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.

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.

The file upload feature in OTRS and ((OTRS)) Community Edition has a path traversal vulnerability. This issue permits authenticated agents or customer users to upload potentially harmful files to directories accessible by the web server, potentially leading to the execution of local code like Perl scripts. This issue affects OTRS: from 7.0.X through 7.0.49, 8.0.X, 2023.X, from 2024.X through 2024.3.2; ((OTRS)) Community Edition: from 6.0.1 through 6.0.34.

IBM System Storage DS8900F 89.22.19.0, 89.30.68.0, 89.32.40.0, 89.33.48.0, 89.40.83.0, and 89.40.93.0 could allow a remote user to create an LDAP connection with a valid username and empty password to establish an anonymous connection.   IBM X-Force ID: 279518.

AutoGPT, a component of significant-gravitas/autogpt, is vulnerable to an improper neutralization of special elements used in an OS command ('OS Command Injection') due to a flaw in its shell command validation function. Specifically, the vulnerability exists in versions v0.5.0 up to but not including 5.1.0. The issue arises from the application's method of validating shell commands against an allowlist or denylist, where it only checks the first word of the command. This allows an attacker to bypass the intended restrictions by crafting commands that are executed despite not being on the allowlist or by including malicious commands not present in the denylist. Successful exploitation of this vulnerability could allow an attacker to execute arbitrary shell commands.

An OS command injection vulnerability exists in the MacOS Text-To-Speech class MacOSTTS of the significant-gravitas/autogpt project, affecting versions up to v0.5.0. The vulnerability arises from the improper neutralization of special elements used in an OS command within the `_speech` method of the MacOSTTS class. Specifically, the use of `os.system` to execute the `say` command with user-supplied text allows for arbitrary code execution if an attacker can inject shell commands. This issue is triggered when the AutoGPT instance is run with the `--speak` option enabled and configured with `TEXT_TO_SPEECH_PROVIDER=macos`, reflecting back a shell injection snippet. The impact of this vulnerability is the potential execution of arbitrary code on the instance running AutoGPT. The issue was addressed in version 5.1.0.

parisneo/lollms-webui is vulnerable to path traversal and denial of service attacks due to an exposed `/select_database` endpoint in version a9d16b0. The endpoint improperly handles file paths, allowing attackers to specify absolute paths when interacting with the `DiscussionsDB` instance. This flaw enables attackers to create directories anywhere on the system where the application has permissions, potentially leading to denial of service by creating directories with names of critical files, such as HTTPS certificate files, causing server startup failures. Additionally, attackers can manipulate the database path, resulting in the loss of client data by constantly changing the file location to an attacker-controlled location, scattering the data across the filesystem and making recovery difficult.

A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.http_dataset_source.py` module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the `Content-Disposition` header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0.

IBM Engineering Requirements Management DOORS Next 7.0.2 and 7.0.3 is vulnerable to an XML External Entity Injection (XXE) attack when processing XML data. A remote attacker could exploit this vulnerability to expose sensitive information or consume memory resources. IBM X-Force ID: 268758.

Luxion KeyShot BIP File Parsing Uncontrolled Search Path Element Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Luxion KeyShot. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of BIP files. The issue results from loading a library from an unsecured location. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-22738.

Luxion KeyShot Viewer KSP File Parsing Out-Of-Bounds Write Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Luxion KeyShot Viewer. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of KSP files. The issue results from the lack of proper validation of user-supplied data, which can result in a write past the end of an allocated buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-22267.

Luxion KeyShot Viewer KSP File Parsing Stack-based Buffer Overflow Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Luxion KeyShot Viewer. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of KSP files. The issue results from the lack of proper validation of the length of user-supplied data prior to copying it to a stack-based buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-22266.

Luxion KeyShot Viewer KSP File Parsing Out-Of-Bounds Write Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Luxion KeyShot Viewer. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of KSP files. The issue results from the lack of proper validation of user-supplied data, which can result in a write past the end of an allocated buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-22514.

NETGEAR ProSAFE Network Management System UpLoadServlet Directory Traversal Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of NETGEAR ProSAFE Network Management System. Authentication is required to exploit this vulnerability. The specific flaw exists within the UpLoadServlet class. The issue results from the lack of proper validation of a user-supplied path prior to using it in file operations. An attacker can leverage this vulnerability to execute code in the context of SYSTEM. Was ZDI-CAN-22724.

A Server-Side Request Forgery (SSRF) vulnerability exists in the 'add_webpage' endpoint of the parisneo/lollms-webui application, affecting the latest version. The vulnerability arises because the application does not adequately validate URLs entered by users, allowing them to input arbitrary URLs, including those that target internal resources such as 'localhost' or '127.0.0.1'. This flaw enables attackers to make unauthorized requests to internal or external systems, potentially leading to access to sensitive data, service disruption, network integrity compromise, business logic manipulation, and abuse of third-party resources. The issue is critical and requires immediate attention to maintain the application's security and integrity.

A remote code execution (RCE) vulnerability exists in the lightning-ai/pytorch-lightning library version 2.2.1 due to improper handling of deserialized user input and mismanagement of dunder attributes by the `deepdiff` library. The library uses `deepdiff.Delta` objects to modify application state based on frontend actions. However, it is possible to bypass the intended restrictions on modifying dunder attributes, allowing an attacker to construct a serialized delta that passes the deserializer whitelist and contains dunder attributes. When processed, this can be exploited to access other modules, classes, and instances, leading to arbitrary attribute write and total RCE on any self-hosted pytorch-lightning application in its default configuration, as the delta endpoint is enabled by default.

Kofax Power PDF PSD File Parsing Out-Of-Bounds Write Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Kofax Power PDF. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of PSD files. The issue results from the lack of proper validation of user-supplied data, which can result in a write past the end of an allocated buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-22919.

Kofax Power PDF PDF File Parsing Out-Of-Bounds Write Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Kofax Power PDF. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of PDF files. The issue results from the lack of proper validation of user-supplied data, which can result in a write past the end of an allocated buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-22918.

Kofax Power PDF PSD File Parsing Heap-based Buffer Overflow Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Kofax Power PDF. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of PSD files. The issue results from the lack of proper validation of the length of user-supplied data prior to copying it to a fixed-length heap-based buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-22917.

In lunary-ai/lunary version 1.2.4, a vulnerability exists in the password recovery mechanism where the reset password token is not invalidated after use. This allows an attacker who compromises the recovery token to repeatedly change the password of a victim's account. The issue lies in the backend's handling of the reset password process, where the token, once used, is not discarded or invalidated, enabling its reuse. This vulnerability could lead to unauthorized account access if an attacker obtains the recovery token.