FortiWeb Bot Protection Demo | Web Application Firewall

### Overview This demonstration video highlights FortiWeb's bot defense and bot mitigation capabilities, specifically focusing on safeguarding e-commerce websites against transaction fraud executed by retail bots.

### Key Topics - **Major Web Application Use Cases**: FortiWeb covers five primary use cases: web application security, bot defense, regulatory compliance, protecting internet APIs, and SOC operations. - **Retail Bot Threats**: Attackers deploy retail bots to automate account registration, account login, profile submission, adding items to shopping carts, and final checkout. The malicious goal behind these automated retail bots is often profiting by reselling products while preventing legitimate shoppers from purchasing goods. - **FortiWeb Bot Mitigation**: Configuring and enabling bot defense stops automated purchase workflows and blocks bot transactions.

### Technical Details - **Biometric-Based Detection**: FortiWeb checks client events, such as touchscreen, mouse, and keyboard interactions, to distinguish whether an incoming web request originates from a human or an automated bot. - **Policy Configuration**: To implement bot mitigation, the biometric-based detection is enabled, added into a bot mitigation policy, and then associated with the web protection profile inside the server policy. - **Attack Blocking and Verification**: When the retail bot attempts the automated checkout sequence after protection is enabled, FortiWeb successfully blocks the purchase attempt, which can be verified and reviewed directly within FortiWeb's attack logs. - **Detection Techniques**: In addition to biometrics, FortiWeb defends against automated threats using IP reputation, signatures, traffic thresholds, analysis of keyboard and mouse interactions, bot deception, and machine learning.

### Takeaways Automated retail bots can rapidly disrupt commerce by monopolizing inventory and executing fraudulent transactions. FortiWeb effectively mitigates bot-driven attacks by layering multiple detection techniques—ranging from biometric and behavioral tracking to signatures and machine learning—enabling administrators to monitor threats via attack logs and preserve service availability for legitimate users.