> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/deployment/self-hosted/inference-server/configuration/input-formats.md).

# Accepted Input Formats

## Why this matters

The Inference server is designed to be straightforward to integrate, which is why some convenient but potentially less secure data loading methods are available. For production deployments, configuration options let you disable those behaviors.

This page explains how to configure the server to either harden it or enable more flexible behavior, depending on your needs.

## Deserialization of pickled numpy objects

One way to send requests to the Inference server is with serialized numpy objects:

```python
import cv2
import pickle
import requests

image = cv2.imread("...")
img_str = pickle.dumps(image)

infer_payload = {
    "model_id": "{project_id}/{model_version}",
    "image": {
        "type": "numpy",
        "value": img_str,
    },
    "api_key": "YOUR_API_KEY",
}

res = requests.post(
    "http://localhost:9001/infer/{task}",
    json=infer_payload,
)
```

Starting with version `v0.14.0`, deserialization of this payload type is disabled by default. You can enable it by setting `ALLOW_NUMPY_INPUT=True`. See the [Inference CLI](https://docs.roboflow.com/reference/inference/inference-cli/server) docs for how to run the server with that flag. This option is **not available in Roboflow's hosted APIs**.

{% hint style="warning" %}
Do not enable this option in production if the server is open to requests from the open internet, or is not locked down to accept only authenticated requests from your workspace's API key.
{% endhint %}

## Sending URLs to inference images

Fetching images from URLs is convenient, but it can expose the server to [server-side request forgery (SSRF) attacks](https://en.wikipedia.org/wiki/Server-side_request_forgery):

```python
import requests

infer_payload = {
    "model_id": "{project_id}/{model_version}",
    "image": {
        "type": "url",
        "value": "https://some.com/image.jpg",
    },
    "api_key": "YOUR_API_KEY",
}

res = requests.post(
    "http://localhost:9001/infer/{task}",
    json=infer_payload,
)
```

This option is **enabled by default**. We recommend configuring the server with one or more of these environment variables:

* `ALLOW_URL_INPUT` - set to `False` to reject image URLs of any kind. Default: `True`.
* `ALLOW_NON_HTTPS_URL_INPUT` - set to `False` to only allow the HTTPS protocol in URLs. Default: `False`.
* `ALLOW_URL_INPUT_WITHOUT_FQDN` - set to `False` to enforce fully qualified domain names only and reject URLs based on IPs. Default: `False`.
* `WHITELISTED_DESTINATIONS_FOR_URL_INPUT` - comma-separated list of allowed destinations for URL requests, for example `WHITELISTED_DESTINATIONS_FOR_URL_INPUT=192.168.0.15,some.site.com`. URLs pointing elsewhere are rejected.
* `BLACKLISTED_DESTINATIONS_FOR_URL_INPUT` - comma-separated list of forbidden destinations for URL requests.
* `ALLOW_LOADING_IMAGES_FROM_LOCAL_FILESYSTEM` - set to `False` to disable local filesystem access to images. Default: `True`.
* `ALLOW_URL_TO_NON_GLOBAL_ADDRESSES` - set to `False` to reject URLs whose host resolves to a non-global address (loopback, private/RFC1918, link-local and cloud metadata `169.254.169.254`, CGNAT, IPv6 ULA) and pin the connection to the validated IP so DNS rebinding cannot swap the target. Default: `True` (scheduled to change to `False` in Q4 2026).
* `VALIDATE_IMAGE_URL_REDIRECTS` - set to `True` to follow redirects one hop at a time and re-validate every hop URL (scheme, FQDN, allow-list, block-list, non-global address) instead of letting the client follow redirects blindly. Default: `False` (scheduled to change to `True` in Q4 2026).
* `MAX_IMAGE_URL_REDIRECTS` - hard cap on the number of redirect hops allowed when fetching a URL image, enforced regardless of `VALIDATE_IMAGE_URL_REDIRECTS`. Default: `30`.

See [Securing a Self-Hosted Server](/deployment/self-hosted/inference-server/configuration/security.md) for a fuller explanation of the SSRF controls and recommended configurations, and the [Inference CLI](https://docs.roboflow.com/reference/inference/inference-cli/server) docs for running the server with specific flags.