| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| A vulnerability was identified in Oinone Pamirs up to 7.2.0. This affects the function JsonUtils.parseMap of the file PamirsParserConfig.java of the component appConfigQuery Interface. Such manipulation leads to deserialization. The attack can be launched remotely. The exploit is publicly available and might be used. The vendor was contacted early about this disclosure but did not respond in any way. |
| GitLab has remediated an issue in GitLab EE affecting all versions from 11.9 before 18.9.7, 18.10 before 18.10.6, and 18.11 before 18.11.3 that could have allowed an unauthenticated user to cause denial of service by uploading a specially crafted file due to improper validation. |
| DataHub is an open-source metadata platform. Prior to 1.5.0.3, The DataHub frontend (datahub-frontend-react) deserializes attacker-controlled Java objects from the REDIRECT_URL HTTP cookie during the OIDC callback flow, with no integrity protection (no HMAC, no encryption). This is a Deserialization of Untrusted Data vulnerability (CWE-502) affecting the GET /callback/oidc endpoint. Successful exploitation requires a valid user account in the configured OIDC identity provider This vulnerability is fixed in 1.5.0.3. |
| Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. From version 4.0.0 to before version 4.0.5, the workflow executor logs all artifact repository credentials (S3 access keys, secret keys, GCS service account keys, Azure account keys, Git passwords, etc.) in plaintext on artifact operation. Any user with read access to workflow pod logs can extract these credentials. This issue has been patched in version 4.0.5. |
| PyTorch-Lightning versions 2.6.0 and earlier contain an insecure deserialization vulnerability (CWE-502) in the checkpoint loading mechanism. The LightningModule.load_from_checkpoint() method, which is commonly used to load saved model states, internally calls torch.load() without setting 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 checkpoint file, leading to arbitrary code execution on the victim's system when the file is loaded. |
| PyTorch Lightning is a deep learning framework to pretrain and finetune AI models. Versions 2.6.2 and 2.6.2 have introduced functionality consistent with a credential harvesting mechanism. |
| 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. |
| A supply chain attack compromised the official installation packages of DAEMON Tools Lite (Windows versions 12.5.0.2421 through 12.5.0.2434), distributed from the legitimate website daemon-tools.cc between approximately April 8, 2026, and May 5, 2026. Attackers gained unauthorized access to the vendor's (AVB Disc Soft) build or distribution infrastructure and trojanized three binaries: DTHelper.exe, DiscSoftBusServiceLite.exe, and DTShellHlp.exe. These files were digitally signed with the legitimate AVB Disc Soft code-signing certificate, allowing the malicious installers to appear trustworthy and bypass signature-based detection. |
| Vasion Print (formerly PrinterLogic) Virtual Appliance Host versions prior to 22.0.843 and Application prior to 20.0.1923 (VA and SaaS deployments) contains dangerous PHP dead code present in multiple Docker-hosted PHP instances. A script named /var/www/app/resetroot.php (found in several containers) lacks authentication checks and, when executed, performs a SQL update that sets the database administrator username to 'root' and its password hash to the SHA-512 hash of the string 'password'. Separately, commented-out code in /var/www/app/lib/common/oses.php would unserialize session data (unserialize($_SESSION['osdata']))—a pattern that can enable remote code execution if re-enabled or reached with attacker-controlled serialized data. An attacker able to reach the resetroot.php endpoint can trivially reset the MySQL root password and obtain full database control; combined with deserialization issues this can lead to full remote code execution and system compromise. This vulnerability has been identified by the vendor as: V-2023-003 — Dead / Insecure PHP Code. |
| Vasion Print (formerly PrinterLogic) Virtual Appliance Host versions prior to 22.0.843 and Application prior to 20.0.1923 (macOS/Linux client deployments) contain an arbitrary file write vulnerability via the response file handling. When tasks produce output the service writes response data into files under /opt/PrinterInstallerClient/tmp/responses/ reusing the requested filename. The service follows symbolic links in the responses directory and writes as the service user (typically root), allowing a local, unprivileged user to cause the service to overwrite or create arbitrary files on the filesystem as root. This can be used to modify configuration files, replace or inject binaries or drivers, and otherwise achieve local privilege escalation and full system compromise. This vulnerability has been identified by the vendor as: V-2023-019 — Arbitrary File Write as Root. |
| The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework 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. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. |
| The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization (CWE-502) when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method uses torch.load() to load the pytorch_model.bin weight file 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 publishing a malicious model repository on HuggingFace Hub. When a victim loads a model from this repository, arbitrary code is executed on the victim's system in the context of the mamba process. |
| 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. |
| 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 imgaug library thru 0.4.0 contains an insecure deserialization vulnerability in its BackgroundAugmenter class within the multicore.py module. The class uses Python's pickle module to deserialize data received via a multiprocessing queue in the _augment_images_worker() method without any safety checks. An attacker who can influence the data placed into this queue (e.g., through social engineering, malicious input scripts, or a compromised shared queue) can provide a malicious pickle payload. When deserialized, this payload can execute arbitrary code in the context of the worker process, leading to remote or local code execution depending on the deployment scenario. |
| The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. |
| HCL AION is affected by a vulnerability where basic authorization tokens are used for authentication. Use of basic authorization mechanisms may expose credentials to potential interception or misuse, especially if not combined with secure transmission practices. |
| 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. |
| HCL AION is affected by a vulnerability where sensitive information may be included in URL parameters. Passing sensitive data in URLs may expose it through browser history, logs, or intermediary systems, potentially leading to unintended information disclosure under certain conditions. |
| 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. |
