Security Risks of Artificial Intelligence: Examples and Ways of Defense

The issue of AI and cyber security risks has become more severe. Amazon’s Chief Information Security Officer, CJ Moses, revealed in a WSJ interview that they now face billions of cyberattack attempts, averaging 750 million daily (up from 100 million just months ago).

Moses confirmed that generative AI is fueling this surge, empowering even non-technical people to execute sophisticated attacks and creating highly convincing phishing attempts. For all its benefits, Gen AI has undeniably handed new superpowers to cybercriminals.

That’s why, in our new blog post, we’ve decided to shed light on the most disturbing AI-powered security threats and ways to deal with them. So, you’ll gain the following key takeaways:

• The danger behind AI: phishing and social engineering, attack optimization, etc.
• Real-world examples of risks associated with AI and Machine Learning Models, as well as AI cyberattacks and their consequences.
• How to deal with security risks of artificial intelligence and how to prevent these attacks.

AI Optimize and Simplify Attacks Even for Unexperienced Hackers

Out of the billions of people on this planet, only a select few truly know how to perform sophisticated cyberattacks. But now, with generative AI on the rise, that elite knowledge is being handed out to everyone like candy.

Giants like Amazon are witnessing a boom in new threat actors and cyber attacks. Although these people may lack top-notch skills, they can still use AI to supercharge their attacks, making them faster, bigger, and more scalable. The flood of adversaries is set to grow exponentially, and we’re only seeing the tip of the iceberg.

AI and Machine Learning misuse: examples

These days, you can ask an AI model to whip up a step-by-step guide on exploiting a critical vulnerability.

As Anton Lukianchenko said, most models have built-in guardrails, but just one quick Google search away is a slew of uncensored models that will eagerly share with you a recipe for any illegal substance known to man, instructions to build a weapon of mass destruction, or, more relevant to our conversation, a ready and working piece of malware and instructions on how to deploy it.

Tasks like decompiling vulnerabilities, reverse engineering, or creating black-market exploits used to take days or even weeks in the past. And what about now? They can be done in mere hours or even minutes. AI not only speeds up cyberattacks but makes them sharper and more intricate.

Another headache is AI-powered hacking tools. These tools make it easy for even unskilled hackers to launch large, complex attacks, adding fuel to an already-flaming fire.

AI-powered attacks

AI-powered tools find weak spots, test new attack routes, and pull it all off with lightning-fast precision. On the technical side, AI powers and scales attacks like:

• Designing advanced phishing scams by studying communication patterns.
• Identifying software weaknesses through automated code analysis.
• Producing deepfake videos or disinformation to target individuals or organizations.

While AI’s role in traditional DDoS attacks is limited since these rely more on quantity than complexity, it could still make them slicker by analyzing traffic patterns and dodging detection systems. As Lukianchenko puts it, “AI might not beef up DDoS attacks much, but it can surely make them smarter.”

Even so-called “script kiddies” – amateur hackers – are using AI to level up their game. The result? A flood of attacks that are not only more frequent but also harder to defend against. With AI in the mix, it’s clear the cat’s out of the bag, and we’re all scrambling to keep up.

Ihor Sasovets, Lead Security Engineer at TechMagic, experienced SDET engineer:

I would say that one of the most important advantages that AI grants to attackers is an opportunity to speed up offensive actions at different stages of exploitation and scale conducted attacks. It can be a significant challenge for organizations that do not have enough capabilities to implement security processes and perform constant monitoring in order to detect possible threats in the early stages.

But, on the other hand, AI also helps to increase blue team capabilities, so it’s like a constant cat-and-mouse game that becomes more sophisticated as AI evolves.

AI-Powered Phishing and Social Engineering

This issue isn’t new, as phishing was a threat long before the AI era. But now, when malicious actors actively use AI to create phishing scams and spread false information, the problem becomes much more severe.

These attacks often act as the gateway for hackers to break into systems, steal sensitive data, explore networks, gain higher access levels, and cause significant damage. And thanks to AI, they are now more scalable and effective than ever.

Moreover, generative AI has taken these risks to a whole new level. How? You can receive incredibly realistic, personalized messages that even cautious people might fall for. And it happened really fast.

On top of that, deepfake tech makes things worse by producing fake audio or video that looks and sounds like someone you trust, making targeted phishing attempts even more convincing.

