Aggregating NVD, CVE, and multi-source threat feeds, this list provides deep analysis of high-risk threats such as RCE. By integrating CVSS and EPSS models, the system dynamically tracks Exp (Exploit) resources and PoC availability to accurately assess Exploitability. Combined with official Patches and remediation strategies, it helps prioritize Vulnerability Management workflows, significantly shortening response cycles and securing your critical assets.
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| CVE | Description | Max CVSS | EPSS % | Published | Updated |
|---|---|---|---|---|---|
| CVE-2026-11816 | Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary become | 8.1 | N/A | 2026-06-11 | 2026-06-11 |
| CVE-2026-5497 | vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded frame count processing in the `VideoMediaIO.load_base64()` method. When processing `video/jpeg` data URLs, the method splits the base64 data string on commas to extract individual JPEG frames without enforcing a frame count limit. An attacker can exploit this by crafting a single API request containing thousands of comma-separated base64-encoded JPEG frames in a data URL, causin | 7.5 | 0.08% | 2026-06-11 | 2026-06-11 |
| CVE-2026-6657 | A vulnerability in jupyter-server versions 1.12.0 through 2.17.0 allows an attacker to bypass CORS origin validation when the `allow_origin_pat` configuration is used. The issue arises from the use of `re.match()` for validating the `Origin` header, which only anchors at the start of the string. This allows attacker-controlled domains such as `trusted.example.com.evil.com` to pass validation against patterns intended to match `trusted.example.com`. The vulnerability affects multiple locations in | 6.1 | 0.02% | 2026-06-03 | 2026-06-04 |
| CVE-2026-5241 | A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `Lig | 9.6 | 0.07% | 2026-06-03 | 2026-06-04 |
| CVE-2026-4035 | A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to th | 7.7 | 0.09% | 2026-06-03 | 2026-06-04 |
| CVE-2026-5422 | A path traversal vulnerability exists in jupyter-server version 2.17.0 due to an incorrect root directory boundary check in the _get_os_path() function within jupyter_server/services/contents/fileio.py. The check uses startswith(root) without appending a trailing path separator, allowing sibling directories with names starting with the same prefix as root_dir to bypass the check. Additionally, the to_os_path() function in utils.py does not strip ".." from path parts, enabling traversal sequences | 8.1 | 0.05% | 2026-06-02 | 2026-06-03 |
| CVE-2026-3514 | In version 3.6.19 of prefecthq/prefect, an authentication bypass vulnerability exists due to the improper handling of URL path exemptions for health check probes. Specifically, the authentication middleware exempts any URL path ending with 'health' or 'ready' from authentication checks. This allows an attacker to create resources with names ending in 'health' or 'ready' and access them without authentication. Affected endpoints include those for variables, flows, work pools, work queues, and dep | 7.5 | 0.08% | 2026-06-02 | 2026-06-03 |
| CVE-2026-3198 | MLflow 3.9.0 with basic-auth (`--app-name basic-auth`) fails to enforce authorization checks for multiple Gateway API 'list' endpoints. Specifically, the `BEFORE_REQUEST_HANDLERS` dictionary in `mlflow/server/auth/__init__.py` does not include entries for `ListGatewaySecretInfos`, `ListGatewayEndpoints`, and `ListGatewayModelDefinitions`. This allows any authenticated user, regardless of their assigned permissions, to enumerate all gateway secrets, endpoints, and model definitions. This vulnerab | 6.5 | 0.03% | 2026-06-02 | 2026-06-03 |
| CVE-2026-4944 | vllm-project/vllm version 0.14.1 contains a vulnerability where the `trust_remote_code=True` parameter is hardcoded in two model implementation files (`vllm/model_executor/models/nemotron_vl.py` and `vllm/model_executor/models/kimi_k25.py`). This bypasses the user's explicit `--trust-remote-code=False` setting, enabling remote code execution via malicious HuggingFace model repositories. This issue is an incomplete fix for CVE-2025-66448 and CVE-2026-22807, as it affects separate code paths in mo | 8.8 | 0.09% | 2026-05-28 | 2026-05-29 |
| CVE-2026-2651 | A vulnerability in MLflow versions <=3.10.1.dev0 allows unauthorized access to multipart upload (MPU) endpoints when the `--serve-artifacts` mode is enabled. The authorization logic does not enforce resource-level permission checks for `/mlflow-artifacts/mpu/*` endpoints, enabling attackers to overwrite artifacts belonging to other users. This can lead to unauthorized cross-user writes, model supply chain poisoning, and arbitrary code execution when compromised models are loaded. The issue is re | 9.0 | 0.05% | 2026-05-25 | 2026-06-04 |
