Vulnerabilities (CVE)

Filtered by CWE-502
Total 2015 CVE
CVE Vendors Products Updated CVSS v2 CVSS v3
CVE-2025-50472 2025-08-04 N/A 9.8 CRITICAL
The modelscope/ms-swift library thru 2.6.1 is vulnerable to arbitrary code execution through deserialization of untrusted data within the `load_model_meta()` function of the `ModelFileSystemCache()` class. Attackers can execute arbitrary code and commands by crafting a malicious serialized `.mdl` payload, exploiting the use of `pickle.load()` on data from potentially untrusted sources. This vulnerability allows for remote code execution (RCE) by deceiving victims into loading a seemingly harmless checkpoint during a normal training process, thereby enabling attackers to execute arbitrary code on the targeted machine. Note that the payload file is a hidden file, making it difficult for the victim to detect tampering. More importantly, during the model training process, after the `.mdl` file is loaded and executes arbitrary code, the normal training process remains unaffected'meaning the user remains unaware of the arbitrary code execution.
CVE-2025-50460 2025-08-04 N/A 9.8 CRITICAL
A remote code execution (RCE) vulnerability exists in the ms-swift project version 3.3.0 due to unsafe deserialization in tests/run.py using yaml.load() from the PyYAML library (versions = 5.3.1). If an attacker can control the content of the YAML configuration file passed to the --run_config parameter, arbitrary code can be executed during deserialization. This can lead to full system compromise. The vulnerability is triggered when a malicious YAML file is loaded, allowing the execution of arbitrary Python commands such as os.system(). It is recommended to upgrade PyYAML to version 5.4 or higher, and to use yaml.safe_load() to mitigate the issue.
CVE-2024-10382 1 Google 1 Androidx.car.app 2025-08-04 N/A 7.5 HIGH
There exists a code execution vulnerability in the Car App Android Jetpack Library. CarAppService uses deserialization logic that allows construction of arbitrary java classes. This can lead to arbitrary code execution when combined with specific Java deserialization gadgets. An attacker needs to install a malicious application on victims device to be able to attack any application that uses vulnerable library. We recommend upgrading the library past version 1.7.0-beta02.
CVE-2025-7504 1 Alex.kirk 1 Friends 2025-08-02 N/A 7.5 HIGH
The Friends plugin for WordPress is vulnerable to PHP Object Injection in version 3.5.1 via deserialization of untrusted input of the query_vars parameter This makes it possible for authenticated attackers, with subscriber-level access and above, to inject a PHP Object. No known POP chain is present in the vulnerable software, which means this vulnerability has no impact unless another plugin or theme containing a POP chain is installed on the site. If a POP chain is present via an additional plugin or theme installed on the target system, it may allow the attacker to perform actions like delete arbitrary files, retrieve sensitive data, or execute code depending on the POP chain present. This requires access to the sites SALT_NONCE and and SALT_KEY to exploit.
CVE-2025-43846 1 Rvc-project 1 Retrieval-based-voice-conversion-webui 2025-08-01 N/A 9.8 CRITICAL
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_path1 variable takes user input (e.g. a path to a model) and passes it to the show_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.
CVE-2025-43847 1 Rvc-project 1 Retrieval-based-voice-conversion-webui 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-43848 1 Rvc-project 1 Retrieval-based-voice-conversion-webui 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-43849 1 Rvc-project 1 Retrieval-based-voice-conversion-webui 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-43850 1 Rvc-project 1 Retrieval-based-voice-conversion-webui 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-43851 1 Rvc-project 1 Retrieval-based-voice-conversion-webui 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-43852 1 Rvc-project 1 Retrieval-based-voice-conversion-webui 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-27780 1 Applio 1 Applio 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-27781 1 Applio 1 Applio 2025-08-01 N/A 9.8 CRITICAL
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.
CVE-2025-27778 1 Applio 1 Applio 2025-08-01 N/A 9.8 CRITICAL
Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to unsafe deserialization in `infer.py`. The issue can lead to remote code execution. As of time of publication, a fix is available on the `main` branch of the Applio repository but not attached to a numbered release.
