Cyberlytic

Intelligent web application security that applies cognitive machine learning & risk anlytics to detect, prioritize & prevent web attacks.

Cyberlytic has developed a revolutionary approach to detecting and preventing web-based attacks, such as SQL injection(SQLia) and cross-site scripting (XSS).  Our software uses machine learning to classify attack data, identify threat patterns and detect anomalies.  By analysing web server traffic in real-time, our software detects and immediately determines the sophistication, capability and effectiveness of each attack.  This information is translated into a risk score to prioritise incident response or initiate an automated response with our Defender product.    Our classification approach is far more effective at identifying attacks than traditional signature-based security solutions and adapts to new or evolving threats without requiring any manual intervention.   Advanced Detection: Machine learning classifies web traffic based on threat characteristics, to effectively detect web-based attacks.   Risk-based Prioritisation: Each attack is prioritised based on the risk it poses to the organisation. Dynamic reporting presents a risk-based summary of malicious activity.   Intelligent Prevention: Just the malicious content is stripped from an attack, preventing it reaching the target application. The attacker will only see a normal server response and will remain unaware that he has been detected.