AI vs. AI: How Cybercriminals Are Using AI to Bypass AI-Driven Security Systems

AI in cybersecurity is growing in importance. 2024 reported a deepfake attempt occurred every five minutes, while digital document forgeries surged 244% year-over-year.

Also, 87% of organizations experienced AI-led cyberattacks in the past year, and 91% anticipate a significant surge in such threats over the next three years.

The financial stakes are just as alarming, with figures claiming cyber crimes will continue to increase between 2024 and 2029 by 6.4 trillion U.S. dollars, a 69.4% increase.

So, can your business outsmart AI-led threats before they outsmart you? And are you well prepared to stay ahead? Keep reading to learn more about the latest AI threats and how to defend against them.

Increase in AI-led Cyber Crimes

Businesses worldwide leverage AI solutions to enhance efficiency and boost productivity. Unfortunately, criminals are also finding ways to use AI to make their attacks more effective.

AI’s Use in Phishing

Phishing has always been a cybersecurity threat, but AI has taken it to a level where malicious actors might fool even the most cautious professionals.

What was once an attack identifiable by odd formatting or generic messages is now a near-perfect deception. AI-led phishing bypasses many detection methods by crafting highly personalized, grammatically perfect emails that look indistinguishable from legitimate corporate communication.

The criminals behind these attacks use AI models to scrape the internet for a target’s digital footprint—social media, company websites, and even past corporate announcements. With this data, AI generates personalized phishing messages that appear to come from a known colleague or executive. AI can even mimic writing styles, ensuring phishing emails sound like a trusted sender.

More Sophisticated AI Deepfakes

If AI-generated phishing is the entry point, deepfake technology is the next evolution of cyber deception. Deepfakes—AI-generated synthetic videos, voice clips, and images intended to look like a celebrity or trusted individual—are already being used to bypass traditional verification methods, fool employees, and manipulate executives into financial fraud.

Deepfake AIs take publicly available videos, interviews, or conference calls of executives and train themselves to mimic the target’s facial expressions, voice, and speech patterns. The deepfake is then deployed in video calls or internal corporate communications, instructing employees to approve financial transfers, disclose sensitive information, or execute unauthorized actions.

In early 2024, a financial institution lost $25 million after criminals tricked an employee into transferring funds during a video call with what appeared to be the CFO. The deepfake replicated the facial expressions, lip movements, and voices of several colleagues the employee recognized, creating a seamless, real-time interaction.

Although initially suspicious, the victim was convinced they were speaking to a trusted executive and processed the transaction, only realizing later that the CFO had never actually made the call.

Malware Exploits

Once cybercriminals gain access, their next step is often deploying malware. However, AI has changed how malware is created and executed. Instead of manually writing exploit code, attackers now use AI to generate malware, making detection nearly impossible.

Generative AI can write exploit code for known vulnerabilities in seconds. AI-powered malware automatically adjusts if detected, reconfiguring itself to bypass security tools. This means that zero-day exploits—vulnerabilities unknown to software providers—are now being found and exploited at machine speed.

AI Prompt Injection & Data Poisoning

AI cybersecurity was supposed to make enterprises safer—but now, attackers are targeting the AI itself. Instead of attacking networks and software, cybercriminals manipulate AI models to turn security tools into vulnerabilities.

AI prompt injection refers to cybercriminals exploiting weaknesses in AI chatbots and security assistants by injecting malicious inputs. For example, a hacker might trick an AI-powered security chatbot into revealing sensitive internal data by manipulating its prompts.

Data poisoning involves hackers feeding AI models false data, altering their ability to detect and prevent attacks. If an AI-powered fraud detection system is trained on manipulated data, it can be taught to ignore fraudulent transactions.

Attackers can also poison security models, blinding them to malware or unauthorized access.

Why AI Security Isn’t Enough (Yet)

A fully autonomous AI security system that runs without human intervention is a dangerous illusion. Many believe that AI-powered cybersecurity tools can operate independently—constantly monitoring, detecting, and responding to threats with minimal human input. In theory, this sounds like the ultimate defense system. In reality, no AI system can be left unattended.

