{"kind": "product", "path": "vulns/pypi/mlflow", "name": "mlflow", "product": "mlflow", "ecosystem": "PyPI", "items": [{"id": "CVE-2026-115886", "noindex": false, "published": "2026-10-23T21:17:21.462Z", "modified": "2026-10-23T21:17:21.462Z", "cvss": 6.5, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N", "severity": "medium", "epss": 0.00324, "kev": false, "exploits": ["public-poc"], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-115886", "title": "MLflow: SSRF on unauthenticated MLflow servers via third-party scorer kwargs in the scorer invoke, register, and GenAI evaluate endpoints", "description": "MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.12.0rc0 until 3.17.0, the scorer invoke, register, and GenAI evaluate endpoints, including unauthenticated POST /ajax-api/3.0/mlflow/scorer/invoke, accept serialized third-party scorer data that Scorer.model_validate_json resolves using a module-path allowlist without constraining the selected class or its constructor arguments. When optional trulens and trulens-providers-litellm packages are installed, an attacker can select mlflow.genai.scorers.trulens, choose a model URI outside MLflow's native provider registry so execut", "references": ["https://github.com/mlflow/mlflow/security/advisories/GHSA-2wqp-q3c6-ccj5", "https://github.com/mlflow/mlflow/pull/25890", "https://github.com/mlflow/mlflow/commit/bac30b4148c4f40045b4d4db07ae60ab3838803f"], "fixes": ["3.17.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-53995", "noindex": false, "published": "2026-10-19T21:05:16.530Z", "modified": "2026-10-20T17:34:23.424Z", "cvss": 8.8, "cvss_vector": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:H/VA:L/SC:N/SI:N/SA:N", "severity": "high", "epss": 0.00604, "kev": false, "exploits": ["public-poc"], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-53995", "title": "MLflow 3.17.1 and prior Path Traversal via Trace ID API", "description": "MLflow 3.17.1 and earlier contains a path traversal vulnerability in the FileStore tracking backend that allows unauthenticated attackers to control filesystem paths by submitting a crafted trace ID containing traversal sequences to the POST /api/3.0/mlflow/traces endpoint. Attackers can exploit FileStore.start_trace() to write trace_info.yaml, request_metadata, and tag files with attacker-controlled metadata outside the intended experiment trace directory, subject to the server process's filesystem permissions. FileStore is the default tracking backend before MLflow 3.7.0 and opt-in thereafter (the default changed to a SQLite database), so d", "references": ["https://github.com/SaiTeja-Erukude/CVE-2026-53995-mlflow-path-traversal", "https://github.com/mlflow/mlflow/pull/26842", "https://www.vulncheck.com/advisories/mlflow-path-traversal-via-trace-id-api"], "fixes": ["3.17.2"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "GHSA-gqvg-gmmx-x4hm", "noindex": false, "published": "2026-09-01T17:04:30Z", "modified": "2026-09-01T17:15:05.362285883Z", "cvss": 8.8, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H", "severity": "high", "epss": null, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/ghsa-gqvg-gmmx-x4hm", "title": "MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False safety control bypassed by mlflow.statsmodels flavor — RCE via crafted model artifact", "description": "## Summary\n\nMLflow introduced `MLFLOW_ALLOW_PICKLE_DESERIALIZATION` as a security control to prevent unsafe `pickle.load` execution during model loading, in response to CVE-2024-37052 through CVE-2024-37060. When set to `False`, operators expect all pickle deserialization to be blocked. The most recent related fix (#21188) patched a bypass in the pyfunc flavor.\n\nHowever, the `mlflow.statsmodels` flavor completely omits this guard. An attacker who places a crafted MLmodel artifact into any accessible artifact store can trigger arbitrary code execution on any process that calls `mlflow.pyfunc.load_model()` against the malicious model — **even w", "references": ["https://github.com/mlflow/mlflow/security/advisories/GHSA-gqvg-gmmx-x4hm", "https://github.com/mlflow/mlflow/pull/24686", "https://github.com/mlflow/mlflow/commit/38615289094a4b700a20b5d1dbfbe57bdfb0411f"], "fixes": ["3.15.