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| CVE | CVSS | EPSS | Vendor, product | Description | Modified |
|---|---|---|---|---|---|
| CVE-2026-57845exploit | 8.7 high | 1.0% | no CPE yet | Hugging Face Datasets through 5.1.0 contains an insecure deserialization vulnerability that allows attackers to execute arbitrary Python code by crafting a malicious pickle file loaded through the deprecated pandas packaged builder. Attackers can supply a pickle-backed dataset that is processed by Pandas._generate_tables via pandas.read_pickle() without validation, so when a victim calls datasets.load_dataset("pandas", data_files=...), the embedded __reduce__ payload executes code with the victim process's privileges. | 23 Oct |
| CVE-2026-9335exploit | 6.5 medium | 1.0% | no CPE yet | A vulnerability in keras-team/keras versions <= 3.14.0 allows arbitrary local HDF5 file content disclosure due to improper handling of HDF5 ExternalLinks. The `KerasFileEditor` and `keras.saving.load_weights` functions bypass the `safe_get_h5_group` and `safe_get_h5_dataset` helpers, which are designed to reject ExternalLinks and SoftLinks. This results in automatic dereferencing of links to external HDF5 files, enabling attackers to disclose sensitive data from the victim's local filesystem. Specifically, `KerasFileEditor` extracts attributes and datasets from linked files into its internal structures, while `keras.saving.load_weights` loads weights from linked files into the user's model. This issue can be exploited by providing a malicious `.h5`, `.weights.h5`, or `.keras` file containing ExternalLinks. | 23 Oct |
| CVE-2026-35492exploit | 6.5 medium | 0.00% | no CPE yet | Kedro-Datasets is a Kendo plugin providing data connectors. Prior to 9.3.0, PartitionedDataset in kedro-datasets was vulnerable to path traversal. Partition IDs were concatenated directly with the dataset base path without validation. An attacker or malicious input containing .. components in a partition ID could cause files to be written outside the configured dataset directory, potentially overwriting arbitrary files on the filesystem. Users of PartitionedDataset with any storage backend (local filesystem, S3, GCS, etc.) are affected. This vulnerability is fixed in 9.3.0. | Mon 26 Oct |
| CVE-2026-73487 | 9.0 critical | 1.0% | flowiseai, flowise | Flowise before 3.1.3 contains a regex-based Python code validator bypass in CSV and Airtable Agent nodes that allows unauthenticated attackers to inject malicious code via prompt injection. Attackers can exploit unblocked pandas functions like pd.read_json() to exfiltrate datasets, perform SSRF against internal services, or achieve code execution through the unauthenticated prediction API. | Sat 24 Oct |
| CVE-2026-56445 | 8.8 high | 1.0% | no CPE yet | The qrscp application's C-STORE handler uses a specific instance from attacker-supplied DICOM datasets directly in os.path.join() without sanitization, allowing file writes to arbitrary paths. | Sun 25 Oct |
| CVE-2026-75111 | 8.7 high | 1.0% | no CPE yet | Evidently UI fails to properly validate the filename parameter in the dataset materialization endpoint, allowing unauthenticated attackers to read arbitrary files outside the workspace directory. Attackers can supply traversal sequences or absolute paths in the filename field to access system files, which are then materialized into datasets and retrieved through the download endpoint. | 23 Oct |
| CVE-2026-11816 | 8.1 high | 1.0% | keras | 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 becomes the filesystem root, allowing traversal paths to bypass the security check. Additionally, the zip filter contains a bug that causes an `AttributeError` when a blocked entry is encountered, leading to incomplete extraction. Furthermore, Python 3.11 installations lack the `filter="data"` safety net, leaving them entirely reliant on the flawed CWD-based filter. Exploitation of this vulnerability can result in arbitrary file writes outside the intended extraction directory, enabling attackers to overwrite configuration files, inject malicious code, or corrupt machine learning datasets and pipelines. | Mon 26 Oct |
| CVE-2026-66007 | 6.9 medium | 1.0% | huggingface, datasets | Datasets through 5.0.0, fixed in commit f989ef9, contains a path traversal vulnerability in folder-based dataset builders where the file_name metadata field is not properly validated before being joined to the dataset directory. Attackers can supply crafted file_name values with directory traversal sequences to read arbitrary local files, which are then embedded into output when save_to_disk or push_to_hub is called. | Sat 24 Oct |
| CVE-2026-118684 | 8.2 high | 0.00% | no CPE yet | MONAI before 1.6.1 contains an insufficient integrity verification vulnerability in check_hash() that silently returns True when hash_val is None, with MD5 as the default hash type. Attackers performing man-in-the-middle or registry compromise can substitute bundles, datasets, or model archives downloaded without hashes, enabling malicious file delivery and potential code execution. | Wed 28 Oct |
| CVE-2026-31952 | 8.1 high | 0.00% | xibosignage, xibo | Xibo is an open source digital signage platform with a web content management system and Windows display player software. Versions 1.7 through 4.4.0 have an SQL injection vulnerability in the API routes inside the CMS responsible for Filtering DataSets. This allows an authenticated user to to obtain and modify arbitrary data from the Xibo database by injecting specially crafted values in to the API filter parameter. Exploitation of the vulnerability is possible on behalf of an authorized user who has either of the `Access to DataSet Feature` privilege or the `Access to the Layout Feature` privilege. Users should upgrade to version 4.4.1 which fixes this issue. Customers who host their CMS with Xibo Signage have been patched if they are using 4.4, 4.3, 3.3, 2.3 or 1.8. Upgrading to a fixed version is necessary to remediate. Patches are available for earlier versions of Xibo CMS that are out of support, namely 3.3, 2.3, and 1.8. | Mon 26 Oct |
