Base de CVEs

Deserialization of untrusted data vulnerability that may allow class-registration checks to be bypassed during Java lambda deserialization. Only lambda capture class is affected This issue affects Apache Fory: from before 1.4.0. Users are recommended to upgrade to version 1.4.0, which fixes the issue.

Heap type confusion and out-of-bounds read/write in the Apache Fory C++ implementation. When deserializing data in compatible mode, the field-skip paths do not correctly validate the declared field types against the actual data, so input with an inconsistent schema can cause type confusion and out-of-bounds memory access. Only the C++ implementation is affected; other language implementations of Apache Fory are not. This issue affects Apache Fory C++: from 0.14.0 before 1.4.0. Users are recommended to upgrade to version 1.4.0, which fixes the issue.

ktransformers through 0.6.3, fixed in commit def0f93, contains an unauthenticated pickle deserialization vulnerability that allows remote attackers to execute arbitrary commands by sending crafted pickle payloads to the SchedulerServer ZMQ ROUTER socket bound to all interfaces. Attackers can exploit malicious __reduce__ methods embedded in crafted pickle payloads to execute arbitrary shell commands as the server process.

Wazuh is a free and open source platform used for threat prevention, detection, and response. Prior to version 4.14.5, issues in the Cluster Distributed API (DAPI) handling allow a cluster peer, or any actor able to authenticate to the cluster channel using the shared cluster key, to make the master node deserialize an attacker-controlled callable and execute it under an attacker-controlled RBAC context. The cluster code in `framework/wazuh/core/cluster/common.py` deserializes JSON with `as_wazuh_object()`, which resolves any callable whose top-level package is wazuh or api (an overly broad allowlist controlled only by `ALLOWED_CALLABLES_PACKAGES`), and DAPI requests handled in framework/wazuh/core/cluster/dapi/dapi.py accept a client-supplied rbac_permissions value that `run_local()` applies as the global RBAC context, so supplying an rbac_mode of black causes authorization checks for expose_resources-protected functions to pass without any legitimate permission assignment. Combined, these allow privileged administrative actions on the master node such as arbitrary file writes under WAZUH_PATH, creation of new API users, and tampering with security.yaml, and can be chained into full manager compromise. This issue has been fixed in version 4.14.5.

IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the disk-based caching mechanism. The AsyncDiskCache class uses Python's unsafe pickle.loads() function to deserialize cached objects from disk without validation, integrity verification, or authentication, enabling arbitrary code execution when malicious pickle payloads are processed. Attackers who can influence cached data through file system access, malicious workflow inputs, custom components, or API manipulation can achieve complete system compromise with the privileges of the Langflow server process.

SGLang uses an expert-parallel backup subsystem that exposes a ZeroMQ PULL socket on a routable network interface that does not contain authentication or deserialization safeguards, allowing an attacker to provide a malicious pickle file that results in unauthenticated remote code execution when the feature is enabled and the service is reachable over the network.

NVIDIA TensorRT for contains a vulnerability where a user might cause a deserialization of untrusted data. A successful exploit of this vulnerability might lead to code execution.

Deserialization of untrusted data in Microsoft Dynamics NAV allows an unauthorized attacker to execute code over a network.

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

Deserialization of untrusted data in SQL Server allows an unauthorized attacker to execute code over a network.

Deserialization of untrusted data in SQL Server allows an unauthorized attacker to execute code over a network.