There are a few reasons for this. For one, AI security models can misclassify threats or overlook attacks due to biased or incomplete training data. AI can detect anomalies but doesn’t understand the intent—it may flag normal behavior as a threat or fail to recognize sophisticated, low-and-slow attacks.

For another, cybercriminals can manipulate AI models by feeding them crafted inputs designed to trick the system into misidentifying threats or granting unauthorized access. They can also exploit automated AI responses. For example, attackers could intentionally trigger AI defenses to cause disruptions or distract security teams while launching a larger attack.

Rethinking Security Architectures

It is better to have a multi-layered AI security strategy, as traditional methods like firewalls, endpoint protection, and so on are not enough.

Likewise, AI alone is not enough. Humans are still needed to validate AI-driven decisions to avoid false positives and blind spots. Businesses must constantly update and test AI security models to prevent adversarial attacks. AI defenses should be part of a zero-trust security model that assumes no entity—human or AI—should be trusted by default.

How to Defend Against AI-Powered Cyber Threats

Defending against malicious, AI-enhanced attacks requires an approach designed for security that combines AI, human oversight, and regulatory compliance.

1. Secure AI by Design

Embedding security into AI systems from the design phase makes for a stronger defense than trying to patch vulnerabilities later. This requires applying Secure by Design principles.

AI systems should have minimal access to sensitive data—only what they need to function. Granting unrestricted access increases the risk of data breaches and model poisoning.

No single security mechanism is enough. AI security should include multiple defensive layers—firewalls, endpoint protection, anomaly detection, and behavioral monitoring—to prevent AI-driven threats from bypassing defenses.

When AI security tools fail or are compromised, they should default to a secure state, preventing cybercriminals from exploiting vulnerabilities. AI authentication, for example, should require manual verification rather than granting default access.

2. AI Cybersecurity

While AI poses new security challenges, it also provides powerful defense mechanisms. AI models can analyze vast amounts of data to detect unusual behavior and spot deviations that might indicate compromised credentials or AI-driven phishing attempts.

AI can also adjust defenses dynamically based on detected threats—blocking unauthorized access and flagging suspicious activity.

Automating Incident Response with AI: AI security platforms help SOC teams prioritize threats, filter false positives, and automate responses to attacks—reducing human workload and improving response times. They can track emerging attack techniques and predict potential vulnerabilities.

AI Deception Techniques: Security teams can use fake AI systems designed to lure attackers, study their tactics, and prevent real AI models from being compromised. Just as attackers use AI to craft convincing phishing campaigns, you can deploy AI to feed adversaries misleading intelligence—diverting them away from critical assets.

3. Combine AI with Human Collaboration

AI can detect anomalies, but humans understand the intent, detect social engineering attempts, and make strategic security decisions. Human oversight is also required to refine AI responses and prevent manipulation.

• Train employees to recognize the signs of an AI attack.
• Upskill security teams in adversarial AI defense, understanding how attackers manipulate AI models and how to counteract AI-based threats.
• Develop AI Red Teaming Programs that regularly test AI security tools for vulnerabilities and improve AI-driven detection and response mechanisms.

4. Regulatory Compliance & Ethical AI Governance

Everything you do must align with data protection regulations such as GDPR, ISO 27001, and the NIST AI Risk Management Framework. For example, part of GDPR mandates that AI security systems handling personal data must comply with privacy regulations to prevent unauthorized data access and model exploitation. NIST’s AI Risk Management Framework provides guidelines for securing AI models, detecting adversarial attacks, and ensuring AI security systems remain resilient. Finally, ISO 27001 ensures organizations integrate AI security into their broader information security management systems (ISMS).

AI vs. AI in Cybersecurity

Cybercriminals are using AI to create phishing attacks and deepfakes so convincing that they are challenging to detect by traditional means.

Meanwhile, companies use AI in their security systems, but most find that AI alone cannot protect their data and systems.

The fact is, there isn’t an AI security system that will operate independently of human control. AI can turn automatic responses into possible actions with the help of security teams, but it remains susceptible to exploitation through adversarial attacks, data poisoning, and prompt injections.

If you need help implementing a secure AI solution, contact Taazaa. From AI readiness assessments to custom AI development, we have the depth of talent you need to leverage AI for your business. Contact us today!