In an era of unprecedented technological advancement, the adoption of AI continues to increase. However, with the proliferation of this powerful technology, a dark side is emerging. Increasingly, malicious attackers use their AI to enhance every stage of their attacks. Cybercriminals use AI to support a variety of malicious activities, from bypassing algorithms that detect social engineering to imitating human behavior with activities such as AI voice spoofing and other deepfakes creation doing. Among these sophisticated tactics, attackers are also relying on generative AI to level up their efforts, using large-scale language models to create more believable phishing and spear-phishing campaigns. , collecting sensitive data that could be used for malicious purposes.
Defending against adversaries requires a proactive approach, especially when adopting new technologies that make attacks easier and faster. Defenders must not only understand the potential dangers of the use of AI and ML among threat actors, but also leverage its potential to combat this new age of cybercrime. In the fight against the bad guys, we have to fight even more with fire.
AI and generative AI will change the threat landscape
Cyber ​​attackers are constantly increasing the sophistication of their attacks. The threat landscape is rapidly evolving, from new attack types to increasingly damaging attacks. For example, the average time between an attacker first infiltrating a network and being discovered is approximately six months. These developments pose serious risks. New risks also arise as organizations undergo digital transformation.
AI, especially generative AI, poses additional risks. AI technology allows malware campaigns to develop dynamic attack scenarios, such as spear phishing, using different combinations of tactics, especially defense evasion tactics, directed at an organization's systems.
The ML models used by attackers allow them to better predict weak passwords, and the use of chatbots and deepfakes allows them to create eerie, eerily similar images of a “CEO” convincingly approaching a junior employee. impersonate a person or organization in a very realistic way.
Attackers are manipulating generated AI to create reconnaissance tools that can retrieve users' chat history and personally identifiable information such as names, email addresses, and credit card details.
This is not a complete list of AI's potential for cybercrime. Rather, this is a sample of what is currently possible. As bad actors continue to innovate, many new threats are sure to emerge.
fight against threats
To protect against such attacks, organizations must incorporate automation, AI, and machine learning into their defense equation. It is important to understand the different capabilities of these technologies and understand that they are all necessary.
Let's start by thinking about automation. Consider a threat feed that contains threat intelligence and active policies. Automation helps process the required amount of discoveries and policies quickly, reduces response times, and separates day-to-day tasks from her SOC analyst to focus on areas where analytical skills can be applied in ways that machines cannot. play an important role. For example, organizations can start with orchestration and what-if scenarios in analytics tools like SIEM and SOAR and gradually add automated capabilities.
Security teams use AI and ML against unknown threats. ML is the learning component, while AI is the practical component. Each application may use different machine learning models. ML for zero-day malware has nothing to do with machine learning for web threats.
Organizations need AI and ML capabilities to defend against a variety of attack vectors. Applying AI and ML significantly reduces risk. Additionally, the cost of the OpEx model is reduced because there is no need to hire more people to solve the problem.
A key initial use case is implementing AI-powered endpoint technologies like EDR to gain complete visibility into activity. While it is beneficial to employ solutions that use AI and ML models to detect known and unknown threats, organizations can differentiate themselves by using AI for rapid security decision-making. AI is not a panacea, but it can improve cybersecurity at scale by giving organizations the agility they need to respond to an ever-changing threat environment.
AI technology provides a powerful way to defend against spear phishing and other malware threats by learning the patterns of these attacks. Organizations should consider endpoint and sandbox solutions with AI technology as a first step.
Defenders may have an advantage
Unusual in the world of cybersecurity, AI is one area where security professionals are already emerging. AI tools are now available with increasingly sophisticated capabilities to thwart sophisticated attacks. For example, AI-powered network detection and response (NDR) detects indicators of advanced cyberattacks and takes over intensive human analysis capabilities through deep neural networks to identify compromised users and agentless devices. Can be identified.
Another new offensive security project is known as AutoGPT. This is an open source project aimed at automating GPT-4 and has the potential to be a useful tool for cybersecurity. Examine a problem, break it down into smaller components, decide what to do, decide how to perform each step, and then take action, including process improvements (based on user input) and with or without consent). ML models that power these tools have the potential to assist defenders in detecting things like zero-day threats and malware. Currently, these tools must rely on proven attack strategies that have proven effectiveness in order to produce good results, but progress continues.
Please put out the fire
As attackers increasingly use AI, defenders will need to not only follow suit, but also stay ahead and put out more attacks using their technology in both defense and offense. To combat the evolving threat landscape, organizations must incorporate automation, AI, and machine learning into their cybersecurity strategies. By using AI to make decisions, obtain information, and explore new offensive security tools, defenders can counter AI-driven attacks and protect digital assets in an increasingly complex threat environment. You can strengthen your ability to