Cyber threat intelligence is an effective weapon in the ongoing battle to protect digital assets and infrastructure – especially when combined with AI. But AI is only as good as the data feeding it. Access to unique, underground sources is key.
Threat Intelligence offers tremendous value to people and companies. At the same time, its ability to address organizations’ cybersecurity needs and the benefits it offers vary by company, industry, and other factors. A common challenge with cyber threat intelligence (CTI) is that the data it produces can be vast and overwhelming, creating confusion and inefficiencies among security teams’ threat exposure management efforts. Additionally, organizations have different levels of security maturity, which can make access to and understanding of CTI data difficult.
Enter generative AI. Many cybersecurity companies – and more specifically, threat intelligence companies – are bringing generative AI to market to simplify threat intelligence and make it faster and easier to harness valuable insights from the vast pool of CTI data. But there is a fundamental issue with many of these AI offerings: the data they leverage is often limited, outdated, or contains inaccuracies, which then makes AI’s outputs faulty and unreliable.
Put simply, AI is only as good as the data that feeds it. To derive meaningful business value from a generative AI solution, the data it relies on must be credible, current, and relevant. Additionally, the intelligence that feeds AI must pull from a wide range of unique sources to ensure accuracy.
This article serves as a guide to finding the right CTI and generative AI combination to ensure the threat intelligence your team receives is accessible, understandable, and actionable, no matter what level of security maturity the user has. More information about the benefits of AI and CTI is available in our upcoming eBook, From AI to IQ: Transforming Cyber Defense with Generative AI.
images from Hacker News