The Emergence of Automated Cybersecurity Threats  

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Amidst amplified digital advancements across various technological sectors, AI is booming significantly and in use across different domains. With the evolution of technology, the cyber threat landscape is also booming significantly. Cybercriminals leverage myriad AI tools, techniques, & automated methodologies to develop sophisticated scripts & exploits.   

Thus, the growing demand for AI is not only for the companies that reap the benefits of automation & generative power but also for cybercriminals and attackers. In this article, we will decode the various threats that automation and AI tools can cause to cybersecurity. We will also understand how automated cyber-attacks can pose severe issues to enterprises and strategies to mitigate them.  

Understanding Automated Cyber Threats 

The rise of AI and automation has tremendous growth among the cybercriminal community in developing malicious scripts and orchestrating algorithms. Automated cyber threats refer to criminal actions that involve digital aspects powered by automated tools & AI algorithms. Attackers can devise malicious code, exploits, and illicit algorithms at high speed, scalability, and sophistication that can run without human intervention.  

Various automated threats that the attackers’ community implements include:  

  • Phishing bots: Phishing bots are automated malicious systems that help to distribute phishing emails. These bots spawn phishing emails & messages from a trusted sender & can quickly adapt various tactics to bypass email security filters. Since these bots are AI-powered, they can also perform automated information gathering for personalizing & customizing the attacks based on the target victim.  
  • Automated Botnets: Botnets are a network of compromised servers, computers, and IoT devices. Cybercriminals command & control (C&C) these automated botnets to launch Distributed Denial of Service (DDoS) attacks and other multi-level exploits like spam, phishing, and data theft. Modern cybercriminal communities provide DDoS-as-a-Service over the dark web that is highly autonomous and uses AI algorithms to cope up and breach cyber defenses.  
  • AI-generated malicious scripts: Cybercriminals are leveraging advanced tools to identify and exploit vulnerabilities automatically. Then, they use generative AI tools to create customized exploits to perform attacks like buffer overflow, SQL injection, and cross-site scripting (XSS) on the target system. AI-generated scripts increase the exploit development time, making it easy for not-so-expert cybercriminals to build custom exploits.  

Various Challenges of Automated and AI-powered Cyber Threats 

The rise of automation techniques, Artificial Intelligence (AI) tools, and Machine Learning (ML) methods helps cybercriminals in myriad ways to build attacks & exploits. It poses significant challenges to enterprise cybersecurity systems across the globe. Here are some notable pointers that attackers extract utilizing automated tools that lead enterprises to a more challenging situation.  

  1. Highly scalable attacks: Cybercriminals can operate automated attacks at a large scale as they do not require constant surveillance. That becomes advantageous compared to traditional attacks. Attackers can scan hundreds of computers for vulnerabilities and even scale up the scan for thousands of target systems.  
  2. Speed up the attack:  By leveraging automated tools and AI algorithms, cybercriminals can speed up the attack process. Without human intervention, the attackers can launch massive attacks on numerous enterprise systems quickly. The quick creation of exploitable scripts and attack tools using generative AI can also speed up the attack process.  
  3. High volume and effective evasion techniques: By automating attack algorithms & techniques, cybercriminals can deploy sophisticated evasion methods at a high volume. By training Machine Learning models, cybercriminals can create polymorphism to modify code signatures. This modification helps attackers bypass signature-based detection systems in enterprise security solutions.  
  4. Resource Intensive operations: Another hectic challenge that automated cyber threats pose to enterprise systems is that defending against these threats is resource-intensive. To protect against such a massive amount of autonomous attack vectors, enterprises need significant resources like massive time, technological defense systems, and skilled security experts.  

How do Automated AI-powered Cyber Attacks Work?

Cybercriminals took notice of the increase in technologies and digital systems across enterprises. However, through manual techniques, attackers will not be able to target a large number of enterprise systems. Therefore, to increase the potential and the number of targets, cybercriminal communities are leveraging automated tools and AI algorithms.  

They use a state-of-the-art vulnerability framework that utilizes machine learning (ML) techniques to analyze bugs on a target machine. Then, depending on the vulnerability, the autonomous tool will prepare techniques or create exploits to compromise an organization.  It could be generating well-designed spear phishing emails with a touch of personalization for all employees of the target system or performing brute-force attacks on various accounts based on previously found credentials.  

Attackers can also leverage AI-powered automated tools that have the potential to bypass ordinary and traditional cybersecurity solutions. Some examples are:   

  • The automated AI tool will scan for bugs in the existing firewall and deface it.  
  • AI-based hacking tools can also scan for a non-updated software patch in any security system & pose a danger.  

Some cybercriminals can design advanced bots for backdoors and Advanced Persistent Threat (APT) attacks that use specialized signatures to bypass powerful anti-malware or firewalls. Thus, AI-powered automated cyber attacks are known for causing widespread damage to enterprises.  

Attackers also use deepfakes to train samples of the CEO’s voice & generate random messages for employees to steal data. Deepfakes help mimic the voice of a company’s CEO to make an urgent wire transfer from employees. Attackers are also modifying generative AI tools & using those APIs to conduct personalized phishing scams.  

Mitigation Strategies Against Automated Cybersecurity Threats 

Enterprises should think up & utilize advanced technologies plus adopt multifaceted approaches to tackle such automated cyber threats. To embark on AI-powered automated attacks, enterprises should respond with AI-powered solutions.   

Other than continuous vigilance, robust security policies, and using frameworks like Zero Trust Principles, enterprises should use advanced Identity and Access Management (IAM) solutions, Firewall types, IDS/IPS, Security Information and Event Management (SIEM) systems, and Vulnerability Management Solutions that run on top of machine learning, deep learning, and AI algorithms.  

Some key strategies that enterprises should welcome in their existing security infrastructure include:  

  1. Defensive algorithms using AI ML: The way attackers enhance the capabilities of their attacks through AI and ML models, enterprises should also leverage AI/ML to defend against threat detection. AI and ML algorithms can identify signatures & analyze vast amounts of data or threat patterns automatically. 
  2. Threat Intelligence with Continuous Monitoring: Monitoring network traffic with automated tools and filters has become an obvious way to defend against cyber threats. To take this malicious traffic analysis to the next level, integrating threat intelligence AI models trained with previously attacked datasets can enrich proactive defense measures and monitoring. 
  3. Patch Update Checks & Scans: It is also essential for enterprise systems to perform patch updates regularly. Employees may fail or forget to update different security patches regularly or skip them at times of urgency. That is where automated patch scanning systems help to check whether the system is fully up-to-date with the latest patches.  
  4. AI Detectors & Signature Scanners: Enterprises should enforce AI detectors to identify AI-generated automated attacks that use deepfakes & AI-based phishing tools. Automating such AI-generated attacks can help enterprises tackle such threats in bulk.  


Automated cyber-attacks and AI scams have become a digital pandemic across enterprise systems. Enterprises should address the rising concern & advancement of sophisticated attack vectors planned by cyber criminals. Whether the business or the organization is large or small, attackers have prying eyes on it. They are constantly evolving automated attack techniques & utilizing AI to exploit system vulnerabilities. Therefore, enterprises and every nation’s government should work collaboratively with AI to combat these new-age attack vectors.

With VE3’s expertise in automation, AI, and cybersecurity, enterprises can effectively combat the ever-evolving landscape of automated cyber threats. Leveraging VE3’s advanced AI-driven security solutions ensures robust protection against sophisticated cyber-attacks, safeguarding enterprise systems in this digital age.  


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