Weaponized large language models (LLMs) fine-tuned with offensive tradecraft are reshaping cyberattacks, automating reconnaissance, social engineering, and more.
Models like FraudGPT, GhostGPT, and DarkGPT enable attack strategies like phishing and code obfuscation, available for as low as $75 monthly.
Cybercrime entities exploit revenue opportunities through leasing access to weaponized LLMs, resembling legitimate SaaS businesses.
The blurring lines between developer platforms and cybercrime kits indicate a rapid evolution in AI-driven threats.
Fine-tuned LLMs are increasingly vulnerable to producing harmful results, as reported by Cisco’s AI Security Report.
The process of fine-tuning LLMs creates potential security weaknesses, exposing them to attacks like data poisoning and model inversion.
Legitimate LLMs are now at risk of exploitation and integration into cybercriminal tool sets, increasing their susceptibility.
Fine-tuning destabilizes alignment, compromising safety controls especially in sensitive domains governed by strict compliance regulations.
The rise of black-market weaponized LLMs like GhostGPT and FraudGPT sold for $75/month poses significant threats to enterprises.
Cisco's research highlights the need for real-time visibility, adversarial testing, and fortified security measures to combat evolving cyber threats.