AI and Data Breaches: How Artificial Intelligence is Fueling Cybercr
Technology companies have unleashed powerful artificial intelligence solutions that collect massive amounts of data. While some of these tools make life easier and more enjoyable, they blur the lines between legal data collection and privacy invasion, raising significant legal issues.
AI holds immense promise in many aspects of society and our daily lives, but it also presents a serious risk when it is exploited by cybercriminals in data breaches. If you believe an AI system has unlawfully invaded your privacy or stolen your personal data, you may be entitled to compensation.
How Does AI Fuel Cybercrime in Data Breaches?
In this digital age, online security and personal privacy have never been more at risk thanks to data breaches carried out by highly skilled cybercriminals who are expanding their capabilities with AI.
In the past, hackers relied on complex code and brute-force attacks to steal data and infiltrate systems. Today, AI-powered cybercrime is more sophisticated and scalable because AI systems can quickly learn, adapt, and evolve, making it challenging for victims to detect and prevent attacks in numerous ways.
Automation of Attack Processes
In the past, cyberattacks required ongoing human involvement at each step. AI now allows cybercriminals to automate various aspects of a cyberattack, such as data scraping, phishing, and brute force attacks. This makes it easier for them to launch large-scale attacks in a fraction of the time it would take to do so manually.
Enhanced Targeting Capabilities
To identify targets and weaknesses in systems, AI can quickly analyze massive amounts of data, making cybercriminals more effective at exploiting organizational and personal data security weaknesses. Machine learning algorithms can predict where vulnerabilities are most likely to exist.
Advanced Malware and Ransomware
Cybercriminals can leverage AI to create more sophisticated ransomware and malware that adapt to avoid detection by traditional security measures. AI-driven malware can analyze network behavior and modify its tactics based on how it is being tracked.
DeepFake and Social Engineering
Many traditional hacking attempts followed a specific, recognizable pattern. In other words, you could spot a phishing attempt if you knew what to look for. AI can be used to create more convincing social engineering attacks, such as personalized phishing emails or fake websites that appear legitimate, fooling even the most skeptical person.
Compared to the blanket attempts of the past, AI enables highly targeted and precise attacks at scale. Machine learning models can analyze victim data, such as company or social media profiles, to craft highly personalized phishing campaigns or identify the weakest points in a system, making the attack more likely to succeed.
Speed of Execution
Traditional attacks often took time to bear fruit, but AI-powered attacks can execute and achieve success quickly. AI systems can analyze large datasets and identify vulnerabilities almost instantly, enabling cybercriminals to carry out attacks with minimal delay.
In addition, using AI to automate phases of the attack cycle, such as reconnaissance, exploitation, and exfiltration, means that far less human intervention is needed.
What Are the Types of AI-Driven Cyberattacks?
AI-driven cyberattacks can cause financial, emotional, and other harm. Knowledge is power when it comes to defending against such attacks and fighting back after they happen. Learn how AI is fueling a new wave of cyberattacks and leading to different types of data breaches.
AI-Powered Phishing
AI-powered phishing attacks use generative AI to create realistic and personalized SMS messages, emails, social media outreach, and phone communications to fool their targets and achieve a desired result. By analyzing browsing and social media habits, as well as previous communication, AI can attempt to make convincing connections that increase the likelihood of gaining access to sensitive data or manipulating specific behaviors.
Advanced Persistent Threats
Advanced Persistent Threats through AI are targeted, prolonged cyberattacks in which intruders infiltrate a network and remain undetected with the intention of stealing sensitive data or causing harm. AI can quickly analyze extensive networks to identify vulnerabilities, enabling attackers to adjust exploits in real-time to avoid detection. This makes these types of attacks more difficult to identify and defend against.
AI-Driven Ransomware
AI-enabled ransomware is an advanced type of ransomware that optimizes and automates some aspects of the attack. For example, AI can optimize when and where to strike a system by analyzing the network to understand its weaknesses. It can then encrypt the most critical data first to ensure maximum impact.
AI-Based Malware
Traditional malware typically follows fixed patterns, but AI-powered malware uses machine learning to enhance its capabilities and adapt to its environment. This type of malware is more difficult to detect and remove because it can self-encrypt and quickly change its behavior based on the target system’s defense mechanisms.
Distributed Denial-of-Service Attacks
AI is often used to facilitate DDoS attacks. The technology makes these attacks more efficient and effective by mimicking legitimate traffic patterns and optimizing the efforts to overwhelm a network or server. This makes the activity challenging to identify. It can also more readily adapt to countermeasures.