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-64849", "noindex": false, "published": "2026-08-17T21:16:10.612Z", "modified": "2026-10-02T18:22:19.974Z", "cvss": 9.3, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:N", "severity": "critical", "epss": 0.10017, "kev": true, "exploits": ["github-poc", "nuclei"], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-64849", "title": "MLflow: Unauthenticated full-read SSRF in webhook delivery: _validate_webhook_url bypassed via unvalidated HTTP redirects (and DNS rebinding)", "description": "MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Starting in 3.3.0 and prior to 3.15.0, the unauthenticated POST /api/2.0/mlflow/webhooks/{id}/test endpoint calls _validate_webhook_url() in mlflow/utils/validation.py only for the original URL while mlflow/webhooks/delivery.py follows redirects and re-resolves the hostname without pinning the validated address, allowing attackers to reach internal or cloud metadata services and receive response_status and response_body. This issue is fixed in version 3.15.0.", "references": ["https://github.com/mlflow/mlflow/security/advisories/GHSA-7gwp-5pfp-969j", "https://github.com/mlflow/mlflow/issues/24179", "https://github.com/mlflow/mlflow/pull/24258"], "fixes": ["3.15.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}, {"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-71211", "noindex": false, "published": "2026-08-05T06:59:23.394Z", "modified": "2026-08-10T11:45:17.551Z", "cvss": 7.1, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N", "severity": "high", "epss": 0.0029, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-71211", "title": "mlflow - Unvalidated Gateway Secret api_base Enables SSRF via Gateway Proxy Endpoint", "description": "MLflow's AI Gateway accepts an auth_config.api_base value when creating a gateway secret (mlflow/server/handlers.py, _create_gateway_secret) with no validation of scheme, host, or IP range; the value is stored verbatim. The gateway proxy endpoint (mlflow/server/gateway_api.py, raw_proxy) subsequently issues an HTTP request to that stored api_base plus a caller-supplied path and returns the full response body.", "references": ["https://github.com/mlflow/mlflow/tree/v3.14.0/mlflow", "https://nvd.nist.gov/vuln/detail/CVE-2026-71211"], "fixes": [], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-8147", "noindex": false, "published": "2026-07-02T07:32:58.308Z", "modified": "2026-07-02T12:28:31.554Z", "cvss": 8.1, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N", "severity": "high", "epss": 0.00548, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-8147", "title": "Authorization Bypass in mlflow/mlflow", "description": "In MLflow versions prior to 3.14.0, when running with authentication enabled, the trace API endpoints lack proper authorization validators. This allows any authenticated user to bypass experiment-level authorization controls on all trace operations, including reading, deleting, and modifying traces on experiments they do not have permission to access. The issue arises from the `_before_request` handler, which does not register authorization validators for trace endpoints, resulting in requests proceeding without validation. This vulnerability can expose sensitive data, destroy audit logs, and allow unauthorized modifications.", "references": ["https://huntr.com/bounties/b00c3ddd-373e-492f-9bf0-41a28bb21ed5", "https://github.com/mlflow/mlflow/commit/f9b1eb510478570609ef451984a255775aa4b937", "https://nvd.nist.gov/vuln/detail/CVE-2026-8147"], "fixes": ["3.13.0rc0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-10803", "noindex": false, "published": "2026-06-04T11:45:10.363Z", "modified": "2026-06-04T12:55:59.415Z", "cvss": 2, "cvss_vector": "CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N/E:P", "severity": "low", "epss": 0.00103, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-10803", "title": "MLflow Dataset Digest Computation digest_utils.py mlflow.data.digest_utils weak hash", "description": "A flaw has been found in MLflow up to 3.10.0. This issue affects the function mlflow.data.digest_utils of the file mlflow/data/digest_utils.py of the component Dataset Digest Computation. This manipulation causes use of weak hash. It is possible to launch the attack on the local host. The attack is considered to have high complexity. The exploitability is assessed as difficult. The exploit has been published and may be used. The project was informed of the problem early through a pull request but has not reacted yet.", "references": ["https://vuldb.com/vuln/368252", "https://vuldb.com/vuln/368252/cti", "https://vuldb.com/cve/CVE-2026-10803"], "fixes": ["3.10.1"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-4035", "noindex": false, "published": "2026-06-03T07:18:08.512Z", "modified": "2026-08-14T12:04:28.457Z", "cvss": 7.7, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N", "severity": "high", "epss": 0.00521, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-4035", "title": "Environment Variable Resolution Vulnerability in mlflow/mlflow", "description": "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 the configured upstream `api_base`. This vulnerability can be exploited by low-privileged authenticated users in basic-auth deployments or by unauthenti", "references": ["https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233", "https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3", "https://access.redhat.com/security/cve/CVE-2026-4035"], "fixes": ["3.11.