` ### Workarounds No way to fix other than the patch.

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).

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.

An improper authorization vulnerability exists in the zenml-io/zenml repository, specifically within the API PUT /api/v1/users/id endpoint. This vulnerability allows any authenticated user to modify the information of other users, including changing the `active` status of user accounts to false, effectively deactivating them. This issue affects version 0.55.3 and was fixed in version 0.56.2. The impact of this vulnerability is significant as it allows for the deactivation of admin accounts, potentially disrupting the functionality and security of the application.