Cybersecurity

The Right Way to Improve CTI with AI (Hint: Here’s the Data)

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Artificial intelligence

Cyber ​​threat intelligence is an effective weapon in the ongoing battle to protect digital assets and infrastructure – especially when coupled with AI. But AI is only as good as the data that feeds it. Access to unique underground sources is key.

Threat Intelligence offers tremendous value to people and companies. At the same time, its ability to meet an organization’s cybersecurity needs and the benefits it offers vary by company, industry and other factors. A common challenge with cyberthreat intelligence (CTI) is that the data it generates can be overwhelming and redundant, creating confusion and inefficiency among security teams’ threat exposure management efforts. In addition, organizations have different levels of security maturity, which can make it difficult to access and understand CTI data.

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 leverage valuable insights from vast CTI datasets. But there’s an underlying problem with many of these AI offerings: the data they leverage is often limited, out of date, or contains inaccuracies, which then makes AI output corrupt and unreliable.

Simply put, AI is only as good as the data that feeds it. To derive meaningful business value from generative AI solutions, the data they rely on must be credible, current, and relevant. In addition, the intelligence that feeds AI must be drawn from a variety of unique sources to ensure accuracy.

This article serves as a guide to finding the right combination of CTI and generative AI to ensure the threat intelligence your team receives is accessible, understandable, and actionable, regardless of user’s level of security maturity. More information on 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 open-source AI solutions are only as good as the data they have access to, and most of the 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 on a deep web forum or on a dark web market, the response you receive will be either inaccurate or left blank, given the lack of access. to this intel.

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As mentioned above, unique data is critical when relying on generative AI for credible information and answers to a wide range of questions, from the most basic to the most critical. For example, a CISO wants to determine whether their organization is vulnerable to ransomware attacks, or how resilient they are to phishing attacks. They also want to know whether intellectual property is properly protected, and which groups of threat actors pose the greatest threat.

Since most CTI solutions don’t have access to underground resources on the deep and dark web, they can’t answer this question accurately – which means generative AI can’t answer this question either. But knowing the answers is critical to an organization’s ability to manage its threat exposure. In addition, appropriate answers must consider enterprise-specific attack surfaces and link 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 is our comprehensive CTI embedded in a new Attack Surface Management module introduced earlier this year, we’ve also added generative AI capabilities across our product in a solution called Cybersixgill IQ.

Using GPT models trained on Cybersixgill’s vast and unique repository of CTI threat contexts, combined with organization-specific attack surface context, Cybersixgill IQ effortlessly provides instant, accurate answers to seemingly immediate senior leadership threat exposure questions. With the help of Cybersixgill’s generative AI model, questions like “Does CVE XYZ affect my organization?” or “Where are our most vulnerable areas?” produce fast, accurate, and easy-to-understand responses.

Beyond the Chat: Quality Intelligence with Protection Against Misinformation

Most generative AI solutions only offer chat features, which can be useful in some cases, but don’t offer the level of actionable information you need to speed up important decision making. Instead, we’ve embedded AI across all Cybersixgill IQ solutions – from automated, human-readable intelligence analysis in items, to the generation of high-quality intelligence reports in real time, to assistant AI analysts that follow your work and provide important insights in what context or activity. whatever you do.

Cybersixgill IQ delivers business value by intelligently interpreting customer requests and delivering data and insights that are precisely aligned to the required use case in the format they need. For example, the CEO may request a brief threat overview summary, or the detection and response team may require a comprehensive forensic incident report – or, for an MSSP, a vulnerability exposure analysis for each customer may be required. After all, Cybersixgill IQ delivers.

Ready-made LLMs like GPT and Bard also sometimes produce “fake” content or hallucinations. Cybersixgill IQ was designed to solve this problem in several ways. For example, our model is designed to query data using scoped data access and rapid engineering (rapid engineering is the process of designing and refining leads to achieve a specific goal, such as generating content for a marketing campaign or identifying relevant information in a social media post.) In addition, we exclude answers when AI is unsure about the outcome, and offer quick feedback with users to detect and mitigate erroneous AI-generated content.

Data Privacy Issues

Another area of ​​concern for AI is data privacy, as the way existing AI solutions address user data privacy protection is inconsistent. But it is a critical need that must be taken seriously when choosing a generative AI tool. At Cybersixgill, we have implemented measures to ensure that our customers and their data 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 in place to ensure the security and privacy of your data, such as minimizing data transfer, masking sensitive data, only sending metadata, and leveraging local processing. As we enter a new era of AI, we deploy our solutions with a careful security-first approach and do not transmit customer data to services like ChatGPT.

Redefining CTI through our History with AI

Not all AI solutions are the same, and not all CTI vendors have solutions rooted in AI. Cybersixgill is always investing in AI and our automated processing and enrichment of data. We’ve been implementing machine learning and deep learning over the last few years, as evidenced by products like DVE Intelligence, which leverages real-time NLP-based underground chat analysis to predict potential CVE exploits in the near future.

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

To learn more, order a copy of our latest 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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