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-3198", "noindex": false, "published": "2026-06-02T02:50:47.890Z", "modified": "2026-06-02T13:32:42.643Z", "cvss": 6.5, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N", "severity": "medium", "epss": 0.00244, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-3198", "title": "Improper Access Control in mlflow/mlflow", "description": "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 vulnerability exposes sensitive information, such as API keys, endpoint configurations, and proprietary model definitions, to unauthorized users.", "references": ["https://huntr.com/bounties/e57db731-97d3-40c3-a429-831ee959807f", "https://nvd.nist.gov/vuln/detail/CVE-2026-3198"], "fixes": ["3.11.0rc0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-2651", "noindex": false, "published": "2026-05-25T06:00:34.002Z", "modified": "2026-07-15T02:49:04.921Z", "cvss": 9, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H", "severity": "critical", "epss": 0.00345, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-2651", "title": "Missing Authorization Validation in mlflow/mlflow", "description": "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 resolved in version 3.10.0.", "references": ["https://huntr.com/bounties/65beb119-d3e0-4e03-af2f-fa98f78f83dc", "https://github.com/mlflow/mlflow/commit/d7290811d8f3c95366d80109424edc1fb1ad966f", "https://access.redhat.com/security/cve/CVE-2026-2651"], "fixes": ["3.10.0", "3.11.0rc0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}, {"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-2734", "noindex": false, "published": "2026-05-21T03:49:38.297Z", "modified": "2026-05-21T12:40:09.114Z", "cvss": 6.5, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N", "severity": "medium", "epss": 0.00441, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-2734", "title": "Authorization Bypass in SearchModelVersions in mlflow/mlflow", "description": "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 omission from `GraphQLAuthorizationMiddleware.PROTECTED_FIELDS` for GraphQL. This vulnerability can expose sensitive information such as model names, ", "references": ["https://huntr.com/bounties/d632f783-b2c7-4a3b-af5e-1d693e841c08", "https://github.com/mlflow/mlflow/commit/6989066af33fdcb03588fd71a1a67f8fc5ef12c9", "https://nvd.nist.gov/vuln/detail/CVE-2026-2734"], "fixes": ["3.10.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-2611", "noindex": false, "published": "2026-05-19T09:16:42.745Z", "modified": "2026-07-15T02:49:09.458Z", "cvss": 9.6, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H", "severity": "critical", "epss": 0.00384, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-2611", "title": "Improper Origin Validation in mlflow/mlflow", "description": "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-agent. This issue is resolved in version 3.10.0.", "references": ["https://huntr.com/bounties/8462addd-b464-4a84-b6a2-5529604e6e5a", "https://github.com/mlflow/mlflow/commit/8f9c8a53af90842944101eb8b7d60706822c81bc", "https://access.redhat.com/security/cve/CVE-2026-2611"], "fixes": ["3.10.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-4137", "noindex": false, "published": "2026-05-18T20:26:23.104Z", "modified": "2026-05-19T12:47:53.221Z", "cvss": 7, "cvss_vector": "CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.00193, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-4137", "title": "Incomplete Fix for CVE-2025-10279: Insecure Temporary Directory Permissions in mlflow/mlflow", "description": "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 when the tampered artifacts are deserialized via `cloudpickle.load()`. This vulnerability is particularly critical in environments with shared NFS mo", "references": ["https://huntr.com/bounties/648dc30b-76c7-4433-86b8-f43d926fd8d6", "https://github.com/mlflow/mlflow/commit/1dcbb0c2fbd1f446c328830e601ca13a28219b8a", "https://nvd.nist.gov/vuln/detail/CVE-2026-4137"], "fixes": ["3.11.