Cyberlytic Case Studies & Use Cases


  • Detects web injection attacks without the creation of firewall rules
  • Cuts through large volumes of data and immediately prioritises high-risk web attacks
  • Protects against critical data loss and increases the efficiency of IT resources
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Use Cases | Protection for RETAILERS with web applications



The retail industry has drastically exploded online as it is now a part of daily life for many people to make purchases on the web. Online credit/debit card security has come a long way and now retailers are focused on to making the purchasing experience as seamless as possible for customers. It is clear that threats have evolved too and retailers are an obvious target for hackers because of the valuable information they store and collect via the web, which usually includes: credit card details, personally identifiable information and shopping preferences for various marketing purposes. The retail industry came third for having the most web vulnerabilities in 2016, according to a report by White Hat Security, emphasising the need for better security practises industry-wide.

The new Global Data Protection Regulation is coming into place in May 2018, so compliance is a significant driver for retailers to ensure cybersecurity is at the top of the agenda. Companies are taking necessary steps to comply now, but having a security-centric approach is a step further than this and is essential for retailers to gain competitive advantage in a crowded marketplace. It is imperative for the industry to ensure they have the right processes and tools in place to ease the pain of inevitable attacks to their web applications. Response is equally important, in that intelligence and the ability to respond quickly and appropriately will make all the difference.


Cyberlytic has developed a revolutionary approach to detecting and preventing web-based attacks, such as SQL injection (SQLi), 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.

By cutting through the noise generated by millions of events, the Cyber Threat Profiler reduces incident response times from days to seconds, by targeting the most dangerous attacks. Our patented 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 injection attacks

Risk-based Prioritisation: Immediately cuts through large volumes of data and prioritises high-risk attacks targeting sensitive information

Protection and compliance: Dynamic risk-based reporting demonstrates web threat protection and supports compliance requirements

Other Case Studies

Our Work with the MoD

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Protecting an Automotive E-Commerce Website from Online Threats

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INSURANCE: Detecting and defending increasing cyber threats

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