| CVE-2026-4372 | A critical remote code execution vulnerability exists in all versions of the HuggingFace transformers library prior to version 5.3.0. The vulnerability allows an attacker to craft a malicious `config.json` file containing the `_attn_implementation_internal` field set to an attacker-controlled HuggingFace Hub repository ID. When a victim loads this model using the standard `AutoModelForCausalLM.from_pretrained()` API, the library downloads and executes arbitrary Python code from the attacker's re | 7.8 | 0.09% | 2026-05-24 | 2026-06-04 |
| CVE-2026-3515 | A vulnerability in the `GitHubRepository` block of the `prefect-github` integration in Prefect version 3.6.18 allows an attacker to inject arbitrary git command-line options via the `reference` field. The `reference` field is concatenated directly into a `git clone` command string without proper sanitization, and then parsed by `shlex.split()`. This enables injection of options such as `-c`, leading to potential Server-Side Request Forgery (SSRF), credential theft, or remote code execution (RCE) | 8.5 | 0.10% | 2026-05-24 | 2026-05-26 |
| CVE-2026-2734 | In mlflow/mlflow versions up to 3.9.0, the `SearchModelVersions` REST API endpoint and the `mlflowSearchModelVersions` GraphQL query lack proper per-model authorization checks when basic authentication is enabled. This allows any authenticated user to enumerate all model versions across all registered models, regardless of their permission level. The issue arises due to the absence of `SearchModelVersions` in the `BEFORE_REQUEST_VALIDATORS` and `AFTER_REQUEST_HANDLERS` for the REST API, and its | 6.5 | 0.03% | 2026-05-21 | 2026-06-02 |
| CVE-2026-2611 | In MLflow version 3.9.0, the MLflow Assistant feature introduced improper origin validation in its /ajax-api endpoints. This vulnerability allows a remote attacker to exploit cross-origin requests from a malicious webpage to interact with the MLflow Assistant running on a victim's local machine. By bypassing the loopback-only restriction, the attacker can modify the Assistant's configuration to enable full access, which in turn allows the execution of arbitrary commands via the Claude Code sub-a | 9.6 | 0.03% | 2026-05-19 | 2026-05-19 |
| CVE-2026-4137 | In mlflow/mlflow versions prior to 3.11.0, the `get_or_create_nfs_tmp_dir()` function in `mlflow/utils/file_utils.py` creates temporary directories with world-writable permissions (0o777), and the `_create_model_downloading_tmp_dir()` function in `mlflow/pyfunc/__init__.py` creates directories with group-writable permissions (0o770). These insecure permissions allow local attackers to tamper with model artifacts, such as cloudpickle-serialized Python objects, and achieve arbitrary code execution | 7.8 | 0.01% | 2026-05-18 | 2026-06-02 |
| CVE-2026-2652 | A vulnerability in mlflow/mlflow versions 3.9.0 and earlier allows unauthenticated access to certain FastAPI routes when the server is started with authentication enabled (`--app-name basic-auth`) and served via uvicorn (ASGI). The FastAPI permission middleware only enforces authentication on `/gateway/` routes, leaving other routes such as the Job API (`/ajax-api/3.0/jobs/*`) and the OpenTelemetry trace ingestion API (`/v1/traces`) unprotected. This allows unauthenticated remote attackers to su | 8.6 | 1.32% | 2026-05-15 | 2026-05-18 |
| CVE-2026-2614 | A vulnerability in the `_create_model_version()` handler of `mlflow/server/handlers.py` in mlflow/mlflow versions 3.9.0 and earlier allows an unauthenticated remote attacker to read arbitrary files from the server's filesystem. The issue arises when a `CreateModelVersion` request includes the tag `mlflow.prompt.is_prompt`, which bypasses source path validation. This enables an attacker to store an arbitrary local filesystem path as the model version source. The `get_model_version_artifact_handle | 7.5 | 0.05% | 2026-05-11 | 2026-05-27 |
| CVE-2026-2393 | A Server-Side Request Forgery (SSRF) vulnerability exists in MLflow versions prior to 3.9.0. The `_create_webhook()` function in `mlflow/server/handlers.py` accepts a user-controlled `url` parameter without validation, and the `_send_webhook_request()` function in `mlflow/webhooks/delivery.py` sends HTTP POST requests to this attacker-controlled URL. This allows an authenticated attacker to force the MLflow backend to send HTTP requests to internal services, cloud metadata endpoints, or arbitrar | 7.1 | 0.03% | 2026-05-11 | 2026-05-27 |
| CVE-2026-3960 | A critical remote code execution vulnerability exists in the unauthenticated REST API endpoint /99/ImportSQLTable in H2O-3 version 3.46.0.9 and prior. The vulnerability arises due to insufficient security controls in the parameter blacklist mechanism, which only targets MySQL JDBC driver-specific dangerous parameters. An attacker can bypass these controls by switching the JDBC URL protocol to jdbc:postgresql: and exploiting PostgreSQL JDBC driver-specific parameters such as socketFactory and soc | 9.8 | 0.35% | 2026-04-23 | 2026-05-19 |
| CVE-2026-1462 | A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file path | 8.8 | 0.06% | 2026-04-13 | 2026-04-17 |