The Go MCP SDK used Go's standard encoding/json. Prior to version 1.4.1, the Go SDK's Streamable HTTP transport accepted browser-generated cross-site `POST` requests without validating the `Origin` header and without requiring `Content-Type: application/json`. In deployments without Authorization, especially stateless or sessionless configurations, this allows an arbitrary website to send MCP requests to a local server and potentially trigger tool execution. Version 1.4.1 contains a patch for the issue.

In mcp-server-git versions prior to 2025.12.17, the git_diff and git_checkout functions passed user-controlled arguments directly to git CLI commands without sanitization. Flag-like values (e.g., `--output=/path/to/file` for `git_diff`) would be interpreted as command-line options rather than git refs, enabling arbitrary file overwrites. The fix adds validation that rejects arguments starting with - and verifies the argument resolves to a valid git ref via rev_parse before execution. Users are advised to update to 2025.12.17 resolve this issue when it is released.

Model Context Protocol Servers is a collection of reference implementations for the model context protocol (MCP). In mcp-server-git versions prior to 2026.1.14, the git_add tool did not validate that file paths provided in the files argument were within the repository boundaries. Because the tool used GitPython's repo.index.add() rather than the Git CLI, relative paths containing `../` sequences that resolve outside the repository were accepted and staged into the Git index. Users are advised to upgrade to 2026.1.14 or newer to remediate this issue.

A Local File Inclusion (LFI) vulnerability was identified in mlflow/mlflow, specifically in version 2.9.2, which was fixed in version 2.11.3. This vulnerability arises from the application's failure to properly validate URI fragments for directory traversal sequences such as '../'. An attacker can exploit this flaw by manipulating the fragment part of the URI to read arbitrary files on the local file system, including sensitive files like '/etc/passwd'. The vulnerability is a bypass to a previous patch that only addressed similar manipulation within the URI's query string, highlighting the need for comprehensive validation of all parts of a URI to prevent LFI attacks.

A directory traversal vulnerability in the /get-artifact API method of the mlflow platform up to v2.0.1 allows attackers to read arbitrary files on the server via the path parameter.

A vulnerability in MLflow's pyfunc extraction process allows for arbitrary file writes due to improper handling of tar archive entries. Specifically, the use of `tarfile.extractall` without path validation enables crafted tar.gz files containing `..` or absolute paths to escape the intended extraction directory. This issue affects the latest version of MLflow and poses a high/critical risk in scenarios involving multi-tenant environments or ingestion of untrusted artifacts, as it can lead to arbitrary file overwrites and potential remote code execution.

A path traversal vulnerability exists in the mlflow/mlflow repository, specifically within the artifact deletion functionality. Attackers can bypass path validation by exploiting the double decoding process in the `_delete_artifact_mlflow_artifacts` handler and `local_file_uri_to_path` function, allowing for the deletion of arbitrary directories on the server's filesystem. This vulnerability is due to an extra unquote operation in the `delete_artifacts` function of `local_artifact_repo.py`, which fails to properly sanitize user-supplied paths. The issue is present up to version 2.9.2, despite attempts to fix a similar issue in CVE-2023-6831.

Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.2.1.

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.

mlflow/mlflow is vulnerable to Local File Inclusion (LFI) due to improper parsing of URIs, allowing attackers to bypass checks and read arbitrary files on the system. The issue arises from the 'is_local_uri' function's failure to properly handle URIs with empty or 'file' schemes, leading to the misclassification of URIs as non-local. Attackers can exploit this by crafting malicious model versions with specially crafted 'source' parameters, enabling the reading of sensitive files within at least two directory levels from the server's root.

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.

Zarf is an Airgap Native Packager Manager for Kubernetes. From version 0.54.0 to before version 0.73.1, a path traversal vulnerability in archive extraction allows a specifically crafted Zarf package to create symlinks pointing outside the destination directory, enabling arbitrary file read or write on the system processing the package. This issue has been patched in version 0.73.1.

A path traversal vulnerability exists in the mlflow/mlflow repository due to improper handling of URL parameters. By smuggling path traversal sequences using the ';' character in URLs, attackers can manipulate the 'params' portion of the URL to gain unauthorized access to files or directories. This vulnerability allows for arbitrary data smuggling into the 'params' part of the URL, enabling attacks similar to those described in previous reports but utilizing the ';' character for parameter smuggling. Successful exploitation could lead to unauthorized information disclosure or server compromise.

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.

A path traversal vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the `artifact_location` parameter when creating an experiment. Attackers can exploit this vulnerability by using a fragment component `#` in the artifact location URI to read arbitrary files on the server in the context of the server's process. This issue is similar to CVE-2023-6909 but utilizes a different component of the URI to achieve the same effect.

A path traversal vulnerability exists in mlflow/mlflow version 2.9.2, allowing attackers to access arbitrary files on the server. By crafting a series of HTTP POST requests with specially crafted 'artifact_location' and 'source' parameters, using a local URI with '#' instead of '?', an attacker can traverse the server's directory structure. The issue occurs due to insufficient validation of user-supplied input in the server's handlers.

A path traversal vulnerability exists in the `_create_model_version()` function within `server/handlers.py` of the mlflow/mlflow repository, due to improper validation of the `source` parameter. Attackers can exploit this vulnerability by crafting a `source` parameter that bypasses the `_validate_non_local_source_contains_relative_paths(source)` function's checks, allowing for arbitrary file read access on the server. The issue arises from the handling of unquoted URL characters and the subsequent misuse of the original `source` value for model version creation, leading to the exposure of sensitive files when interacting with the `/model-versions/get-artifact` handler.

In mcp-server-git versions prior to 2025.12.17, when the server is started with the --repository flag to restrict operations to a specific repository path, it did not validate that repo_path arguments in subsequent tool calls were actually within that configured path. This could allow tool calls to operate on other repositories accessible to the server process. The fix adds path validation that resolves both the configured repository and the requested path (following symlinks) and verifies the requested path is within the allowed repository before executing any git operations. Users are advised to upgrade to 2025.12.17 upon release to remediate this issue.

Model Context Protocol Servers is a collection of reference implementations for the model context protocol (MCP). In mcp-server-git versions prior to 2025.9.25, the git_init tool accepted arbitrary filesystem paths and created Git repositories without validating the target location. Unlike other tools which required an existing repository, git_init could operate on any directory accessible to the server process, making those directories eligible for subsequent git operations. The tool was removed entirely, as the server is intended to operate on existing repositories only. Users are advised to upgrade to 2025.9.25 or newer to remediate this issue.

A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.http_dataset_source.py` module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the `Content-Disposition` header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0.

Path Traversal in GitHub repository mlflow/mlflow prior to 2.9.2.

Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.

MLflow allowed arbitrary files to be PUT onto the server.

Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') vulnerability in Brainstorm Force Ultimate Addons for WPBakery Page Builder allows PHP Local File Inclusion.This issue affects Ultimate Addons for WPBakery Page Builder: from n/a through 3.19.14.