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Use Case

AI-driven cybersecurity threat detection

Generative AI models can play a vital role in AI-driven cybersecurity threat detection. For instance, Language Models like GPT-3 can be used to analyze patterns in network traffic and detect anomalies in behavior. These anomalies can be a sign of a potential threat. Large language models can also be trained with datasets containing cybersecurity threat information, allowing the AI to learn and predict new threats.

Image generators can be implemented to analyze visual data, capturing suspicious activities in high-security areas or identifying modifications in security tokens or barcodes. The AI model can generate a distorted version of the image and compare it to the original, a discrepancy will flag a potential security issue.

Lastly, with phishing scams becoming more intelligent, AIs can be programmed to generate fake phishing emails, test the system’s strength, and improve its ability to detect real threats.

How to build with Clevis

Text Input

Enter the URL of the website to analyze

Prompt ChatGPT

Prompt ChatGPT to provide an overview of potential threats based on the website URL

HTTP Request

Fetch the latest threat intelligence data from a cybersecurity API

Prompt ChatGPT

Prompt ChatGPT to analyze the fetched threat intelligence data

Display Output

Display the summarized analysis of potential threats to the user

This is an example of an AI-Based Cybersecurity Threat Detection app that you can build using the tool, Clevis. This application leverages different capabilities of ChatGPT and OpenAI to monitor and analyze potential digital security threats for websites.

The app functions in a series of steps. The process begins with user input where the URL of the website to be analyzed is entered. This input is provided to ChatGPT which in turn generates a basic overview of potential threats that could be associated with the website.

Then an HTTP request is sent to fetch the latest threat intelligence data from a reliable cybersecurity API. This real-time feed further improves the detection capabilities of the application by providing the most up-to-date threat information available.

This retrieved data is then sent back to ChatGPT for thorough analysis. After analyzing this data, ChatGPT provides a comprehensive summary of potential threats. The final result is then displayed to the user, helping them understand any possible risks associated with the entered URL.

Clevis provides a powerful and versatile platform to build such AI-driven applications within the cybersecurity domain and beyond.

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