Cybercriminals using readily available generative AI tools managed to breach more than 600 internet-facing FortiGate firewalls across 55 countries within a little over a month, according to a recent incident analysis released by Amazon Web Services (AWS).
The operation, active between mid-January and mid-February, did not rely on sophisticated zero-day vulnerabilities. Instead, attackers automated large-scale attempts to access exposed systems by rapidly testing weak or reused credentials—essentially the digital equivalent of trying every unlocked door, but at high speed with the assistance of AI.
AWS investigators believe the operation was carried out by a financially motivated Russian-speaking group. The attackers scanned for publicly accessible FortiGate management interfaces, attempted to log in using commonly reused passwords, and once successful, extracted configuration files that provided detailed insight into the victims’ network environments.
According to AWS’s security team, the threat actors leveraged multiple commercially available AI tools to produce attack playbooks, scripts, and operational documentation. This allowed a relatively small or less technically advanced group to conduct a campaign that would typically require greater manpower and development effort. Analysts also discovered traces of AI-generated code and planning materials on compromised systems, indicating that AI tools were used extensively throughout the operation rather than just for occasional scripting tasks.
"The volume and variety of custom tooling would typically indicate a well-resourced development team," said CJ Moses, CISO at Amazon. "Instead, a single actor or very small group generated this entire toolkit through AI-assisted development."
After gaining access to the firewalls, the attackers retrieved configuration data containing administrator and VPN credentials, network architecture information, and firewall policies. Armed with these details, they attempted deeper intrusions by targeting directory services such as Active Directory, harvesting credentials, and exploring options for lateral movement across compromised networks. Backup infrastructure, including servers running Veeam, was also targeted during the intrusions.
AWS researchers noted that although the tools used in the campaign were functional, they appeared somewhat crude. The scripts showed basic parsing methods and repetitive comments often associated with machine-generated drafts. Despite their imperfections, the tools proved effective enough for large-scale automated attacks. When systems proved difficult to compromise, the attackers often abandoned them and shifted focus to easier targets, suggesting that their strategy prioritized volume over precision.
The affected organizations were spread across several regions, including Europe, Asia, Africa, and Latin America. The activity did not appear to focus on a single sector or country, indicating opportunistic targeting. However, investigators observed clusters of incidents suggesting that some breaches may have provided access to managed service providers or shared infrastructure, potentially increasing the scale of downstream exposure.
AWS emphasized that many of the compromises could have been avoided with standard cybersecurity practices. Preventing management interfaces from being publicly accessible, implementing multi-factor authentication, and avoiding password reuse would have significantly reduced the attackers’ chances of success.
The report comes shortly after Google cautioned that cybercriminal groups are increasingly integrating generative AI technologies—including tools such as Gemini AI—into their operations. These technologies are being used for tasks such as reconnaissance, target profiling, phishing campaign creation, and malware development
