04 Jun AI is now a Powerhouse in Cybersecurity Attacks
The “miracle solution” to all of our tech woes has instead transformed into a cybersecurity nightmare. A tried and tested rule in the IT domain is this: what benefits us benefits them, “them” an umbrella term for threat actors, malicious third parties, and cyber-criminal gangs. Toolsets released into the wild to benefit a user or business can be altered to boost, automate, and strengthen the capabilities of a threat entity.
At the center of all this is AI, the machine-learning tool that has “captivated” industries across the spectrum. The tech industry shifts and gravitates towards “the next big thing,” a romanticized concept regarding technology that can singlehandedly change technology forever. AI fits this profile, at least in the sense virtually every professional entity wants it, uses it, or blends it into their workflows. Built on LLMs, AI finds itself on most common website platforms. For instance, even performing a Google search will initially yield a quick, summarized AI-overview of the search subject.
Its ability to automate tasks and perform mundane duties has, naturally, attracted industries to rapidly deploy it in their service models. That same level of automation and generation, however, also attracts malicious actors who readily use it in modern-day cyber-attacks.
Malicious AI-Assisted Attacks
AI has stratified attacks at an unprecedented pace. For example, phishing and social manipulation is easier for malicious third parties to engage with, given the ability to quickly generate falsified media, faces, images, and even voices. AI toolsets can also search, identify, and collect enormous pools of person information, which is then used for massive phishing attacks.
Since 2024 and onward, AI technology has evolved, and so too the attack capabilities of hackers. Each year has seen an exponential increase in the volume of attack, and it’s only expected to rise as AI toolsets grow more advanced. Furthermore, AI toolsets have “democratized” cyber threats. The barrier of entry is virtually nonexistent. If an individual has access to an AI generative tool, they can launch an elementary form of attack without the need for comprehensive IT, cybersecurity, or programming skills. Additionally, the ease at which attackers can locate social information and transform it into phishing attacks (or similar) creates immense scalability. In other words, they’re able to outpace defense mechanisms designed to catch and prevent AI-centric cyberattacks.
Generating malicious code or developing media for a phishing attack is easy. Automating and implementing said attack methods on en masse is, today, even easier.
It’s not an overstatement to say the sheer volume of AI-powered attacks can, and will, overwhelm businesses without preparation. One harrowing discovery, for instance, found that since 2020, the exploit time, or TTE (time to exploit) shrank to just 44 days. In other words, with AI assisted powerhouses, single threat actors can compromise systems in a concerningly small-time frame. In contrast, in 2020, estimated exploit times typically required 700+ days to discover and compromise exploits in a network.
Defending Against the Deluge
There’s no easy way to put it: AI-driven attacks are escalating and show no sign of slowing down. Their ability to manifest exploits, phishing campaigns, and even malicious code is staggering. More than ever, professional industries need to start preparing now.
Doing so can be challenging. However, good defense starts with identifying threat surfaces and mitigating potential intrusions that can occur from them. There are a few ways you can accomplish this.
Assess Your Third-Party Vendors and Security
Even if your own cybersecurity and defense infrastructure is sound, malicious actors can still find a way in via third-party vendors. Usually, that’s because while you may have stringent security policies in place, a utilized vendor has different defense methods, oversights, and policies. These areas are potentially creating a perfect opening for attackers.
You need to verify with all your vendors what their current security posture is on things like exploits, phishing, vulnerabilities, and AI-generated attack awareness. That’s doubly so if your business utilizes third-party vendor support with AI service models. Any of these vendors should be willing to provide succinct explanations of their approach towards threat actors and AI-assisted cyberattacks.
Review AI Governance
Next, take some time to review the governing logistics of your cybersecurity model. How are AI tools part of your workflows? Where are they used? What kind of information is accessed? Often, to perform tasks, AI models require deeper access to a company’s data pools. Therefore, they are in proximity to information that staff members are not, thus creating massive risks to your internal security.
Also, if your enterprise is deeply entwined with AI toolsets, attackers can poison the data models LLMs rely on, rendering them ineffective. There are limited, if any, regulatory guardrails regarding AI models for internal use, so it’s up to your organization to establish them.
Invest in Cybersecurity Staff
While leveraging AI tools to automate redundant tasks and address low-level problems, it is not a succinct replacement for complex cybersecurity tasks. Considering the importance of cybersecurity and the diminishing pools of available experts, investing in the right talent, education, and infrastructure for cybersecurity is vital. Remember, the barrier of entry for hacker hopefuls is virtually nonexistent.
Conclusion
As AI LLM models advance, the abilities of hackers will scale in tandem. Therefore, you need to prepare accordingly and understand the dangers presented by AI charged attacks. Taking appropriate precautions within your infrastructure can better prepare you.
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