Anton Lukianchenko, Senior Web Engineer, AI advocate, coach, and speaker, adds on generative AI security risks:

Imagine your boss texting you to transfer 10000 dollars into a bank account for some services provided to your company. You obviously become suspicious, and decide to be a responsible employee and give them a video call to verify this is not a phishing attempt.

The boss picks up. Their video is a bit more grainy than usual, but the voice checks out, and the video seems real as well, so you do what’s asked for, just to find out a couple of hours later that you have been a victim of an elaborate scam using an automated phishing email campaign followed up by a deepfake video, cloned voice and your SEO’s compromised zoom account that he used a Password123$ for…

Real-world case

An Ontario man was scammed out of $11,000 after falling for a deepfake video featuring fake endorsements from Justin Trudeau and Elon Musk. The convincing video led him to invest small amounts at first, which appeared to double, prompting him to put in more money until his funds were "blocked" with a demand for an additional $6,000 to release them.

Security Risks of Integrating Generative AI into Services

When you integrate generative AI into services like chat interfaces, it can create significant security challenges. Providers must assess these risks carefully, especially when systems are exposed to unpredictable user interactions. The primary concerns boil down to input and output risks.

Input AI security risk

AI systems can be exploited by regular users and malicious actors. Cybercriminals might craft adversarial prompts, tricky inputs designed to manipulate the AI into generating harmful or inappropriate outputs. Maintaining system integrity might be a critical challenge.

Platforms that adapt and learn from user interactions face an additional layer of risk. A system that absorbs large amounts of politically or ethically skewed data may inadvertently produce biased or damaging outputs. Such distortions threaten the trust users place in these platforms and the efficacy of the service itself.

Output AI security vulnerabilities

Here, it all comes down to adversarial prompts that lead to several critical issues.

Information leakage

Even in the most secure systems, AI might unintentionally expose sensitive details about other users or internal system data.

Real-world case

In May 2023, Samsung employees accidentally leaked confidential data when using ChatGPT to review internal code and documents. The company decided to ban the use of gen AI tools to prevent future breaches.

In January 2023, Amazon cautioned staff members against sharing private information with ChatGPT after observing several cases in which the LLM's responses closely matched private company data, which was most likely used as training data. Walter Haydock's investigation estimated the incident's losses at more than $1 million.

Inappropriate responses

There is the risk of AI generating content that is not only inaccurate or biased but also potentially harmful. This includes discriminatory remarks, violent incitement, or even infringement of intellectual property, all of which can erode trust and create legal headaches.

Real-world case

In February 2024, an Air Canada customer was able to manipulate the airline's AI chatbot to receive a refund that was higher than anticipated. The chatbot misunderstood the user's request, resulting in the company losing more money than intended.

Unintended system behavior

When AI outputs influence other interconnected systems, unforeseen or dangerous actions may occur. This could escalate the risk of larger-scale harm, from reputational damage to real-world consequences.

Real-world  case

In February 2023, shortly after introducing its Bard AI, Google faced credibility problems. The chatbot gave false information during a James Webb Space Telescope demonstration, instantly plunging Alphabet's stock price and wiping out $100 billion in the company's worth.

Without proper checks, AI systems could reinforce existing biases or even create new vulnerabilities. This means that your developers and service providers must monitor the situation closely, update their algorithms regularly, and improve security to stay ahead of risks.

How To Protect Your Business From Security Risks of AI

Our security experts are confident that AI is an incredible assistant, and we can mitigate security risks with AI. A simple example is using AI for anomaly detection. But as the saying goes, “with great power comes great responsibility.”

It’s crucial to approach AI-generated information and code with care, ensuring we don’t accidentally introduce security vulnerabilities into our systems or organizations. One key piece of advice we’d like to share is to be cautious with the data you share with AI or large language model (LLM) systems. Many vendors use this data for training, which creates a risk of information leaks that could have serious consequences in certain scenarios.

Strategies to stay protected against AI cyber security risks

From our point of view, the best place to start is with the basics, then gradually build up your defenses step by step. A “defense-in-depth” approach works well. It helps cover a wide range of risks and raises awareness among employees because, let’s face it, people are often the weakest link in an organization’s security.

Another essential element is continuously monitoring your assets and implementing automated responses wherever possible, especially if your organization doesn’t have a dedicated SOC or incident response team.

Tools are an entirely new topic. The tools you choose will depend on your specific needs, requirements, and capabilities. There’s no one-size-fits-all solution, but tailoring your approach to your current situation is always the smartest move.

