| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Retrieval-based-Voice-Conversion-WebUI is a voice changing framework based on VITS. Versions 2.2.231006 and prior are vulnerable to unsafe deserialization. The ckpt_path2 variable takes user input (e.g. a path to a model) and passes it to the extract_small_model function in process_ckpt.py, which uses it to load the model on that path with torch.load, which can lead to unsafe deserialization and remote code execution. As of time of publication, no known patches exist. |
| Retrieval-based-Voice-Conversion-WebUI is a voice changing framework based on VITS. Versions 2.2.231006 and prior are vulnerable to unsafe deserialization. The ckpt_path0 variable takes user input (e.g. a path to a model) and passes it to the change_info function in process_ckpt.py, which uses it to load the model on that path with torch.load, which can lead to unsafe deserialization and remote code execution. As of time of publication, no known patches exist. |
| Retrieval-based-Voice-Conversion-WebUI is a voice changing framework based on VITS. Versions 2.2.231006 and prior are vulnerable to unsafe deserialization. The ckpt_a and cpkt_b variables take user input (e.g. a path to a model) and pass it to the merge function in process_ckpt.py, which uses them to load the models on those paths with torch.load, which can lead to unsafe deserialization and remote code execution. As of time of publication, no known patches exist. |
| Retrieval-based-Voice-Conversion-WebUI is a voice changing framework based on VITS. Versions 2.2.231006 and prior are vulnerable to unsafe deserialization. The ckpt_dir variable takes user input (e.g. a path to a model) and passes it to the change_info function in export.py, which uses it to load the model on that path with torch.load, which can lead to unsafe deserialization and remote code execution. As of time of publication, no known patches exist. |
| Retrieval-based-Voice-Conversion-WebUI is a voice changing framework based on VITS. Versions 2.2.231006 and prior are vulnerable to unsafe deserialization. The model_choose variable takes user input (e.g. a path to a model) and passes it to the uvr function in vr.py. In uvr , a new instance of AudioPre class is created with the model_path attribute containing the aformentioned user input. In the AudioPre class, the user input, is used to load the model on that path with torch.load, which can lead to unsafe deserialization and remote code execution. As of time of publication, no known patches exist. |
| Retrieval-based-Voice-Conversion-WebUI is a voice changing framework based on VITS. Versions 2.2.231006 and prior are vulnerable to unsafe deserialization. The model_choose variable takes user input (e.g. a path to a model) and passes it to the uvr function in vr.py. In uvr , if model_name contains the string "DeEcho", a new instance of AudioPreDeEcho class is created with the model_path attribute containing the aforementioned user input. In the AudioPreDeEcho class, the user input is used to load the model on that path with torch.load, which can lead to unsafe deserialization and remote code execution. As of time of publication, no known patches exist. |
| Apollo Gateway provides utilities for combining multiple GraphQL microservices into a single GraphQL endpoint. Prior to 2.10.1, a vulnerability in Apollo Gateway allowed queries with deeply nested and reused named fragments to be prohibitively expensive to query plan, specifically during named fragment expansion. Named fragments were being expanded once per fragment spread during query planning, leading to exponential resource usage when deeply nested and reused fragments were involved. This could lead to excessive resource consumption and denial of service. This has been remediated in @apollo/gateway version 2.10.1. |
| Apollo Gateway provides utilities for combining multiple GraphQL microservices into a single GraphQL endpoint. Prior to 2.10.1, a vulnerability in Apollo Gateway allowed queries with deeply nested and reused named fragments to be prohibitively expensive to query plan, specifically due to internal optimizations being frequently bypassed. The query planner includes an optimization that significantly speeds up planning for applicable GraphQL selections. However, queries with deeply nested and reused named fragments can generate many selections where this optimization does not apply, leading to significantly longer planning times. Because the query planner does not enforce a timeout, a small number of such queries can render gateway inoperable. This could lead to excessive resource consumption and denial of service. This has been remediated in @apollo/gateway version 2.10.1. |
| Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to unsafe deserialization in model_information.py. `model_name` in model_information.py takes user-supplied input (e.g. a path to a model) and pass that value to the `run_model_information_script` and later to `model_information` function, which loads that model with `torch.load` in rvc/train/process/model_information.py (on line 16 in 3.2.8-bugfix), which is vulnerable to unsafe deserialization. The issue can lead to remote code execution. A patch is available in the `main` branch of the repository. |
| Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to unsafe deserialization in inference.py. `model_file` in inference.py as well as `model_file` in tts.py take user-supplied input (e.g. a path to a model) and pass that value to the `change_choices` and later to `get_speakers_id` function, which loads that model with `torch.load` in inference.py (line 326 in 3.2.8-bugfix), which is vulnerable to unsafe deserialization. The issue can lead to remote code execution. A patch is available on the `main` branch of the repository. |
| Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to arbitrary file write in inference.py. This issue may lead to writing arbitrary files on the Applio server. It can also be used in conjunction with an unsafe deserialization to achieve remote code execution. As of time of publication, no known patches are available. |
| Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to arbitrary file write in train.py. This issue may lead to writing arbitrary files on the Applio server. It can also be used in conjunction with an unsafe deserialization to achieve remote code execution. As of time of publication, no known patches are available. |
| Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to arbitrary file read in train.py's `export_pth` function. This issue may lead to reading arbitrary files on the Applio server. It can also be used in conjunction with blind server-side request forgery to read files from servers on the internal network that the Applio server has access to. As of time of publication, no known patches are available. |
| Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to arbitrary file read in train.py's `export_index` function. This issue may lead to reading arbitrary files on the Applio server. It can also be used in conjunction with blind server-side request forgery to read files from servers on the internal network that the Applio server has access to. As of time of publication, no known patches are available. |
| A vulnerability in confederation implementation for the Border Gateway Protocol (BGP) in Cisco IOS XR Software could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition.
