AI and cybersecurity — attacks and defense

An arms race

Cybersecurity has always been a cat-and-mouse game between attackers and defenders. AI gives both sides new weapons — and disrupts the balance in ways that are fundamentally changing the security world.

Illustration created with Canva AI

AI as an attack weapon

• Personalized phishing — AI generates convincing fake emails at scale, tailored to the specific recipient based on public data
• Deepfake fraud — fake voices and videos are used for social engineering and CEO fraud
• Automated vulnerability scanning — AI finds weaknesses in systems faster than human attackers
• Malware generation — AI tools like WormGPT (an unfiltered LLM) help attackers write code
• Adversarial attacks — subtle manipulations of input that mislead AI security systems

AI as a defense weapon

• Anomaly detection — AI recognizes abnormal behavior in networks that indicates an intrusion
• Automatic patch prioritization — AI determines which vulnerabilities are most urgent
• Threat intelligence — AI processes millions of threat signals faster than a SOC team
• Anti-phishing — email filters use AI to detect fake messages
• Automated response — automatically isolating infected systems during an attack

The biggest risks

The asymmetry is concerning: attackers only need to succeed once; defenders must always succeed. AI makes attacks cheaper and more accessible. State hackers and criminal organizations are investing heavily in AI-driven attack tools.

Recommendations

• Implement AI-driven detection systems (SIEM/SOAR)
• Train employees specifically on AI-generated phishing
• Always verify via a second channel for unusual requests, even from known senders