| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| sealed-env is a cross-stack, zero-trust secret management library for Node.js and Java/Spring Boot. In sealed-env enterprise mode, versions 0.1.0-alpha.1 through 0.1.0-alpha.3 embedded the operator's literal TOTP secret in the JWS payload of every minted unseal token. JWS payload is base64-encoded JSON, NOT encrypted. Any party who could observe a minted token (CI build logs, container env dumps, kubectl describe pod, Sentry/Rollbar stack traces, log aggregators) could decode the payload and extract the TOTP secret in plaintext. This vulnerability is fixed in 0.1.0-alpha.4. |
| JunoClaw is an agentic AI platform built on Juno Network. Prior to 0.x.y-security-1, the upload_wasm MCP tool accepted a filesystem path from the agent and uploaded whatever bytes the path resolved to, with no validation of location, symlink target, file size, or file format. This vulnerability is fixed in 0.x.y-security-1. |
| HashiCorp Nomad and Nomad Enterprise prior to 2.0.1 are vulnerable to arbitrary file read and write on the client host as the Nomad process user through a symlink attack. This vulnerability (CVE-2026-6959) is fixed in Nomad 2.0.1, 1.11.5 and 1.10.11. |
| The coreActivity: Activity Logging for WordPress plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 3.0. This is due to the plugin failing to validate or strip PHP serialization syntax from the User-Agent HTTP header before storing it in the logmeta table, and subsequently calling `maybe_unserialize()` on every retrieved `meta_value` in `query_metas()` without verifying the data was originally serialized by the application. This makes it possible for unauthenticated attackers to inject a crafted PHP serialized payload via the User-Agent header during any logged event (such as a failed login attempt), which, when an administrator views the Logs page, is deserialized and passed to `DeviceDetector::setUserAgent()`, triggering a Fatal TypeError that creates a persistent Denial of Service condition blocking administrator access to the Logs page entirely. |
| Files or directories accessible to external parties in Microsoft Teams allows an unauthorized attacker to perform spoofing locally. |
| HashiCorp Nomad’s exec2 task driver prior to 0.1.2 is vulnerable to arbitrary file read and write on the client host as the Nomad process user through a symlink attack. This vulnerability (CVE-2026-8052) is fixed in version 0.1.2 of the exec2 task driver. |
| CosyVoice thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e (2025-30-21) contains an insecure deserialization vulnerability (CWE-502) in its make_parquet_list.py data processing tool. The script loads PyTorch .pt files (utterance embeddings, speaker embeddings, speech tokens) using torch.load() without enabling the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing malicious .pt files within a data directory. When a victim processes this directory using the tool, arbitrary code is executed on the victim's system. |
| The flash-attention training framework thru commit e724e2588cbe754beb97cf7c011b5e7e34119e62 (2025-13-04) contains an insecure deserialization vulnerability (CWE-502) in its checkpoint loading mechanism. The load_checkpoint() function in checkpoint.py and the checkpoint loading code in eval.py use torch.load() without enabling 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 checkpoint file. When a victim loads this checkpoint during model warmstarting or evaluation, arbitrary code is executed on the victim's system. |
| CosyVoice thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e (2025-30-21) contains an insecure deserialization vulnerability (CWE-502) in its average_model.py model averaging tool. The script loads PyTorch checkpoint files (epoch_*.pt) for model averaging using torch.load() without enabling the weights_only=True security parameter. This allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing malicious checkpoint files within a directory. When a victim uses the tool to average models from this directory, arbitrary code is executed on the victim's system. |
| Wazuh version 4.12.0 contains an exposure vulnerability in GitHub Actions workflow artifacts that allows attackers to extract the GITHUB_TOKEN from uploaded artifacts. Attackers can use the exposed token within a limited time window to perform unauthorized actions such as pushing malicious commits or altering release tags. |
| Horovod thru 0.28.1 contains an insecure deserialization vulnerability (CWE-502) in its KVStore HTTP server component. The KVStore server, used for distributed task coordination, lacks authentication and authorization controls, allowing any remote attacker to write arbitrary data via HTTP PUT requests. When a Horovod worker reads data from the KVStore (via HTTP GET), it deserializes the data using cloudpickle.loads() without verifying its source or integrity. An attacker can exploit this by sending a malicious pickle payload to the server before the legitimate data is written, causing the victim worker to deserialize and execute arbitrary code, leading to remote code execution. |
| 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. |
| A path handling issue was addressed with improved logic. This issue is fixed in macOS Sequoia 15.7.7, macOS Sonoma 14.8.7, macOS Tahoe 26.5. An app may be able to observe unprotected user data. |
| A logging issue was addressed with improved data redaction. This issue is fixed in iOS 18.7.9 and iPadOS 18.7.9, iOS 26.5 and iPadOS 26.5, macOS Sequoia 15.7.7, macOS Sonoma 14.8.7, macOS Tahoe 26.5, tvOS 26.5, watchOS 26.5. An app may be able to leak sensitive kernel state. |
| DEPRECATED: Authentication Bypass Issues vulnerability in digest authentication in Apache Tomcat.