CVE-2025-27779 1 Applio 1 Applio 2025-08-01 N/A 9.8 CRITICAL
Applio is a voice conversion tool. Versions 3.2.8-bugfix and prior are vulnerable to unsafe deserialization in `model_blender.py` lines 20 and 21. `model_fusion_a` and `model_fusion_b` from voice_blender.py take user-supplied input (e.g. a path to a model) and pass that value to the `run_model_blender_script` and later to `model_blender` function, which loads these two models with `torch.load` in `model_blender.py (on lines 20-21 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 Applio repository.
CVE-2025-30165 1 Vllm 1 Vllm 2025-07-31 N/A 8.0 HIGH
vLLM is an inference and serving engine for large language models. In a multi-node vLLM deployment using the V0 engine, vLLM uses ZeroMQ for some multi-node communication purposes. The secondary vLLM hosts open a `SUB` ZeroMQ socket and connect to an `XPUB` socket on the primary vLLM host. When data is received on this `SUB` socket, it is deserialized with `pickle`. This is unsafe, as it can be abused to execute code on a remote machine. Since the vulnerability exists in a client that connects to the primary vLLM host, this vulnerability serves as an escalation point. If the primary vLLM host is compromised, this vulnerability could be used to compromise the rest of the hosts in the vLLM deployment. Attackers could also use other means to exploit the vulnerability without requiring access to the primary vLLM host. One example would be the use of ARP cache poisoning to redirect traffic to a malicious endpoint used to deliver a payload with arbitrary code to execute on the target machine. Note that this issue only affects the V0 engine, which has been off by default since v0.8.0. Further, the issue only applies to a deployment using tensor parallelism across multiple hosts, which we do not expect to be a common deployment pattern. Since V0 is has been off by default since v0.8.0 and the fix is fairly invasive, the maintainers of vLLM have decided not to fix this issue. Instead, the maintainers recommend that users ensure their environment is on a secure network in case this pattern is in use. The V1 engine is not affected by this issue.
CVE-2024-11041 1 Vllm 1 Vllm 2025-07-31 N/A 9.8 CRITICAL
vllm-project vllm version v0.6.2 contains a vulnerability in the MessageQueue.dequeue() API function. The function uses pickle.loads to parse received sockets directly, leading to a remote code execution vulnerability. An attacker can exploit this by sending a malicious payload to the MessageQueue, causing the victim's machine to execute arbitrary code.
CVE-2025-49841 1 Rvc-boss 1 Gpt-sovits-webui 2025-07-30 N/A 9.8 CRITICAL
GPT-SoVITS-WebUI is a voice conversion and text-to-speech webUI. In versions 20250228v3 and prior, there is an unsafe deserialization vulnerability in process_ckpt.py. The SoVITS_dropdown variable takes user input and passes it to the load_sovits_new function in process_ckpt.py. In load_sovits_new, the user input, here sovits_path is used to load a model with torch.load, leading to unsafe deserialization. At time of publication, no known patched versions are available.
CVE-2025-49840 1 Rvc-boss 1 Gpt-sovits-webui 2025-07-30 N/A 9.8 CRITICAL
GPT-SoVITS-WebUI is a voice conversion and text-to-speech webUI. In versions 20250228v3 and prior, there is an unsafe deserialization vulnerability in inference_webui.py. The GPT_dropdown variable takes user input and passes it to the change_gpt_weights function. In change_gpt_weights, the user input, here gpt_path is used to load a model with torch.load, leading to unsafe deserialization. At time of publication, no known patched versions are available.
CVE-2025-49838 1 Rvc-boss 1 Gpt-sovits-webui 2025-07-30 N/A 9.8 CRITICAL
GPT-SoVITS-WebUI is a voice conversion and text-to-speech webUI. In versions 20250228v3 and prior, there is an unsafe deserialization vulnerability in vr.py AudioPreDeEcho. The model_choose variable takes user input (e.g. a path to a model) and passes it to the uvr function. In uvr, a new instance of AudioPreDeEcho class is created with the model_path attribute containing the aforementioned user input (here called locally model_name). Note that in this step the .pth extension is added to the path. In the AudioPreDeEcho class, the user input, here called model_path, is used to load the model on that path with torch.load, which can lead to unsafe deserialization. At time of publication, no known patched versions are available.