CQAI
Automates the detection and mitigation of malicious bot attacks targeting your API and web applications with the industry’s most scalable, ML-based behavioral analytics engine.
Application Source Profiling
Automated ML-based profiling of incoming requests to validate that the application sources – the browser or mobile application are genuine. A common attack is to spoof the browser, user agent or the mobile application itself. Read the CQAI Tech Brief.
Credential Stuffing Detection
CQAI detects potential credential stuffing by matching user credentials against known data breaches. Read the CQAI Tech Brief.
Source IP Reputation Analysis
Evaluation of client IP address against the millions of IP addresses that are commercially available from a range of Bulletproof Proxy vendors. Attackers will use these proxy services to mask their identity and location.
Source Tools Profiling
Attackers will create and monetize predefined attack configurations to simplify and monetize their attack techniques. This CQAI technique compares discovered attack characteristics with those found in commercially available toolkit configurations.
Behavioral Fingerprinting
ML-based behavioral analytics to detect evasive techniques often missed by client-based JS and SDK techniques. Behavioral profiles are combined with the user, network, organization, and application sources to result in unique fingerprints that identify the particular class of traffic.
Rule Validation and Risk Scoring
Risk scoring by analyzing behavioral profiles against more than 150 predefined and custom automation indicators. Findings can be translated into Bot Defense or App Firewall policies. Learn more in the CQAI Tech Brief.