This issue affects Apache Tomcat: from 11.0.0-M1 through 11.0.21, from 10.1.0-M1 through 10.1.54, from 9.0.0.M1 through 9.0.117, from 8.5.0 through 8.5.100, from before 7.0.0.
Older unsupported versions any also be affect
Users are recommended to upgrade to version 11.0.22, 10.1.55 or 9.0.118 which fix the issue. |
| n8n-MCP is an MCP server that provides AI assistants access to n8n node documentation, properties, and operations. Prior to version 2.47.13, when n8n-mcp runs in HTTP transport mode, authenticated MCP tools/call requests had their full arguments and JSON-RPC params written to server logs by the request dispatcher and several sibling code paths before any redaction. When a tool call carries credential material — most notably n8n_manage_credentials.data — the raw values can be persisted in logs. In deployments where logs are collected, forwarded to external systems, or viewable outside the request trust boundary (shared log storage, SIEM pipelines, support/ops access), this can result in disclosure of: bearer tokens and OAuth credentials sent through n8n_manage_credentials, per-tenant API keys and webhook auth headers embedded in tool arguments, arbitrary secret-bearing payloads passed to any MCP tool. The issue requires authentication (AUTH_TOKEN accepted by the server), so unauthenticated callers cannot trigger it; the runtime exposure is also reduced by an existing console-silencing layer in HTTP mode, but that layer is fragile and the values are still constructed and passed into the logger. This issue has been patched in version 2.47.13. |
| 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. |
| A logging issue was addressed with improved data redaction. This issue is fixed in macOS Sequoia 15.7.7, macOS Sonoma 14.8.7, macOS Tahoe 26.5. A malicious app may be able to break out of its sandbox. |
| The consul-template library before version 0.42.0 is vulnerable to a sandbox path bypass in the file template helper that may allow reading an out-of-sandbox file. This vulnerability (CVE-2026-5061) is fixed in consul-template 0.42.0. |
| When enabling trace logging in Spring Cloud Config Server sensitive information was placed in plain text in the logs.
Spring Cloud Config 3.1.x: affected from 3.1.0 through 3.1.13 (inclusive); upgrade to 3.1.14 or greater (Enterprise Support Only). Spring Cloud Config 4.1.x: affected from 4.1.0 through 4.1.9 (inclusive); upgrade to 4.1.10 or greater (Enterprise Support Only). Spring Cloud Config 4.2.x: affected from 4.2.0 through 4.2.6 (inclusive); upgrade to 4.2.7 or greater (Enterprise Support Only). Spring Cloud Config 4.3.x: affected from 4.3.0 through 4.3.2 (inclusive); upgrade to 4.3.3 or greater. Spring Cloud Config 5.0.x: affected from 5.0.0 through 5.0.2 (inclusive); upgrade to 5.0.3 or greater. |
