Hackers using AI breach 600 FortiGate firewalls in 5 weeks by exploiting weak credentials

Reviewed byNidhi Govil

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A Russian-speaking hacker used commercial generative AI tools to compromise more than 600 FortiGate firewalls across 55 countries in just five weeks, according to Amazon security research. The attacker exploited weak credentials and single-factor authentication rather than advanced vulnerabilities, demonstrating how AI is lowering the barrier for threat actors to scale attacks rapidly.

Hackers Using Artificial Intelligence Compromise Hundreds of Devices

A small group of hackersβ€”possibly just one personβ€”leveraged commercial generative AI services to execute an AI cyberattack that compromised more than 600 FortiGate firewalls across 55 countries between January 11 and February 18, 2026, according to security research from

Amazon

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. The breach of FortiGate firewalls represents a significant escalation in how threat actors are exploiting weak security measures to conduct operations at unprecedented scale. CJ Moses, who leads security engineering and operations at Amazon, characterized the campaign as "an AI-powered assembly line for cybercrime, helping less skilled workers produce at scale."

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Source: Analytics Insight

Source: Analytics Insight

Exploiting Weak Security Measures Rather Than Zero-Day Vulnerabilities

The AI-assisted hacking campaign did not rely on sophisticated exploits or zero-day vulnerabilities. Instead, the Russian-speaking actor targeted exposed management interfaces running on ports 443, 8443, 10443, and 4443, using brute-force attacks with common passwords to gain access

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. The attacker specifically sought out devices protected by weak credentials and single-factor authentication, demonstrating opportunistic rather than targeted behavior. When encountering more hardened network security, the hackers simply moved on to other targets rather than persisting

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. The compromised devices were spread across South Asia, Latin America, the Caribbean, West Africa, Northern Europe, and Southeast Asia.

Scaling Attacks with AI Through Automated Tools

Once inside the networks, the attacker extracted configuration files containing VPN credentials, SSL certificates, and authentication tokens, then used AI-assisted Python and Go tools to parse and decrypt this data

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. Analysis of the attack scripts revealed clear indicators of AI-generated code, including redundant comments that merely restated function names, simplistic architecture with disproportionate investment in formatting over functionality, and naive JSON parsing via string matching rather than proper deserialization

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. The reconnaissance tools automated network analysis by examining routing tables, classifying networks by size, running port scans, identifying SMB hosts and domain controllers, and using Nuclei to search for HTTP services.

Source: BleepingComputer

Source: BleepingComputer

AI Accelerating Cybercrime and Ransomware Preparation

The threat actor's operational documentation, written in Russian, detailed plans for lateral movement within victim networks and preparations for potential ransomware deployment. The campaign specifically targeted Veeam Backup & Replication servers using custom PowerShell scripts and attempted to exploit vulnerabilities including CVE-2023-27532 and CVE-2024-40711

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. Targeting backup infrastructure before deploying ransomware prevents victims from restoring encrypted files from backups. In one instance, the actor submitted a full internal victim network topology, including IP addresses, hostnames, credentials, and known services, to an AI service and requested assistance spreading further into the network

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Lowering the Barrier for Threat Actors

The campaign demonstrates how commercial generative AI services are fundamentally changing the threat landscape by enabling low-to-medium-skilled actors to conduct operations that would previously require larger, more skilled teams. The threat actor utilized at least two large language model providers to generate code, debug scripts, and plan attack strategies

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. While the tools were functional for specific use cases, they lacked robustness and commonly failed under edge casesβ€”characteristics typical of AI-generated code used without significant refinement. Moses noted that "organizations should anticipate that AI-augmented threat activity will continue to grow in volume from both skilled and unskilled adversaries."

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This incident follows a 2025 case where a hacker leveraged technology from Anthropic PBC as part of a vast cybercrime scheme impacting at least 17 organizations

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. Amazon recommends that FortiGate administrators avoid exposing management interfaces to the internet, enable multi-factor authentication, ensure VPN passwords differ from Active Directory credentials, and harden backup infrastructure

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