CWE-502

QOS.ch Logback before 1.2.0 has a serialization vulnerability affecting the SocketServer and ServerSocketReceiver components.

An authenticated remote code execution vulnerability through undisclosed vectors exists in the BIG-IP and BIG-IQ Configuration utility.  Note: Software versions which have reached End of Technical Support (EoTS) are not evaluated.

Deserialization of untrusted data in Microsoft Office SharePoint allows an authorized attacker to execute code over a network.

Deserialization of untrusted data in Microsoft Office SharePoint allows an authorized attacker to execute code over a network.

Deserialization of untrusted data in Microsoft Office SharePoint allows an authorized attacker to execute code over a network.

Deserialization of untrusted data in Microsoft Office SharePoint allows an authorized attacker to execute code over a network.

The CosyVoice project thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e (2025-30-21) contains an insecure deserialization vulnerability (CWE-502) in its model loading process. When loading model files (.pt) from a user-specified directory (via the --model_dir argument), the code uses torch.load() without the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the Pickle module. An attacker can exploit this by providing a maliciously crafted model directory containing .pt files with embedded pickle payloads. When a victim loads this directory using CosyVoice's web interface, the malicious payload is executed, leading to remote code execution on the victim's system.

The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the MultitaskClassifier.load() method of the MultitaskClassifier class. The method loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method.

The snorkel library thru v0.10.0 contains a critical insecure deserialization vulnerability (CWE-502) in the BaseLabeler.load() method of the BaseLabeler class. The method loads serialized labeler models using the unsafe pickle.load() function on user-supplied file paths without any validation or security controls. Python's pickle module is inherently dangerous for deserializing untrusted data, as it can execute arbitrary code during the deserialization process. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method.

The snorkel library thru v0.10.0 contains an insecure deserialization vulnerability (CWE-502) in the Trainer.load() method of the Trainer class. The method loads model checkpoint files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution on the victim's system when the file is loaded via the vulnerable method.

The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) is vulnerable to insecure deserialization (CWE-502). When a user provides a single model file path (e.g., .pt or .pth) via the --model command-line argument, the function loads the file using torch.load() without enabling the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects through the Pickle module. A remote attacker can exploit this by providing a maliciously crafted model file, leading to arbitrary code execution during deserialization on the victim's system.

The _load_model() function in the neural_magic_training.py script of the optimate project in commit a6d302f912b481c94370811af6b11402f51d377f (2024-07-21) is vulnerable to insecure deserialization (CWE-502). When loading a model state dictionary from a state_dict.pt file via torch.load(), the function does not enable the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects through the Pickle module. A remote attacker can exploit this by providing a maliciously crafted state_dict.pt file within a directory specified via the --model argument, leading to arbitrary code execution during the deserialization process on the victim's system.

The User Frontend: AI Powered Frontend Posting, User Directory, Profile, Membership & User Registration plugin for WordPress is vulnerable to Deserialization of Untrusted Data in versions up to, and including, 4.3.1 This is due to insufficient input validation and type checking on the wpuf_files parameter during form submission, combined with unconditional deserialization via maybe_unserialize() when displaying post content. This makes it possible for authenticated attackers, with Subscriber-level access and above, to inject arbitrary PHP objects, which can be leveraged to execute arbitrary code, delete arbitrary files, or perform other malicious actions if a POP chain is present on the target system.

NVIDIA FLARE SDK contains a vulnerability in FOBS, where an attacker may cause deserialization of untrusted data by sending a malicious FOBS- encoded message. A successful exploit of this vulnerability might lead to code execution.

DataEase is an open-source data visualization and analytics platform. Versions 2.10.20 and below ship the legacy velocity-1.7.jar, which pulls in commons-collections-3.2.1.jar containing the InvokerTransformer deserialization gadget chain. Quartz 2.3.2, also bundled in the application, deserializes job data BLOBs from the qrtz_job_details table using ObjectInputStream with no deserialization filter or class allowlist. An authenticated attacker who can write to the Quartz job table, such as through the previously described SQL injection in previewSql, can replace a scheduled job's JOB_DATA with a malicious CommonsCollections6 gadget chain payload. When the Quartz cron trigger fires, the payload is deserialized and executes arbitrary commands as root inside the container, achieving full remote code execution. This issue has been fixed in version 2.10.21.

Dag Authors, who normally should not be able to execute code in the webserver context could craft XCom payload causing the webserver to execute arbitrary code. Since Dag Authors are already highly trusted, severity of this issue is Low. Users are recommended to upgrade to Apache Airflow 3.2.0, which resolves this issue.

Deserialization of Untrusted Data vulnerability in Apache Storm. Versions Affected: before 2.8.6. Description: When processing topology credentials submitted via the Nimbus Thrift API, Storm deserializes the base64-encoded TGT blob using ObjectInputStream.readObject() without any class filtering or validation. An authenticated user with topology submission rights could supply a crafted serialized object in the "TGT" credential field, leading to remote code execution in both the Nimbus and Worker JVMs. Mitigation: 2.x users should upgrade to 2.8.6. Users who cannot upgrade immediately should monkey-patch an ObjectInputFilter allow-list to ClientAuthUtils.deserializeKerberosTicket() restricting deserialized classes to javax.security.auth.kerberos.KerberosTicket and its known dependencies. A guide on how to do this is available in the release notes of 2.8.6. Credit: This issue was discovered by K.

IBM Langflow Desktop 1.6.0 through 1.8.2 Langflow could allow an authenticated user to execute arbitrary code on the system, caused by an insecure default setting which permits the deserialization of untrusted data in the FAISS component.

Open Access Management (OpenAM) is an access management solution. Prior to 16.0.6, OpenIdentityPlatform OpenAM is vulnerable to pre-authentication Remote Code Execution (RCE) via unsafe Java deserialization of the jato.clientSession HTTP parameter. This bypasses the WhitelistObjectInputStream mitigation that was applied to the jato.pageSession parameter after CVE-2021-35464. An unauthenticated attacker can achieve arbitrary command execution on the server by sending a crafted serialized Java object as the jato.clientSession GET/POST parameter to any JATO ViewBean endpoint whose JSP contains <jato:form> tags (e.g., the Password Reset pages). This vulnerability is fixed in 16.0.6.

NVIDIA BioNeMo contains a vulnerability where a user could cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution, denial of service, information disclosure, and data tampering.