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}, {"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-2652", "noindex": false, "published": "2026-05-15T02:13:19.541Z", "modified": "2026-05-15T13:22:21.060Z", "cvss": 8.6, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:L", "severity": "high", "epss": 0.20783, "kev": false, "exploits": ["nuclei"], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-2652", "title": "Authentication Bypass in mlflow/mlflow", "description": "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 submit jobs, read job results, cancel running jobs, and inject arbitrary trace data into experiments. The issue arises from an architectural mismatch be", "references": ["https://huntr.com/bounties/5aeff5f0-49c7-4180-b5cb-c9a046f16756", "https://github.com/mlflow/mlflow/commit/bb62e773263c14e9ba4d1a82fe72d0de2442c6aa", "https://nvd.nist.gov/vuln/detail/CVE-2026-2652"], "fixes": ["3.10.0", "3.11.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}, {"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-2614", "noindex": false, "published": "2026-05-11T19:02:46.025Z", "modified": "2026-08-28T12:04:27.071Z", "cvss": 7.5, "cvss_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N", "severity": "high", "epss": 0.03691, "kev": false, "exploits": ["nuclei"], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-2614", "title": "Arbitrary File Read via Prompt Tag Source Validation Bypass in mlflow/mlflow", "description": "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_handler()` function later uses this source to serve files without verifying the model version's prompt status, leading to a complete confidentiality comprom", "references": ["https://huntr.com/bounties/19380271-3fbf-4beb-987e-6fd7069c55e6", "https://github.com/mlflow/mlflow/commit/6e801f4259d96804c73107315b24cef0f6aa115a", "https://access.redhat.com/security/cve/CVE-2026-2614"], "fixes": ["3.10.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-2393", "noindex": false, "published": "2026-05-11T16:30:04.201Z", "modified": "2026-05-11T18:52:41.710Z", "cvss": 7.1, "cvss_vector": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N", "severity": "high", "epss": 0.00288, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-2393", "title": "Server-Side Request Forgery (SSRF) in mlflow/mlflow", "description": "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 arbitrary external servers. The lack of input sanitization, URL scheme filtering, or allowlist validation on the webhook URL enables exploitation, potentially", "references": ["https://huntr.com/bounties/04ef100d-06b5-4a70-95b1-b7be23aa8150", "https://github.com/mlflow/mlflow/commit/64aa0ab7207f9c649b59ba1a5f40d82196817389", "https://nvd.nist.gov/vuln/detail/CVE-2026-2393"], "fixes": ["3.9.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-33866", "noindex": false, "published": "2026-04-07T12:57:44.380Z", "modified": "2026-04-14T15:12:44.168Z", "cvss": 5.3, "cvss_vector": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N", "severity": "medium", "epss": 0.00362, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-33866", "title": "Authorization Bypass in MLflow AJAX Endpoint", "description": "MLflow is vulnerable to an authorization bypass affecting the AJAX endpoint used to download saved model artifacts. Due to missing access‑control validation, a user without permissions to a given experiment can directly query this endpoint and retrieve model artifacts they are not authorized to access.\n\n \nThis issue affects MLflow version through 3.10.1", "references": ["https://github.com/mlflow/mlflow/pull/21708", "https://cert.pl/en/posts/2026/04/CVE-2026-33865/", "https://afine.com/blogs/attacking-mlflow-how-ml-artifacts-become-attack-vectors"], "fixes": ["3.11.0rc0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-33865", "noindex": false, "published": "2026-04-07T12:57:38.525Z", "modified": "2026-04-14T15:13:57.547Z", "cvss": 5.1, "cvss_vector": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:N/VI:L/VA:N/SC:L/SI:L/SA:N", "severity": "medium", "epss": 0.00218, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-33865", "title": "Stored XSS via unsafe YAML parsing in MLflow", "description": "MLflow is vulnerable to Stored Cross-Site Scripting (XSS) caused by unsafe parsing of YAML-based MLmodel artifacts in its web interface. An authenticated attacker can upload a malicious MLmodel file containing a payload that executes when another user views the artifact in the UI. This allows actions such as session hijacking or performing operations on behalf of the victim. \n\nThis issue affects MLflow version through 3.10.1", "references": ["https://github.com/mlflow/mlflow/pull/21435", "https://cert.pl/en/posts/2026/04/CVE-2026-33865/", "https://afine.com/blogs/attacking-mlflow-how-ml-artifacts-become-attack-vectors"], "fixes": ["3.11.0rc0", "3.11.1"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}, {"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-0545", "noindex": false, "published": "2026-04-03T17:03:12.833Z", "modified": "2026-08-28T12:04:27.665Z", "cvss": 