Credential Stuffing and Brute-Force Attacks
AI-based credential stuffing and brute force attacks are automated cyberattacks designed to gain unauthorized access to online accounts.
Credential stuffing uses leaked username and password combinations, often from data breaches, to test logins across multiple websites at scale. Brute force attacks will systematically attempt all possible combinations of usernames and passwords until the correct ones are found. AI-enhanced attacks can carry out these processes more quickly and bypass common security features like rate-limiting and CAPTCHA.
Data Exfiltration
Data exfiltration is also known as data exportation, data extrusion, or data theft. AI can identify and copy valuable data to steal by analyzing a company’s data structure and patterns using machine learning and natural language processing. It can help exfiltrate data without detection by disguising its presence and avoiding traditional anomaly detection systems, speeding up the process and reducing the risk of interception.
Which Platforms Have Recently Fallen Victim to AI-Assisted Cyberattacks?
AI-assisted cyberattacks are on the rise and rank as a top concern among business executives. A recent Gartner survey shows that AI-enhanced malicious attacks are the top emerging risk concern. This not only impacts businesses, it also the people who rely on them and trust them with their personal data.
Just a few of the platforms that have fallen victim to cybercriminals using AI include:
- TaskRabbit (2018): Hackers used an AI-controlled botnet to carry out an effective DDoS attack on TaskRabbit’s servers, which led to the suspension of the entire platform. The cybercriminals also stole the Social Security and bank account numbers of 3.75 million freelancers and clients registered on the site.
- Instagram (2019): Instagram experienced several cyberattacks that led to a massive data breach. Security experts speculate that AI-driven systems were used to scan user data, identify vulnerabilities, and gain access to the passwords and other personal information of approximately 49 million users.
- T-Mobile (2022): Attackers exploited an AI-equipped API to access T-Mobile’s internal system, allowing them to steal 37 million customers’ personal data, such as names and PINs.
- Activision (2023): An AI-powered phishing campaign targeted the gaming company that created the Call of Duty franchise. Cybercriminals used AI to create convincing SMS messages. A company HR staff member fell victim to the campaign and granted the attackers access to the company’s internal systems, including all employee personal data.
- Snowflake (2024): Hackers used AI-powered tools to gain access to the cloud storage service, Snowflake. This allowed the cybercriminals to access and steal data from Snowflake customers, namely Ticketmaster, Santander, Lending Tree, and Advance Auto Parts. The stolen data included bank account and credit card details for 30 million customers as well as human resources information for company staff.
What To Do if You Fall Victim to AI-Assisted Cyberattacks
As AI becomes more powerful and sophisticated, it will supercharge cyberattacks and make defending against them even more challenging. If you’ve been the victim of one of these attacks, specific actions can help you protect your rights and fight back against these bad actors. Here are the steps to take following an AI-assisted cyberattack:
- Stay Calm and Secure Your Accounts: Before doing anything else, you should stop the threat from spreading. Start by immediately changing passwords for all accounts, especially sensitive ones like email, banking, and social media. If you haven’t already, enable two-factor authentication wherever possible as an extra layer of protection.
- Monitor Your Financial Accounts: Regularly screen your bank, credit card, and online payment accounts for any unauthorized transactions. If your personal information was compromised, consider placing fraud alerts on your accounts or temporarily freezing your credit with credit bureaus.
- Notify Relevant Authorities and Companies: If you believe you’ve been the victim of a data breach, don’t keep it to yourself. File a police report immediately if your financial details and identity have been stolen. Also, report the attack to the Federal Trade Commission.
- Notify Your Credit Card Companies and Banks: If your personal data has been compromised, consider notifying your financial services of the attack. They may decide to issue new cards or accounts and assist in monitoring for fraud.
- Contact a Data Breach Lawyer: Finally, reach out to an attorney experienced with data breaches and cybercrime for legal advice, potential lawsuits, and compensation opportunities. These lawyers have the legal and technical knowledge to handle cases involving the unauthorized access of personal data. They can help you understand the legal actions you can take, such as class action lawsuits or personal claims for damages.
How Class Action U Can Help
If you were impacted by a data breach, we urge you to explore your options. Unfortunately, many people aren’t sure where to turn when something like this happens. You may be entitled to compensation that covers your out-of-pocket expenses, emotional distress, and other related costs.
In these difficult situations, Class Action U is here to provide guidance at no cost to you. Our team is committed to leveling the playing field to ensure that justice is served when companies don’t take their data security responsibilities seriously. We can connect you with an experienced data breach lawyer who will fight for your rights. Contact us today for a free, no-obligation case evaluation.
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