Did you participate in the trend of using AI to generate professional images of yourself? A perfect answer for camera-shy people. Just use your favorite picture with a few commands to generate another that serves a purpose. Imagine if someone takes your image of the net and generates another of whatever they like. And maybe they decide to impersonate you using generated images of you. 

There has been a debate on X (Twitter) on who wins if 10 men are asked to fight a fully grown gorilla. Do you know there’s already an AI-generated video of 10,000 gorillas fighting 1,000,000 men? Amazing, yeah? I know. Now, envision someone tweaking your video to implicate or destroy your image. Scary and real.

Whenever there’s a debate on X (Twitter), you will see posts asking Grok (Twitter’s AI) to answer or for context. Interesting and easy to get a response explaining or giving points to support your argument. Isn’t it convenient to get well-worded and clearly explained answers to one question than to start tracing tweets?.

Artificial intelligence (AI) is making life easy for everyone. It can do almost everything a human does. In fact, it is said that AI simulates human intelligence processes in computer systems. Because of AI, computers can perform tasks that typically require human intelligence, such as understanding their environment, learning, processing data, problem-solving, and decision-making. 

How, then, do you protect yourself from AI-generated attacks? How do you prove to your boss that the video of you in Paris when you were in the hospital is fake? This is where AI in cybersecurity comes in. AI in cybersecurity is deploying AI algorithms to detect, prevent, and respond to cyber threats. 

This may all seem trivial and fun-filled, but in reality, it isn’t. Irrespective of its vast uses, AI poses serious threats to your cybersecurity. Several cybercriminal organizations have invested in machine learning, automation, and AI to launch large-scale, targeted cyberattacks against organizations. 

On 28th April, 2025, power was lost in Portugal and parts of France. The immediate speculation was that it was an unconfirmed cyberattack, even as no one took responsibility for it. This power loss caused panic, medical and essential services were interrupted or halted, and gridlock traffic in many areas. Luckily, power was restored that evening. Imagine if it were an AI-powered cyberattack and it involved a ransom demand.

AI as a Foe: The Reality

It may seem that people were quick to jump to the cyberattack conclusion. This may have seemed farfetched a mere 5 years ago, but today? Anything is possible. This is because AI has increased the number of threats and potential ransomware attacks. The commonisation of AI use has led to the rise of more sophisticated attack vectors such as polymorphic malware, scripting, and “living-off-the-land” attacks. These make it easier for cybercriminals to bypass native tools and antivirus defenses.

Early this year, there was a rave about a Chinese chatbot that was way better than ChatGPT. Guess what? In April 2025, it was discovered that the chatbot, DeepSeek, had transferred personal information of approximately one million South Koreans to China without proper consent. Even as it was discovered, the pilfered data has been sent, and can’t be undone. This led the US and Italy to ban its use, citing the chatbot as a weapon of cyberwarfare. This is a blatant AI misuse, raising the issue of ethics in AI use.

Ever heard of the AI-powered application Cluely? Cluely is a desktop application used mainly for its “assists” in job applications and interviews. It monitors conversations in real time and offers suggestions and answers. This raises an issue of privacy, as the other party is unaware they are being analyzed. There really should be standards and policies guiding the use of AI.

The first use of Deepfakes in a cybercrime was in 2020. Cybercriminals tricked a UK-based energy company CEO into transferring approximately $243,000 to a fraudulent account. These criminals used AI-generated voice cloning to mimic the voice of the company’s German parent CEO, ordering the UK executive to urgently transfer the funds to a Hungarian supplier over the phone. The money was routed to Mexico and beyond, and the perpetrators were never caught. 

In another incident, a multinational company’s finance worker in Hong Kong received a Zoom call with several people who appeared to be senior executives. During this meeting, the employee followed a request to transfer HK$200 million (about US$25.6 million) to five different bank accounts. The scam was uncovered after the employee double-checked with HQ later.

Cybersecurity is scrambling to keep up with AI-based attacks and AI misuse, however, most of these scenarios would have ended differently with the use of the most common cybersecurity legacy mitigation methods: educating employees, principles of least privilege, separation of duties, and MFA.

AI as a Friend: The Hope

What can you do to protect yourself and your organisation when AI is your foe? Simple, make AI your friend. Luckily, the use of AI in cybersecurity is evolving with more sophisticated tools replacing and modernizing traditional tools. These tools are beneficial in critical aspects of cybersecurity.

AI automates repetitive processes, improves threat detection, and enhances responses to cyber incidents. Cybersecurity analysts could level the field by utilising AI and machine learning to process massive amounts of data, providing rapid insights based on analysis, and cutting through the noise of daily security alerts and false positives.

Additionally, AI could address the gaps between detecting known and zero-day threats. More modern AI-based approaches, such as behavior analysis, are becoming more popular in cybersecurity to protect against this malware evolution. Behavior analysis and detection approaches are powerful tools, as all malware eventually needs to exhibit malicious behavior to succeed. Properly trained AI can capably monitor, detect, and respond to these malicious heuristics faster than humans using non-AI-based tools.

How AI in Cybersecurity Can Help Your Business

Threat Detection

A key advantage of AI is automation. Automating network traffic and user behavior monitoring is a proactive way of detecting threats. If anomalies are detected, AI systems reduce response times and improve accuracy in detecting real threats, minimizing the risk of successful cyber attacks. These systems can anticipate potential attacks and deploy countermeasures. 

Tip: Use AI-enhanced IDS/IPS like Darktrace to analyze large volumes of internal data to detect anomalies, suspicious patterns, or unusual behavior.

Benefit: This ensures that the security measures vital for maintaining data integrity and security are as efficient as those powering the threats. It also detects zero-day exploits and subtle attacks missed by legacy rule-based systems.

