AI: The Great Equalizer in Cyber Offense

For decades, the cybersecurity industry worked on one assumption: advanced attacks require advanced attackers. Nation-states and elite teams had the skills, training and resources. That exclusivity was itself a defense.

That barrier has collapsed.

Recent threat intelligence reports from both Anthropic and OpenAI reveal a fundamental shift: non-technical actors are successfully executing complex cyber operations using AI assistance. They’re developing functional ransomware,  embedding in enterprises, and conducting scaled extortion campaigns. AI has become the ultimate force multiplier, rewriting  the entire threat equation.

The capability revolution

AI eliminates the learning curve for cybercrime

Cybercrime used to demand years of training: coding, network knowledge, tool mastery. Even “easy” frameworks like Metasploit required baseline expertise. AI erases that barrier.

Threat actors now move faster and at higher volume by leveraging AI capabilities rather than developing them personally. OpenAI and Anthropic reports documented threat actors progressing from basic scripts to sophisticated systems incorporating dark web integration, and even automated social media manipulation fleets controlling Android devices.

And it’s not just technical capability.. . Operations like “VAGue Focus” blended covert influence  with social engineering, using AI to contact US senators and researchers with tailored economic policy requests.

Similarly, romance scam operations now use AI to generate culturally nuanced, emotionally intelligent communications that overcome language barriers.

AI provides instant sophistication, regardless of who’s behind the keyboard.

 

The speed and scale paradigm shift

Weeks of work collapse into days, and one attacker becomes a crowd.

What makes AI-enabled threats different isn’t just accessibility. It’s speed and scale.

Operations that once took months now take weeks. Campaigns that required teams can be run by one person.

• ScopeCreep: malware went from concept to deployment, with active evasion, in weeks.

• GTG-2002: 17 victims in 30 days, all by a single operator.

• High Five: thousands of fake TikTok and Facebook comments created at machine speed.

• Sneer Review: simultaneous influence campaigns in English, Chinese, and Urdu.

This compression of time and multiplication of reach breaks traditional security assumptions.

 

Case studies in AI-enabled operations

The evidence is striking. Across continents and criminal ecosystems, AI is rewriting the rules of cybercrime:

The UK Ransomware Developer (GTG-5004): With no cryptography training, one individual built ransomware using ChaCha20 encryption, EDR evasion, and anti-recovery features. Marketed for $400–1,200, it delivered enterprise-grade capability without enterprise skill.

Operation ScopeCreep: A Russian-speaking threat actor used ChatGPT to build Windows malware with multi-stage execution, DLL side-loading, and custom Themida packing. Their limited expertise showed, but so did AI’s fingerprints, which gave investigators new visibility.

North Korean Remote Workers: Operators are successfully infiltrating and maintaining developer positions at Western companies while relying heavily on AI for technical tasks. OpenAI documented evolved tactics where actors from all over the world attempted to automate résumés, interview responses, and coding tasks, while researching bypasses for corporate controls. This model has already generated hundreds of millions in disguised revenue.

The Automated Extortion Campaign (GTG-2002): A single operator compromised 17 organizations in one month, using Claude Code throughout the attack lifecycle, from reconnaissance to ransom negotiation. The campaign reached operational scale that once required entire teams, with demands climbing to over $500,000.

And this isn’t limited to individuals.

• Iran’s APT42 has used Gemini for advanced phishing campaigns and vulnerability research.

• China’s KEYHOLE PANDA and VIXEN PANDA used AI for brute-force password scripts, custom port scanners, and even AI-driven penetration testing, where tools iterated on Nmap output to refine attacks automatically.

These aren’t traditional tool adoptions. They represent a structural shift in how capabilities are acquired and deployed.

 

Adapting to the new reality

Security must pivot from capability-based to behavior-based defence.

The real threat isn’t novel attack methods: it’s the collapse of barriers. Sophisticated methods are now available on demand, collapsing development cycles and eroding trust boundaries.   

This deepfake-enabled $25.6 million fraud shows how AI undermines traditional verification at every level, from executive impersonation to AI-augmented technical staff. 

• This speed and scale breaks traditional security models, emphasizing the need for defenses to adapt: Test SOCs against AI-driven campaigns that break traditional patterns.

• Validating identity verification processes against AI-generated personas and deepfakes

• Accelerate incident response to match AI-level attack speed.

• Detect insider threats where AI helps adversaries masquerade as legitimate staff.
   

The paradox: AI lowers entry barriers but leaves new trails. Operation ScopeCreep was flagged because of AI development traces. Fake “remote workers” left digital breadcrumbs. Even high-volume influence campaigns revealed themselves through the very automation that powered them.

 

The challenge ahead

The era of capability-based threat assessment is over.  Advanced techniques are no longer exclusive to nation-states, they’re accessible to anyone with AI access.

Security leaders must shift focus to behavior, velocity, and AI fingerprints.

The democratization of cyber capabilities through AI isn’t coming – it’s here. The question isn’t if your organization will face AI-enabled threats. It’s  whether you’ll be ready when they arrive faster and louder than your defenses expect.