# Fraud Orders

<figure><img src="/files/FVYLHoqFq6EgvYsoLlgi" alt=""><figcaption></figcaption></figure>

### 1. Orders Table

Columns include:

* **Last Access** → When the order was placed.
* **Order ID** → Unique order identifier.
* **Order Type** → Risk level: None, Low, Medium, High.
* **Visitor IP** → IP used to place the order.
* **Total Price** → Order value.
* **IP Score** → Reputation score for the IP.
* **Detection** → Traffic type (Proxy, VPN, etc.).
* **Order Score** → Fraud score calculated by system.
* **Action** → Apply enforcement to visitor IP.

***

### 2. Order Risk Types

* **None** → No risk detected.
* **Low risk** → Likely safe.
* **Medium risk** → Some suspicious signals, review before fulfillment.
* **High risk** → Strong indicators of fraud, do not fulfill without verification.

***

### 3. Detection Types

<figure><img src="/files/ftbiuaOyxGYIPDhr2ryG" alt=""><figcaption></figcaption></figure>

Same as in Visitors:

* **Clean** → No suspicious signals.
* **Proxy** → Using anonymous proxy.
* **VPN** → Browsing through a VPN.
* **Compromised** → Known compromised IP.
* **Scraper** → Automated scraping detected.
* **Tor** → Connected via TOR anonymity network.
* **Hosting** → IP belongs to hosting/cloud provider.

***

### 4. Filters & Search

* Filter by Date Range, Total Price, Detection, IP Score.
* Search by IP or Order ID.

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### 5. Actions (IP Blocking)

From the **Action** column, you can:

* **Block Visitor IP** → Adds the IP that placed the order to your **Blacklist** immediately. Future visits from this IP will be denied or redirected according to your rules.
* This prevents repeat fraud attempts from the same source.

👉 Currently, **Actions are limited to blocking visitor IPs**. Planned features will include **auto-cancel high risk orders** and **conditional checkout blocking**.

***

### Best Practices

* Always review **High Risk** orders → block the visitor IP if fraudulent.
* Place **Medium Risk** orders on hold for manual verification.
* Keep exporting fraud order logs for compliance and deeper analysis.

If you have any questions, feel free to contact us via **Crisp Chat** or email us at [support@mida-app.io](mailto:support@mida-app.io?subject=%5BMIDA%20Support%5D%20Question%20about%20Fraud%20Score\&body=Hi%20MIDA%20Team%2C%0A%0AI%20have%20a%20question%20about%20the%20Fraud%20Score%20feature.%20Please%20assist%20me%20with%20the%20following%3A%0A%0A-%20Shop%20URL%3A%20%0A-%20Issue%20details%3A%20%0A%0AThank%20you!%0A%0A%2D%20Your%20Name).


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