Malware and Phishing Detection 

Rapid detection is critical in preventing the spread of malware and phishing scams, minimizing the risk to sensitive information and organizational assets. AI significantly boosts malware and phishing detection by tracking evolving malware and phishing techniques. This ensures the system swiftly and effectively identifies and neutralizes cyberthreats promptly. 

Tip: Use Mimecast and Google’s AI for Gmail to block phishing and business email compromise attempts more effectively.

Benefit: Scans incoming emails for suspicious links, spoofed domains, or language patterns indicative of phishing. 

Incident Management

AI’s role in automated incident response is vital in managing security incidents efficiently. By leveraging AI, organizations can automate the detection, analysis, and remediation of security threats, reducing the need for human intervention. This capability allows for immediate action, minimizing damage and enabling faster recovery from breaches.

Tips: 

• Install CrowdStrike, SentinelOne, or Microsoft Defender for Endpoint to monitor activity on endpoints (e.g., laptops, mobile devices) to detect malware or unauthorized access.
• Use Splunk UEBA to build profiles of typical user behavior and flags deviations (e.g., logging in at odd hours, attempting to or successfully accessing unusual data).
• Implement IBM QRadar or Splunk to correlate logs and events across systems using ML to detect threats and reduce false positives.
• Install IBM Resilient or similar tools to orchestrate and automate responses to known threats and revoke access when necessary.

Benefits: 

• Real-time threat hunting and automated remediation
• Detects insider threats, compromised credentials, or lateral movement
• Prioritizes alerts and assists with incident response
• Reduces human workload and speeds containment

Vulnerability Scanning and Patch Management

AI optimizes vulnerability scanning and enhances patch management. It simplifies and automates continuous network and system monitoring, leading to rapid identification of weaknesses in systems and applications. AI systems can detect and prioritise vulnerabilities as they arise, ensuring high-risk, high-impact vulnerabilities are addressed promptly, effectively mitigating potential threats. AI systems automate the deployment, tracking, and application of security patches, mitigating and eliminating risks introduced by unpatched vulnerabilities.

Tip: Use Tenable.io with Predictive Prioritization or Qualys to predict the most critical vulnerabilities based on historical data and threat intelligence.

Benefit: Focuses patching efforts where it matters most.

Identity and Access Management 

AI systems are highly adaptable, making them capable of automating access control policies while ensuring compliance with security standards. They analyze user behaviour and authentication patterns to ensure only authorized access to systems and data. They also detect anomalies that indicate unauthorised access attempts, preventing breaches. AI can continuously monitor and analyze attempted access to organisations’ data, reducing the likelihood of cyberattacks and fraud perpetration.

Tips: 

• Use BeyondTrust with AI-enhanced monitoring to monitor and evaluate the use of privileged accounts to detect unusual commands or unauthorized access.
• Implement Microsoft Entra ID (formerly Azure AD) to learn typical access patterns (e.g., login time, location, device) for each user and flag anomalies.

Benefits: 

• AI can flag when an admin downloads large volumes of sensitive files outside normal maintenance hours.
• AI can trigger an alert or block access if a user logs in from Nigeria at 3 a.m., when the user usually works in Kenya during office hours.

IoT Security

AI capably manages large networks of interconnected devices, enhancing security by ensuring secure device management. As most IoT devices do not have built-in security features, AI ensures IoT devices are operated securely, protecting sensitive data and ensuring reliable device functionality. By monitoring IoT devices for anomalies, AI systems can detect and mitigate threats effectively.

Tip: Install SentinelOne or similar tools to identify indicators of compromise (IoCs) across devices and launch automated investigations or remediation.

Benefit: Isolates endpoints and runs malware scans.

Penetration Testing

Novel AI-driven tools can easily stimulate attack scenarios, simplifying vulnerability detection to address security gaps. AI also automates and modifies network vulnerability detection, relying on its ability to identify previously unknown vulnerabilities. This automated penetration testing, further strengthened by continuous monitoring with AI, ensures that organizations maintain robust security postures, adapting to evolving security environments.

Tip: Contract penetration testers to use Cobalt Strike to simulate advanced persistent threats (APTs).

Benefit: Uses AI scripts and automation to adapt payloads, evade detection, and simulate lateral movement.

Data Loss Prevention

Data loss prevention is proactively analyzing data patterns to identify exploitable vulnerabilities to prevent loss. AI enhances data loss prevention by monitoring and protecting sensitive data from unauthorized access and breaches, ensuring data integrity and security. Moreover, AI aids in identifying and managing security risks associated with data handling practices. 

Tip: Use Microsoft Purview to monitor and learn cloud usage patterns to identify risky or unauthorized file sharing.

Benefit: Stops exfiltration through SaaS apps or personal cloud storage.

Integrating AI into your cybersecurity strategy is no longer optional but essential. AI dramatically improves the efficiency, accuracy, and responsiveness of digital defense systems. It does this by processing vast amounts of data in real time to rapidly identify and neutralize emerging threats.

With its predictive capabilities, AI helps organizations stay ahead of cybercriminals by anticipating attacks before they occur. Its automated response mechanisms enable swift mitigation, minimizing downtime and protecting critical data. AI-driven systems evolve alongside emerging threats, ensuring robust, real-time protection across all endpoints.

Beyond real-time defense, AI enhances compliance efforts, strengthens customer trust, and reduces the cost of managing risk. It empowers businesses to maintain operational continuity, safeguard sensitive information, and remain resilient in today’s constantly shifting threat landscape.

Are you ready to elevate your cybersecurity strategy? Partner with us to deploy cutting-edge, AI-powered solutions tailored to your organization’s needs. Let us help you stay secure, compliant, and competitive every step of the way. Send a message to us at info@hacktales.com.ng.