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CVE-2026-53995

MLflow < 3.18.0 Path Traversal via Trace ID API

MLflow before 3.18.0 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 deployments in the earlier part of the affected range are vulnerable without special configuration while later ones are affected only when FileStore is explicitly selected.

CVSS 4.0 · 8.8 High EPSS < 1% KEV · Not listed
Vendors
Lfprojects Mlflow
Products
Mlflow Mlflow
CVE-2026-127202

MLflow < 3.18.0 Path Traversal via model_id in log_outputs API

MLflow before 3.18.0 using the FileStore backend contains a path traversal vulnerability that allows unauthenticated remote attackers to write files outside the intended run directory by supplying a malicious model_id parameter to the log outputs API. Attackers can exploit the unvalidated model_id containing ../ sequences via the POST /api/3.0/mlflow/runs/outputs endpoint to create directories and write a meta.yaml file at arbitrary filesystem locations, limited only by the server account's permissions. FileStore was the default backend before 3.7.0 and is opt-in afterward through MLFLOW_ALLOW_FILE_STORE.

CVSS 4.0 · 6.3 Medium EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-118628

MLflow get-artifacts Server-Side Request Forgery Information Disclosure Vulnerability

MLflow get-artifacts Server-Side Request Forgery Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of MLflow. Authentication is not required to exploit this vulnerability. The specific flaw exists within the get-artifacts function. The issue results from the lack of proper validation of a URI prior to accessing resources. An attacker can leverage this vulnerability to disclose information in the context of the server. Was ZDI-CAN-28192.

CVSS 3.1 · 5.3 Medium EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-118627

MLflow SHAP load_explainer Deserialization of Untrusted Data Remote Code Execution Vulnerability

MLflow SHAP load_explainer Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of MLflow. 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 loading of SHAP explainer models. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-30301.

CVSS 3.1 · 7.8 High EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-118626

MLflow Tracking Server Issues Missing Authorization Privilege Escalation Vulnerability

MLflow Tracking Server Issues Missing Authorization Privilege Escalation Vulnerability. This vulnerability allows remote attackers to escalate privileges on affected installations of MLflow. Authentication is required to exploit this vulnerability. The specific flaw exists within the configuration of the BEFORE_REQUEST_HANDLERS. The issue results from the lack of authorization prior to allowing access to functionality. An attacker can leverage this vulnerability to escalate privileges to resources normally protected from the user. Was ZDI-CAN-32108.

CVSS 3.1 · 5.4 Medium EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-118625

MLflow Tracking Server Missing Authorization Privilege Escalation Vulnerability

MLflow Tracking Server Missing Authorization Privilege Escalation Vulnerability. This vulnerability allows remote attackers to escalate privileges on affected installations of MLflow. Authentication is required to exploit this vulnerability. The specific flaw exists within the get_endpoints function. The issue results from the lack of authorization prior to allowing access to functionality. An attacker can leverage this vulnerability to escalate privileges to resources normally protected from the user. Was ZDI-CAN-32107.

CVSS 3.1 · 6.3 Medium EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-118624

MLflow Tracking Server Jobs Missing Authorization Information Disclosure Vulnerability

MLflow Tracking Server Jobs Missing Authorization Information Disclosure Vulnerability. This vulnerability allows remote attackers to disclose sensitive information on affected installations of MLflow. Authentication is required to exploit this vulnerability. The specific flaw exists within the _find_validator function. The issue results from the lack of authorization prior to allowing access to functionality. An attacker can leverage this vulnerability to disclose information in the context of the service account. Was ZDI-CAN-31894.

CVSS 3.1 · 5.4 Medium EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-118623

MLflow PickleEvaluationArtifact Deserialization of Untrusted Data Remote Code Execution Vulnerability

MLflow PickleEvaluationArtifact Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of MLflow. 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 parsing of pickle files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-29513.

CVSS 3.1 · 7.8 High EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2025-15381

Unauthorized Access to Tracing and Assessment Endpoints in mlflow/mlflow

In the latest version of mlflow/mlflow, when the `basic-auth` app is enabled, tracing and assessment endpoints are not protected by permission validators. This allows any authenticated user, including those with `NO_PERMISSIONS` on the experiment, to read trace information and create assessments for traces they should not have access to. This vulnerability impacts confidentiality by exposing trace metadata and integrity by allowing unauthorized creation of assessments. Deployments using `mlflow server --app-name=basic-auth` are affected.

CVSS 3.1 · 7.1 High EPSS < 1% KEV · Not listed
Vendors
Lfprojects Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-116691

MLflow CrewAI autologging records LLM provider API keys in logged trace spans

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 2.19.0 until 3.17.0, mlflow.crewai.autolog() records CrewAI Agent objects without consistently sanitizing nested credential-bearing values. mlflow/crewai/autolog.py::_get_agent_attributes() converts the Agent llm field to a string that includes the provider API key, while mlflow/crewai/autolog.py::_construct_full_inputs() expands the Agent object into mlflow.spanInputs. Applications can therefore send plaintext provider credentials to the MLflow trace backend or a configured OTLP destination, where trace readers can obtain them. This issue is fixed in version 3.17.0.