| CVE-2026-104103 | 8.1 high | 0.00% | no CPE yet | Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extract_archive() validated tar member names before calling TarFile.extractall() but did not validate symlink members or hard-link members. A crafted archive could create a link that escaped the extraction directory and then write a later member through that link, placing attacker-controlled content at an arbitrary filesystem path with the extracting process's privileges. The same containment check used os.path.commonprefix, so a sibling path sharing the destination's character prefix could also pass. The dataset-loading path can download and extract configured archive URLs, but exploitation requires a user to process an archive from a source controlled or compromised by the attacker on supported Python 3.12 and 3.13 runtimes. Python 3.14 is not affected because its default tar data filter rejects escaping links. This issue is fixed in version 0.17.8. | 16 Oct |
| CVE-2026-18286 | 7.8 high | 0.00% | no CPE yet | Aeon load_human_activity_segmentation_datasets Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of aeon. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the load_human_activity_segmentation_datasets method. The issue results from the lack of proper validation of a user-supplied string before using it to execute Python code. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-29160. | Mon 26 Oct |
| CVE-2026-111170 | 7.1 high | 0.00% | no CPE yet | kedro-datasets from 9.3.0 through 9.6.0 contains a path traversal vulnerability in MatplotlibDataset.save() that allows attackers to write files outside the dataset directory by supplying absolute plot names. Because validate_sub_path() strips leading slashes while pathlib's join discards the base path, attackers can create or overwrite files anywhere the process can write. | 21 Oct |
| CVE-2026-118760 | 6.5 medium | — | kubeflow, pipelines | Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. From 0.5.1 until 2.17.0, the frontend artifact routes did not check whether an authenticated user was authorized to access the requested namespace. A user who can reach the frontend and knows an artifact location can select another tenant's namespace, or omit the namespace and reach an unguarded direct handler, to read artifact contents such as datasets, models, or pipeline outputs. The issue applies to multi-user deployments that rely on Kubeflow Pipelines authorization for tenant isolation. Authentication at ingress identifies the caller but does not authorize access to the selected artifact namespace. The issue does not establish arbitrary Kubernetes Secret disclosure, storage modification, or server-side code execution. This issue is fixed in version 2.17.0. | Thu 29 Oct |
| CVE-2026-50541 | 6.5 medium | 0.00% | no CPE yet | Xibo is an open source digital signage platform with a web content management system and Windows display player software. Prior to 4.4.3, missing access-control checks on `GET /dataset/export/csv/{id}` allow an authenticated user to export data from any dataset, including datasets created by administrators, by iterating over `sequential dataset IDs`. Exploitation requires access to the privilege allowing edits, including deletion, to all created `DataSets` independently of Layouts. This privilege is not granted to non-administrators as standard. This issue is fixed in version 4.4.3. | Wed 28 Oct |
| CVE-2026-48957 | 6.4 medium | 0.00% | joomla, joomla\! | An improper access check allows unauthorized users to access com_privacy datasets. | Sun 25 Oct |
| CVE-2026-53656 | 6.3 medium | 0.00% | no CPE yet | FiftyOne is an open-source platform for refining high-quality datasets and visual AI models. Prior to 1.17.0, the FiftyOne App/API server in fiftyone/server/app.py and the /media route in fiftyone/server/routes/media.py unconditionally return Access-Control-Allow-Origin: *. Because the embedded server is local and unauthenticated, a malicious website visited by the user can read cross-origin responses. The /media endpoint accepts a filesystem path, allowing a drive-by page to read files accessible to the server process and exfiltrate them without additional clicks. The allowed_origins configuration and FIFTYONE_ALLOWED_ORIGINS environment variable now make cross-origin access explicit, while the default policy is same-origin. This issue is fixed in version 1.17.0. | 12 Oct |
| CVE-2026-14538 | 5.7 medium | 0.00% | google, mcp_toolbox_for_databases | An improper authorization and security-boundary bypass vulnerability in the bigquery-execute-sql tool component of Google mcp-toolbox versions 0.16.1 through 1.4.0 allows an authenticated attacker to bypass allowedDatasets validation checks. The toolbox relies on the BigQuery dry-run API to enforce dataset restrictions, but due to a fail-open logic flaw, it bypasses validation when the API returns an empty array for specialized constructs. This allows the attacker to extract structural DDL schemas for explicitly excluded datasets via INFORMATION_SCHEMA, and access downstream federated row data via EXTERNAL_QUERY connections. | Fri 23 Oct |