This vulnerability is due to a memory corruption that occurs when a BGP update is created with an AS_CONFED_SEQUENCE attribute that has 255 autonomous system numbers (AS numbers). An attacker could exploit this vulnerability by sending a crafted BGP update message, or the network could be designed in such a manner that the AS_CONFED_SEQUENCE attribute grows to 255 AS numbers or more. A successful exploit could allow the attacker to cause memory corruption, which may cause the BGP process to restart, resulting in a DoS condition. To exploit this vulnerability, an attacker must control a BGP confederation speaker within the same autonomous system as the victim, or the network must be designed in such a manner that the AS_CONFED_SEQUENCE attribute grows to 255 AS numbers or more. |
| Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to arbitrary file removal in core.py. `output_tts_path` in tts.py takes arbitrary user input and passes it to `run_tts_script` function in core.py, which checks if the path in `output_tts_path` exists, and if yes, removes that path, which leads to arbitrary file removal. As of time of publication, no known patches are available. |
| A vulnerability in the Internet Key Exchange version 2 (IKEv2) protocol processing of Cisco Adaptive Security Appliance (ASA) Software, Cisco Firepower Threat Defense (FTD) Software, Cisco IOS Software, and Cisco IOS XE Software could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition on an affected device.
This vulnerability is due to insufficient input validation when processing IKEv2 messages. An attacker could exploit this vulnerability by sending crafted IKEv2 traffic to an affected device. A successful exploit could allow the attacker to cause the device to reload, resulting in a DoS condition on the affected device. |
| A vulnerability in the Simple Network Management Protocol (SNMP) feature of Cisco Adaptive Security Appliance (ASA) Software and Cisco Firepower Threat Defense (FTD) Software could allow an authenticated, remote attacker to cause an unexpected reload of the device.
This vulnerability is due to insufficient input validation of SNMP packets. An attacker could exploit this vulnerability by sending a crafted SNMP request to an affected device using IPv4 or IPv6. A successful exploit could allow the attacker to cause the affected device to reload, resulting in a denial of service (DoS) condition. This vulnerability affects all versions of SNMP (versions 1, 2c, and 3) and requires a valid SNMP community string or valid SNMPv3 user credentials. |
| A vulnerability in the AnyConnect firewall for Cisco Adaptive Security Appliance (ASA) Software and Cisco Firepower Threat Defense (FTD) Software could allow an unauthenticated, remote attacker to bypass a configured access control list (ACL) and allow traffic that should have been denied to flow through an affected device. This vulnerability is due to a logic error in populating group ACLs when an AnyConnect client establishes a new session toward an affected device. An attacker could exploit this vulnerability by establishing an AnyConnect connection to the affected device. A successful exploit could allow the attacker to bypass configured ACL rules. |
| A vulnerability in the AnyConnect firewall for Cisco Adaptive Security Appliance (ASA) Software and Cisco Firepower Threat Defense (FTD) Software could allow an unauthenticated, remote attacker to bypass a configured access control list (ACL) and allow traffic that should have been denied to flow through an affected device. This vulnerability is due to a logic error in populating group ACLs when an AnyConnect client establishes a new session toward an affected device. An attacker could exploit this vulnerability by establishing an AnyConnect connection to the affected device. A successful exploit could allow the attacker to bypass configured ACL rules. |