CVSS 3.1 · 6.5 Medium EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow
CVE-2026-116692

MLflow: Remote code execution on unauthenticated MLflow servers via third-party scorer deserialization importing caller-placed artifact modules

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, third-party scorer deserialization in mlflow/genai/scorers/base.py accepts request-selected descendants of THIRD_PARTY_SCORER_ALLOWED_MODULES rather than requiring an exact allowed module. A caller can use MLflow artifact endpoints to place a Python module beneath a writable allowed package and submit its module and class through /ajax-api/3.0/mlflow/scorer/invoke. Scorer.model_validate_json() imports the module and constructs the class before trace processing. Authentication-disabled deployments permit this code execution without credentials, while basic-auth deployments require a principal capable of creating an experiment and run and uploading artifacts. In either configuration, the allowed scorer package must be writable by the server process. This issue is fixed in version 3.17.0.

CVSS 3.1 · 9.8 Critical EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow
CVE-2026-115886

MLflow: SSRF on unauthenticated MLflow servers via third-party scorer kwargs in the scorer invoke, register, and GenAI evaluate endpoints

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 execution uses the LiteLLM fallback, and supply api_base and api_key values that cause the server to send an outbound request to an attacker-chosen or internal host with attacker-controlled headers and body. The vulnerable deserialization occurs before a tracking-store lookup or job submission. This issue is fixed in version 3.17.0.

CVSS 3.1 · 6.5 Medium EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow
CVE-2026-116690

MLflow: Arbitrary file read on unauthenticated MLflow servers via prompt model version source

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.10.0 until 3.17.0, the prompt branch in _create_model_version() accepts schemeless relative sources because path validation runs only when a source has a URL scheme, and mlflow.prompt.is_prompt is interpreted by tag presence rather than a true value. A remote caller can store a server-local path as the model version artifact location and use /api/2.0/mlflow/model-versions/get-artifact to read files accessible to the MLflow server process. Default unauthenticated servers require no privileges, while basic-auth deployments are exposed to authenticated users who can create registered models. This issue is fixed in version 3.17.0.

CVSS 3.1 · 7.5 High EPSS 1.8% KEV · Not listed
Vendors
Mlflow
Products
Mlflow
CVE-2026-64849

MLflow: Unauthenticated full-read SSRF in webhook delivery: _validate_webhook_url bypassed via unvalidated HTTP redirects (and DNS rebinding)

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.

CVSS 3.1 · 9.3 Critical EPSS 10.0% KEV · Listed
Vendors
Lfprojects Mlflow
Products
Mlflow Mlflow
CVE-2026-96804

CVE-2026-96804

MLflow's statsmodel flavor, versions 2.1.0 to 3.14.0, omits the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control entirely in _load_model(), which allows a remote attacker to execute arbitrary code via a crafted MLmodel artifact.

CVSS 3.1 · 8.8 High EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow
CVE-2026-96775

MLflow dspy bypasses pickle deserialization control

MLflow's dspy flavor, versions >= 2.0, applies the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control only when the model_path ends in .pkl, which allows a remote attacker to execute arbitrary code via a crafted MLmodel artifact.

CVSS 3.1 · 8.8 High EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow
CVE-2026-79721

Arbitrary Code Execution via Malicious MLflow Model Artifacts

Code execution can occur in versions of the MLflow platform running version 0.0.1 or newer, enabling a maliciously crafted model artifact to execute arbitrary code on an end user's system when loaded by the project.

CVSS 4.0 · 8.6 High EPSS < 1% KEV · Not listed
Vendors
Mlflow
Products
Mlflow
CVE-2025-15379

Command Injection in mlflow/mlflow

A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.

CVSS 3.1 · 10.0 Critical EPSS 2.4% KEV · Not listed
Vendors
Lfprojects Mlflow
Products
Mlflow Mlflow
CVE-2026-2614

Arbitrary File Read via Prompt Tag Source Validation Bypass in mlflow/mlflow

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 compromise. This issue is fixed in version 3.10.0.

CVSS 3.1 · 7.5 High EPSS 3.6% KEV · Not listed
Vendors
Lfprojects Mlflow
Products
Mlflow Mlflow/mlflow
CVE-2026-0545

Missing Authentication for Critical Function in mlflow/mlflow

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 an authentication bypass, potentially resulting in job spam, denial of service (DoS), or data exposure in job results.

CVSS 3.1 · 9.8 Critical EPSS 4.4% KEV · Not listed
Vendors
Lfprojects Mlflow
Products
Mlflow Mlflow