| CVE-2026-7681 | 5.5 medium | 0.00% | no CPE yet | A security vulnerability has been detected in jsbroks COCO Annotator up to 0.11.1. Affected by this vulnerability is an unknown functionality of the file backend/webserver/api/datasets.py of the component Dataset API. The manipulation of the argument DatasetId leads to authorization bypass. The attack may be initiated remotely. The exploit has been disclosed publicly and may be used. The vendor was contacted early about this disclosure but did not respond in any way. | Mon 26 Oct |
| CVE-2026-12480 | 5.5 medium | 0.00% | no CPE yet | Keras versions up to and including 3.13.2 are vulnerable to an arbitrary HDF5 file read due to an incomplete fix for CVE-2026-1669. The vulnerability resides in the `H5IOStore._verify_dataset()` and `file_editor.py` methods, which fail to check the `dataset.is_virtual` property of HDF5 datasets. This allows an attacker to craft a malicious `.keras` model archive or `.h5` weights file containing a Virtual Dataset (VDS) that references external HDF5 files on the victim's filesystem. When the victim loads the model using `keras.models.load_model()` or `keras.saving.load_model()`, the external file is transparently read, leading to potential information disclosure. Fixed in versions 3.12.2 and 3.14.1. | Sun 25 Oct |
| CVE-2026-12570 | 5.5 medium | 0.00% | no CPE yet | A vulnerability in keras-team/keras versions <= 3.15.0 allows for a denial of service (DoS) attack when loading malicious .keras model files via the keras.models.load_model() function. The H5IOStore.__getitem__ method in keras/src/saving/saving_lib.py does not validate the shape or size of datasets, leading to unbounded memory allocation. A specially crafted .keras file can exploit this flaw to trigger an out-of-memory (OOM) condition, causing the process to be terminated (exit code 137). This issue bypasses the fix for CVE-2026-0897, which only addressed a similar vulnerability in KerasFileEditor. The attack vector includes poisoned models from public repositories or malicious model registries, posing a risk to machine learning pipelines that process untrusted models. | 23 Oct |
| CVE-2026-31955 | 4.9 medium | 0.00% | xibosignage, xibo | Xibo is an open source digital signage platform with a web content management system and Windows display player software. An authenticated Server-Side Request Forgery (SSRF) vulnerability in versions prior to 4.4.1 allows users with DataSet permissions to make arbitrary HTTP requests from the CMS server to internal or external network resources. This can be exploited to scan internal infrastructure, access local cloud metadata endpoints (e.g., AWS IMDS), interact with internal services that lack authentication, or exfiltrate data. Exploitation of the vulnerability is possible on behalf of an authorized user who has both of the following privileges, which are not granted to non-admins as standard: Include "Add DataSet" button to allow for additional DataSets to be created independently to Layouts. Users should upgrade to version 4.4.1 which fixes this issue. Upgrading to a fixed version is necessary to remediate. Users unable to upgrade should revoke such privileges from users they do not trust. | Mon 26 Oct |
| CVE-2026-65010 | 4.4 medium | 0.00% | no CPE yet | Datasets through 5.00, fixed in commit ad2d853, contains a symlink-following vulnerability in Extractor.extract() that allows local attackers to write arbitrary files by pre-planting symlinks at predictable output paths. Attackers can redirect archive extraction to arbitrary filesystem locations in shared-cache environments, enabling overwrite of sensitive files and potential privilege escalation or code execution. | Sat 24 Oct |
| CVE-2026-76297 | 4.2 medium | 0.00% | no CPE yet | In Splunk Enterprise versions below 10.4.4, 10.2.8, 10.0.11, and 9.4.16, an unauthenticated user could trick a user that holds a role with the edit_federated_providers capability into turning off all federated search providers. Successful exploitation could temporarily prevent federated searches from retrieving data from remote datasets. The vulnerability is possible because the federated provider Representational State Transfer (REST) API accepts GET requests for actions that change provider state. The vulnerability requires the attacker to phish the affected user by tricking them into initiating a request within their browser. The unauthenticated user should not be able to exploit the vulnerability at will. For more information see Run federated searches over remote Splunk platform deployments (https://help.splunk.com/en/splunk-enterprise/search/federated-search/10.6/run-federated-searches-across-other-splunk-deployments/run-federated-searches-over-remote-splunk-platform-deployments) and Define roles on the Splunk platform with capabilities (https://help.splunk.com/en/splunk-enterprise/administer/manage-users-and-security/10.4/manage-splunk-platform-users-and-roles/define-roles-on-the-splunk-platform-with-capabilities) in the Splunk documentation. | Wed 28 Oct |
| CVE-2026-7680 | 2.1 low | 0.00% | no CPE yet | A weakness has been identified in jsbroks COCO Annotator up to 0.11.1. Affected is an unknown function of the file backend/webserver/api/datasets.py of the component Data Endpoint. Executing a manipulation of the argument folder can lead to path traversal. The attack can be launched remotely. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way. | Mon 26 Oct |
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EPSS scores: 2026-10-29. NVD cursor: 2026-10-29 00:22. The News page shows only notable CVEs (KEV, your stack, new criticals, EPSS over 50%, or active exploitation per SSVC); this table has all of them.