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Including CVEs outside Waratek scope✕Vendor lfprojects✕
Overview 10 matches · 0 in Waratek scope · 0 protected · 1 CISA KEV · 9 public PoC · 4 EPSS ≥ 0.5
10matches 0in Waratek scope0.0% 0protected0.0% 1CISA KEV10.0% 9public PoC90.0% 4EPSS ≥ 0.540.0%
Protected by Waratek 0 0.0% Rule in development 0 0.0% Mitigation candidate 0 0.0% No exploit published 0 0.0% Outside Waratek scope 0 0.0% Not applicable 10 100.0% Withdrawn CVE 0 0.0%
Critical 4 40.0% High 6 60.0% Medium 0 0.0% Low 0 0.0% None 0 0.0% Unknown 0 0.0%
blocked by ARMR today 0 0.0% partly blocked 0 0.0% not blocked 10 100.0% not established 0 0.0% unrecorded 0 0.0%
Exploited 10 100.0% Working exploit published 0 0.0% Proof of concept only 0 0.0% Forecast only 0 0.0% No public exploit 0 0.0%
split by peak 3 / quarter
Not applicable: 10 High: 6Critical: 4 not blocked: 10 Exploited: 10
Q1 231 Not applicable1 Critical1 not blocked1 Exploited1 Q2 231 Not applicable1 High1 not blocked1 Exploited1 Q3 230 Q4 231 Not applicable1 High1 not blocked1 Exploited1 Q1 240 Q2 241 Not applicable1 High1 not blocked1 Exploited1 Q3 240 Q4 240 Q1 250 Q2 250 Q3 250 Q4 252 Not applicable2 Critical2 not blocked2 Exploited2 Q1 260 Q2 263 Not applicable3 High3 not blocked3 Exploited3 Q3 261 Not applicable1 Critical1 not blocked1 Exploited1
Q1 23Q3 23Q1 24Q3 24Q1 25Q3 25Q1 26Q3 26
10 matches Sign in to download these CVEs as CSV or JSON, or to follow them in a feed.
CVE Severity Published▾ Status Exploitation Description
CVE-2026-64849 Critical 2026-08-17 Not applicable Exploited 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.
CVE-2026-4035 High 2026-06-03 Not applicable Exploited 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 unauthenticated users in default deployments without `basic-auth`. The impact includes potential leakage of sensitive credentials such as cloud artifact credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`), which could lead to artifact poisoning and cross-boundary code execution in downstream environments. The issue is fixed in version 3.11.0.
CVE-2026-2652 High 2026-05-15 Not applicable Exploited 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 between Flask and FastAPI authentication mechanisms, where the `_find_fastapi_validator()` function fails to handle non-`/gateway/` paths, resulting in a complete authentication bypass. This vulnerability is fixed in version 3.10.0.
CVE-2026-2614 High 2026-05-11 Not applicable Exploited 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.
CVE-2025-11201 Critical 2025-10-29 Not applicable Exploited MLflow Tracking Server Model Creation Directory Traversal Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of MLflow Tracking Server. Authentication is not required to exploit this vulnerability. The specific flaw exists within the handling of model file paths. The issue results from the lack of proper validation of a user-supplied path prior to using it in file operations. An attacker can leverage this vulnerability to execute code in the context of the service account. Was ZDI-CAN-26921.
CVE-2025-49844 Critical 2025-10-03 Not applicable Exploited Redis is an open source, in-memory database that persists on disk. Versions 8.2.1 and below allow an authenticated user to use a specially crafted Lua script to manipulate the garbage collector, trigger a use-after-free and potentially lead to remote code execution. The problem exists in all versions of Redis with Lua scripting. This issue is fixed in version 8.2.2. To workaround this issue without patching the redis-server executable is to prevent users from executing Lua scripts. This can be done using ACL to restrict EVAL and EVALSHA commands.
CVE-2024-3848 High 2024-05-16 Not applicable Exploited A path traversal vulnerability exists in mlflow/mlflow version 2.11.0, identified as a bypass for the previously addressed CVE-2023-6909. The vulnerability arises from the application's handling of artifact URLs, where a '#' character can be used to insert a path into the fragment, effectively skipping validation. This allows an attacker to construct a URL that, when processed, ignores the protocol scheme and uses the provided path for filesystem access. As a result, an attacker can read arbitrary files, including sensitive information such as SSH and cloud keys, by exploiting the way the application converts the URL into a filesystem path. The issue stems from insufficient validation of the fragment portion of the URL, leading to arbitrary file read through path traversal.
CVE-2023-6909 High 2023-12-18 Not applicable Exploited Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.
CVE-2023-2356 High 2023-04-28 Not applicable Exploited Relative Path Traversal in GitHub repository mlflow/mlflow prior to 2.3.1.
CVE-2023-1177 Critical 2023-03-24 Not applicable Exploited Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.2.1.