industryopinion
Generative AI: a force for good or a force for evil?
Guy March, senior director of EMEA channels at Tenable discusses the role of generative AI in cybersecurity.
What attacks/threats have we already seen from threat actors harnessing the power of generative AI? There are a number of examples and methods by which generative AI can be leveraged maliciously. Generative AI, simply put, is a method by which a model builds relationships between words and when interacted with can predict what a response should be based on these relationships. It learns about artifacts from data and generates innovative new creations that are similar to, but don’t repeat, the original. When you look at code, from a generative AI perspective, it’s just
words. Looking at how that code has been exploited in the past and using that to find new zero-day vulnerabilities in other code sets becomes much easier. We have seen one example where a security researcher was able to get a bot running in the snapchat application to write in basic code that is similar to how ransomware locks a system down. We have also seen examples of phishing attacks becoming much more sophisticated and being able to easily evade the algorithms of anti-spam software.
How do we expect these attacks to morph in the coming months? Whilst AI can be used to automate more targeted and convincing attacks, the flaws these attacks target haven’t changed. That means the foundation to defending against any style of attack, be it AI or human powered, remains unchanged. What has changed is the rate at which the cat and mouse game is played. Attackers are going to be much more efficient in many aspects. But that doesn’t mean the odds are stacked in the attackers favour.
Defenders have access to the same efficiency gains. The value of generative AI, generally speaking, is its ability to make certain tasks much easier to perform and allows people to be more efficient in what they do. It’s up to security vendors to more easily enable the defenders through the technology they are using.
Can generative AI be used for good? There are a number of ways generative AI can be used for good. Speaking specifically from a cyber perspective, the biggest impact it will have is enabling security professionals to better interact with security data. Your typical security professional is not a data analyst. Maximising the value of the data you have is a very specific skill set that traditionally security professionals have not had.
16 | November/December 2023 Harnessing the power and speed of generative AI, such as Google
Virtex AI, OpenAI GPT-4, LangChain and many others, it is possible to return new intelligent information in minutes. This can be used by security professionals to make sense of the data they have and accelerate their ability to make informed decisions on how best to take action. That said, generative AI depends on a breadth and quality of data
to provide clear and accurate insights. If you have unique data then you’re going to have unique intelligence guiding decisions. It’s truly “garbage in, garbage out” — or “gold in, gold out” — depending on the source.
What part will MSPs play in ensuring customers understand AI and are harnessing its power correctly? You don’t have to spend much time researching security vendors before tripping over messaging around how their products have been improved with AI. Most vendors are investing significant resources into leveraging AI to solve foundational security problems. Harnessing the power of AI potentially enables security teams to work faster, search faster, analyse faster and ultimately make decisions faster. Making sense of it all can be daunting. Customers are looking to
their MSPs to decipher the polished marketing to really understand what exactly is being offered. They want strong counsel to understand what the solution is capable of, what they need it for, and what is unnecessary expense.
As defenders, with MSPs in the role of outsourced defenders, how can they leverage generative AI capabilities to automate the mundane and what are the benefits of doing so? AI has the potential to change how cybersecurity teams, including MSPs, search for patterns, explain what they’re finding in the simplest language possible, and help decide what actions to take that will reduce the customers cyber risk. MSPs are perfectly positioned to help their customers by feeding reliable intelligence into their data sets, drawing from a mix of multiple point solutions to aggregate this information and deliver strategic actions that will reduce cyber risks. It’s important to remember that, for now at least, while AI is
capable of quickly identifying and automating some actions that need to be taken it’s imperative that humans are the ones making critical decisions on where and when to act.
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