The Impact of AI Advancements on the Surge of Cyberattacks in the Tech World - The Hexaa

The Impact of AI Advancements on the Surge of Cyberattacks in the Tech World

Digital advancements in information technology often don’t match the hype in science fiction literature and films. While popular media often portrays a future plagued by robot uprisings and AI-driven cyber-attacks, the reality is not as extreme.

AI cyber-attacks are growing increasingly common and impacting the cybersecurity industry significantly. They pose security threats not only for government agencies but also for ordinary individuals. Hackers have posed a persistent problem since the Internet’s inception, but their reach and capacity to steal massive amounts of data have become increasingly formidable.

Real-time AI Cyberattack Incidents:

WordPress has reported a series of botnet brute-force attacks on over 20,000 self-hosted websites, potentially allowing hackers to access user personal information and credit card numbers, leading to a loss of faith among users and reputable hosting services.

In April 2018, an AI-assisted cyber-attack on TaskRabbit compromised 3.75 million users’ Social Security and bank account details, leading to the temporary suspension of the site. The attack was carried out using a massive botnet controlled by AI, resulting in the loss of 141 million more users.

Instagram faced two cyber-attacks in 2019: one in August where users found their account information shared by hackers, and another in November where a code bug exposed users’ passwords in their browser URLs. While Instagram has not provided detailed information about the breaches, speculation suggests hackers are using AI systems to scan user data for potential vulnerabilities.

Moreover, AI-assisted attacks are expected to escalate due to botnet attacks and malware proliferation. Even seemingly minor security breaches can be catastrophic.

Even with basic internet security measures like firewalls, regular malware checks, secure content management systems, and experienced cybersecurity teams, hackers can exploit existing vulnerabilities.

An Emerging Trend of Exploiting AI-generated Content:

A trend of online scams using AI-generated YouTube videos to deceive people into downloading disguised malware has increased by 200-300% monthly, according to a report by CloudSEK.

The videos, including Raccoon, Vidar, and RedLine, pose as tutorials for obtaining pirated versions of software like Autodesk 3ds Max, AutoCAD, Photoshop, and Premiere Pro, which are exclusive to licensed users.

Hackers are increasingly using AI-generated videos to create an illusion of authenticity and reliability, often on YouTube and social media platforms like Facebook, Instagram, and Twitter.

These videos, which are often linked to a seemingly free application, are data-stealing malware that steals and transmits sensitive financial information, putting users at significant risk. This shift from traditional methods of hiding identities to AI-generated videos is a concerning development in the fight against cybercrime.

AI’s Impact on DDoS Attacks and Disinformation Campaigns:

AI-driven attacks are becoming more prevalent, especially on platforms like Twitter, and political parties are accusing bots of distorting arguments or inflating follower counts. While bots are used to enhance customer engagement, their sophistication is increasing, making it difficult to distinguish them from real people. Google’s AI-generated audio and video demonstrate this trend.

Bots can be exploited for disinformation campaigns, flooding Twitter threads with false posts, and launching DDoS attacks on adversaries’ computers and networks. Bots specializing in spam on platforms like Facebook and Twitter often outperform humans.

Some Effective Strategies to Combat AI- AI-generated Cyberattacks:

To protect against online scams, avoid downloading free software that is exclusively available for purchase, as it may contain malware and viruses. Exercise caution when downloading content or clicking on links from unfamiliar or untrustworthy sources.

Advancements in machine learning and artificial intelligence (AI) have significantly improved cybersecurity by helping security teams identify threats in vast amounts of data. AI can recognize network traffic patterns, malware indicators, and user behavioral trends.

However, attackers also exploit AI and machine learning to their advantage, as cloud environments make it easier for them to construct sophisticated learning models. This article explores how hackers exploit AI and machine learning to target enterprises and strategies for preventing AI-focused cyber-attacks.

Major Tactics Assaulters Use Against Defenders of AI Cyberattacks:

  • Mapping Existing AI Models:

Attackers are attempting to map AI models used by cybersecurity providers and operational teams, disrupting machine learning operations and manipulating models to favor their tactics. They can also subtly change data to evade detection based on known patterns.

Defending against AI-focused attacks is challenging, as defenders must ensure accurate labeling of data used for training models and detection patterns, which may result in smaller data sets for model training, potentially limiting AI efficiency.

  • Exploiting Machine Learning for Malware Attacks:

Machine learning is used by attackers to design malware and attack methodologies, identifying specific events and behaviors that defenders seek. These tactics, techniques, and procedures (TTPs) are a combination of activities that can be observed and utilized by machine learning models to develop detection capabilities.

By observing and predicting how security teams detect TTPs, adversaries can modify indicators and behaviors to stay ahead of defenders who rely on AI-based tools for attack detection.

  • Generating Misleading Data:

Attackers can compromise machine learning and AI environments by injecting inaccurate data into models, which are crucial for accurate detection profiles. They can introduce benign files resembling malware or generate false positive behavior patterns, tricking AI models into accepting malicious actions as harmless. Additionally, they can introduce malicious files wrongly labeled as safe during AI training.

Parting Notes:

The potential for autonomous AI systems is a growing concern in the cybersecurity sector, particularly if cybercriminals continue to evolve.

Cyber threat intelligence companies are part of the solution, but businesses should not ignore cybersecurity and should partner with strong cybersecurity consulting services to combat malicious actors and protect their systems.



Publihsed by: Tanzeela Malik