8.1, "cvss_vector": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H", "severity": "high", "epss": 0.04392, "kev": false, "exploits": ["nuclei"], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-0545", "title": "Missing Authentication for Critical Function in mlflow/mlflow", "description": "In mlflow/mlflow, the FastAPI job endpoints under `/ajax-api/3.0/jobs/*` are not protected by authentication or authorization when the `basic-auth` app is enabled. This vulnerability affects the latest version of the repository. If job execution is enabled (`MLFLOW_SERVER_ENABLE_JOB_EXECUTION=true`) and any job function is allowlisted, any network client can submit, read, search, and cancel jobs without credentials, bypassing basic-auth entirely. This can lead to unauthenticated remote code execution if allowed jobs perform privileged actions such as shell execution or filesystem changes. Even if jobs are deemed safe, this still constitutes a", "references": ["https://huntr.com/bounties/b2e5b028-9541-4d29-8703-a76f1a3734d8", "https://access.redhat.com/security/cve/CVE-2026-0545", "https://bugzilla.redhat.com/show_bug.cgi?id=2454889"], "fixes": [], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}, {"id": "CVE-2026-0596", "noindex": false, "published": "2026-03-31T14:25:27.716Z", "modified": "2026-04-01T03:55:35.518Z", "cvss": 9.6, "cvss_vector": "CVSS:3.0/AV:A/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H", "severity": "critical", "epss": 0.01328, "kev": false, "exploits": [], "stacks": [{"name": "python", "path": "vulns/stack/python", "slug": "python"}], "path": "vulns/cve-2026-0596", "title": "Command Injection in mlflow/mlflow", "description": "A command injection vulnerability exists in mlflow/mlflow when serving a model with `enable_mlserver=True`. The `model_uri` is embedded directly into a shell command executed via `bash -c` without proper sanitization. If the `model_uri` contains shell metacharacters, such as `$()` or backticks, it allows for command substitution and execution of attacker-controlled commands. This vulnerability affects the latest version of mlflow/mlflow and can lead to privilege escalation if a higher-privileged service serves models from a directory writable by lower-privileged users.", "references": ["https://huntr.com/bounties/2e905add-f9f5-4309-a3db-b17de5981285", "https://nvd.nist.gov/vuln/detail/CVE-2026-0596"], "fixes": ["3.9.0"], "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}]}], "total": 84, "unknown_count": 0, "release_unconfirmed": false, "page": 1, "pages": 5, "filtered": false, "noindex": false, "filters": {}, "page_size": 20, "products": [{"name": "mlflow", "path": "vulns/pypi/mlflow", "ecosystem": "PyPI"}], "stacks": [{"name": "system", "path": "vulns/stack/system", "slug": "system"}, {"name": "web", "path": "vulns/stack/web", "slug": "web"}, {"name": "php", "path": "vulns/stack/php", "slug": "php"}, {"name": "python", "path": "vulns/stack/python", "slug": "python"}, {"name": "node", "path": "vulns/stack/node", "slug": "node"}, {"name": "database", "path": "vulns/stack/database", "slug": "database"}, {"name": "containers", "path": "vulns/stack/containers", "slug": "containers"}, {"name": "network", "path": "vulns/stack/network", "slug": "network"}, {"name": "applications", "path": "vulns/stack/applications", "slug": "applications"}], "versions": ["3.17.1", "3.17.0", "3.16.1", "3.16.0", "3.15.2", "3.15.1", "3.15.0", "3.14.0", "3.13.0rc0", "3.13.0", "3.12.0rc0", "3.12.0"], "stats": {"recent": 2, "kev": 0}, "lastmod": "2026-10-23T21:17:21.462Z", "early_advisories": [], "license": "Vous pouvez librement utiliser la sélection de PatchFirst et nos ajouts (priorités, alertes précoces, textes, synthèses et agrégats) pour vos propres besoins, y compris les activités internes de votre entreprise. La revente, la distribution commerciale et la mise en miroir massive de cette sélection ou de ces ajouts nécessitent un accord écrit avec l’opérateur. Lors de toute utilisation ou publication de la sélection ou de nos ajouts, citez PatchFirst (https://patchfirst.dev/vulns/) avec ce lien vers la page du flux de votre région. Les enregistrements originaux des sources ouvertes restent soumis à leurs licences et conditions respectives. Ces conditions ne limitent pas vos droits sur les données originales, que vous pouvez obtenir directement auprès de ces sources.", "terms_url": "https://patchfirst.dev/fr/vulns/#feed-terms", "attribution": {"name": "PatchFirst", "url": "https://patchfirst.dev/vulns/"}, "source_changes": "PatchFirst