Traditional cybersecurity methods, tools, techniques

From my perspective, current approaches like “defense in depth” will remain valid because you cannot just easily move from a low level of awareness to an advanced level. – Ihor Sasovets said.

There is also no silver bullet that can protect you from all types of attacks. But, AI can help us to scale and speed up detection and response processes, as well as assist in doing penetration tests and vulnerability assessments and uncover vulnerabilities before the attackers are able to exploit them. One of the examples is the use of AI-powered tools and platforms for conducting Security Awareness Training and Phishing Simulation.

Education in preventing AI security issues

With phishing becoming more sophisticated than ever, education is even more important for dealing with AI security threats. Your employees must stay alert and diligent in following instructions, opening email links, and so on.

How to achieve this? Again – conducting Security Awareness Training and Phishing Simulation. Our security experts can work with your employees and adjust your security controls to specific threats. Check out our Security Training capabilities.

Stay up to date

Legacy systems are a prime target for cybercriminals. First, they lack support for modern technologies and cybersecurity tools, which makes them totally defenseless against the advanced security risks of Artificial Intelligence.

Secondly, these systems inherently contain numerous security gaps and vulnerabilities that attackers actively exploit. Additionally, they are difficult to maintain and secure.

Therefore, it’s crucial to update your systems and software in time. This is especially important in the healthcare sector, where protecting sensitive patient data is a top priority.

Work with experts

No one has as much expertise in dealing with artificial intelligence security risks as professional cybersecurity experts. In recent years, AI has become their assistant and a serious headache at the same time. That is why they know the smallest details and know how to build a protection system, taking into account the nuances.

It can include limiting AI behavior, implementing strict checks, conducting thorough vulnerability assessments, monitoring suspicious activity, etc. If you use all the techniques at random, you will spend a lot of money, but this does not guarantee you a result. It is better to ask for help and find a reliable cybersecurity consulting services provider.

Wrapping Up: Security Issues With AI Are Severe but Controllable

AI security concerns are undoubtedly severe, but they’re far from uncontrollable. The key lies in adopting proactive, layered strategies that adapt to emerging threats.

Whether your security team is working on the cloud or on local systems, you must consider timely updates for all your systems and processes. Every part of your system should reflect modern risks and be able to accommodate them. Legacy systems often leave vulnerabilities that attackers can exploit, so be attentive.

Collaboration is another powerful tool in combating risks of Artificial Intelligence in cyber security. Partnering with industry experts, especially in strongly regulated sectors like healthcare and finance, makes your security initiatives much more successful.

What is equally important is embedding a security-first mindset across your organization. Security must be treated as a foundational component of strategy, baked into planning and execution phases rather than an afterthought. Continuous maintenance and simplification of security processes go a long way in reducing vulnerabilities.

Plan ahead. Be active. Work with experts. Contact us today, and let’s discuss how we can defend you from AI and security issues.

FAQ

1. What are the main AI-powered risks?

   AI in cybersecurity presents several risks, including data manipulation and breaches, adversarial attacks, and data poisoning. These risks arise from AI's ability to process and manipulate large volumes of sensitive data, which makes it a target for malicious actors.

2. How can businesses protect themselves from AI-powered cyberattacks?

   There are a lot of options, starting with being attentive to training data and ending with building comprehensive data security strategies. Businesses can strengthen their protection by implementing strong access controls, robust security measures, and AI risk mitigation plans, conducting regular security assessments, and using AI-powered security tools for continuous monitoring and threat detection. But the best way to stay secure is to collaborate with cybersecurity experts, who can assess your security posture and create proper security incident handling plans.

3. What role does generative AI play in cyber threats?

   Generative AI can create convincing phishing scams and deepfake content, as well as create a lot of troubles with input data and conduct data poisoning attacks. Moreover, it enables even inexperienced hackers to optimize and scale their attacks, posing significant challenges to cybersecurity defenses.

4. How do adversarial attacks exploit AI systems?

   Adversarial attacks involve preparing inputs designed to manipulate AI model behavior. They cause the production of incorrect or harmful outputs. Such attacks can compromise the integrity of your AI systems, and it's not far from security incidents and data breaches.

5. What measures can organizations take to mitigate AI security risks?

   Organizations can mitigate the security risks of Artificial Intelligence by embedding a security-first mindset, updating legacy systems, and investing in AI-driven security solutions. Regular training and awareness programs can also help staff promptly recognize and respond to potential threats effectively.