The Right Way to Enhance CTI with AI (Hint: It’s the Data)

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 But there is a fundamental issue with many of these AI offerings: the data they leverage is often limited, outdated, or contains inaccuracies, which then makes AI’s outputs faulty and unreliable.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 latest eBook, From AI to IQ: Transforming Cyber Defense with Generative AI.

The Importance of Deep, Dark Web Sources and Attack Surface Context#

Commercially available and open-source AI solutions are only as good as the data they access, and most available solutions have access to a limited set of sources. For example, if you ask chatGPT (or a ChatGPT-based product) a question about something that happened in a deep web forum or on a dark web market, the response you receive will either be inaccurate or left blank, given its lack of access to this intel.

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As stated above, unique data is critical when relying on generative AI for credible information and answers to a range of questions, from the most basic to the most critical. For example, CISOs want to determine if their organization is susceptible to a ransomware attack, or how resilient they are against phishing attacks. They also want to know if intellectual property is properly safeguarded, and which threat actor groups pose the greatest threat.

Because most CTI solutions don’t have access to underground sources on the deep and dark web, they can’t answer these questions accurately – which means the generative AI also can’t answer these questions. But knowing the answers is paramount to an organization’s ability to manage its threat exposure. Additionally, the corresponding answers must take into account the company’s specific attack surface and correlate the information with threat intelligence that provides relevant context.

Enter Cybersixgill — the missing link that unlocks the true potential of AI in helping organizations manage their threat exposure. Not only has our comprehensive CTI been embedded within the new Attack Surface Management module that was introduced earlier this year, we have also added generative AI capabilities throughout our products in a solution called Cybersixgill IQ.

By utilizing GPT models trained on Cybersixgill’s vast and unique repository of CTI threat context, combined with organization-specific attack surface context, Cybersixgill IQ effortlessly provides instantaneous and accurate answers to those seemingly straightforward senior leadership threat exposure questions. With the aid of Cybersixgill’s generative AI models, inquiries such as “Is CVE XYZ impacting my organization?” or “Where are our most vulnerable areas?” yield immediate, accurate and easy to understand responses.

Beyond Chat: Quality Intelligence with Safeguards Against Misinformation#

Most generative AI solutions simply offer a chat feature, which can be helpful in some instances but doesn’t offer the level of actionable information you need to hasten critical decision-making. In contrast, we’ve embedded AI across the Cybersixgill IQ solution – from human-readable, automated analysis of intelligence in items, to on-the-fly generation of high-quality intelligence reports, to an AI analyst assistant that follows your work and provides vital insights in whichever context or activity you’re in.

Cybersixgill IQ delivers business value by intelligently interpreting customer inquiries and delivering the data and insights that precisely align with their required use cases in the format they need. For example, the CEO might demand a concise threat overview summary, or detection and response teams may need a comprehensive forensic incident report – or, for MSSPs, a vulnerability exposure analysis for each customer may be required. In any case, Cybersixgill IQ delivers.

Off-the-shelf LLMs like GPT and Bard may also occasionally generate “fake” or hallucinated content. Cybersixgill IQ is designed to mitigate this issue in several ways. For example, our model is designed to query the data using scoped data access and prompt engineering (prompt engineering is the process of designing and refining prompts to achieve specific goals, such as generating content for marketing campaigns or identifying relevant information in social media posts.) Additionally, we exclude answers if the AI is unsure about the result, and offer fast feedback loops with users to detect and mitigate incorrect AI-generated content.

Data Privacy Matters#

Another area of concern with AI is data privacy, as the way existing AI solutions address the protection of users’ data privacy are inconsistent. Yet this is a critical need that should be taken seriously when choosing a generative AI tool. At Cybersixgill, we have implemented measures to ensure that our customers and their data’s privacy and security are upheld. Generative AI is a promising field with exciting potential. In addition to the Data Processing Addendum (DPA), we have further measures to ensure your data security and privacy, such as minimizing data transfer, masking sensitive data, only sending metadata, and utilizing local processing. As we enter the new age of AI, we’re implementing our solutions with a cautious, security-first approach and do not send customer data to services like ChatGPT.

Redefining CTI through our History with AI#

Not all AI solutions are alike, and not all CTI vendors have solutions that are rooted in AI. Cybersixgill has always invested in AI and the automated processing and enrichment of our data. We’ve implemented machine learning and deep learning for the past several years, as evidenced by products such as DVE Intelligence, which leverages real-time NLP-driven analysis of underground chatter to predict a CVE’s likelihood of exploitation in the near term.

Cybersixgill’s generative AI, combined with our ASM module, is the long-awaited solution that finally unravels the true potential of threat exposure management, providing organizations with actionable insights, simplifying complex topics and empowering them to make informed decisions based on a comprehensive understanding of their threat landscape.

To learn more, reserve your copy of our recent eBook, From AI to IQ: Transforming Cyber Defense with Generative AI.

You can also get a live demo of Cybersixgill IQ here.

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