sélectionne, normalise et combine les enregistrements ; des synthèses et des traductions peuvent être ajoutées. Les actualités sont accompagnées d’un lien vers la source originale dans chaque entrée.", "sources": [{"id": "cve", "name": "CVE List / CVE.org", "url": "https://www.cve.org/", "license": "CVE Terms of Use", "terms_url": "https://www.cve.org/Legal/TermsOfUse", "notice": "Copyright © 1999–2021, The MITRE Corporation. LICENSE Submissions : For all materials you submit to the Common Vulnerabilities and Exposures (CVE™), you hereby grant to The MITRE Corporation (MITRE) and all CVE Numbering Authorities (CNAs) a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare derivative works of, publicly display, publicly perform, sublicense, and distribute such materials and derivative works. Unless required by applicable law or agreed to in writing, you provide such materials on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. CVE Usage : MITRE hereby grants you a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare derivative works of, publicly display, publicly perform, sublicense, and distribute Common Vulnerabilities and Exposures (CVE™). Any copy you make for such purposes is authorized provided that you reproduce MITRE's copyright designation and this license in any such copy. DISCLAIMERS ALL DOCUMENTS AND THE INFORMATION CONTAINED THEREIN PROVIDED BY MITRE ARE PROVIDED ON AN \"AS IS\" BASIS AND THE CONTRIBUTOR, THE ORGANIZATION HE/SHE REPRESENTS OR IS SPONSORED BY (IF ANY), THE MITRE CORPORATION, ITS BOARD OF TRUSTEES, OFFICERS, AGENTS, AND EMPLOYEES, DISCLAIM ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION THEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE."}, {"id": "osv", "name": "OSV", "url": "https://osv.dev/", "terms_url": "https://google.github.io/osv.dev/data/", "terms": "Les licences des bases d’origine varient ; voir le catalogue des sources."}, {"id": "kev", "name": "CISA KEV", "url": "https://www.cisa.gov/known-exploited-vulnerabilities-catalog", "license": "CC0-1.0", "terms_url": "https://github.com/cisagov/kev-data/blob/develop/LICENSE"}, {"id": "epss", "name": "FIRST EPSS", "url": "https://www.first.org/epss/", "terms_url": "https://www.first.org/epss/faq", "terms": "Évaluations publiques gratuites ; mention de la source demandée (FIRST EPSS, évaluations produites par Empirical Security)."}, {"id": "github-advisory", "name": "GitHub Advisory Database", "url": "https://github.com/advisories", "license": "CC-BY-4.0", "terms_url": "https://github.com/github/advisory-database/blob/main/LICENSE.md"}, {"id": "exploitdb", "name": "Exploit-DB", "url": "https://www.exploit-db.com/", "license": "GPL-2.0", "terms_url": "https://gitlab.com/exploit-database/exploitdb/-/blob/main/LICENSE.md"}, {"id": "metasploit", "name": "Metasploit", "url": "https://github.com/rapid7/metasploit-framework", "license": "BSD-3-Clause", "terms_url": "https://github.com/rapid7/metasploit-framework/blob/master/LICENSE", "notice": "Copyright (c) 2006-2026, Rapid7, Inc.\nLicense: BSD-3-clause\n Redistribution and use in source and binary forms, with or without modification,\n are permitted provided that the following conditions are met:\n .\n * Redistributions of source code must retain the above copyright notice,\n this list of conditions and the following disclaimer.\n .\n * Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n .\n * Neither the name of Rapid7, Inc. nor the names of its contributors\n may be used to endorse or promote products derived from this software\n without specific prior written permission.\n .\n THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND\n ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\n WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\n DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR\n ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\n LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON\n ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\n SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE."}, {"id": "nuclei", "name": "Nuclei Templates", "url": "https://github.com/projectdiscovery/nuclei-templates", "license": "MIT", "terms_url": "https://github.com/projectdiscovery/nuclei-templates/blob/main/LICENSE.md", "notice": "MIT License\n\nCopyright (c) 2025 ProjectDiscovery, Inc.\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."}, {"id": "linux-kernel", "name": "Linux kernel releases", "url": "https://www.kernel.org/", "license": "CC-BY-SA-4.0", "terms_url": "https://www.kernel.org/legal.html", "notice": "Copyright (C) 1997-2014 by The Linux Kernel Organization, Inc."}]}