AWS reports AI-augmented attack compromised 600+ FortiGate firewalls

Attack details from AWS incident report
AWS security teams documented a campaign from mid-January to mid-February 2026 where Russian-speaking cybercriminals compromised more than 600 FortiGate firewalls across 55 countries. The attackers used commercial generative AI tools to generate attack playbooks, scripts, and operational notes, enabling a relatively low-skilled group to run what would typically require more resources.
Attack methodology
The campaign focused on scanning for exposed FortiGate management interfaces on the public internet. Attackers then attempted commonly reused or weak credentials. Once inside, they extracted configuration files containing:
- Administrator and VPN credentials
- Network topology details
- Firewall rules
From there, they moved deeper into environments, targeting Active Directory, dumping credentials, and probing for lateral movement opportunities. Backup systems including Veeam servers were also targeted.
AI tooling characteristics
AWS observed that the AI-generated tooling was functional but rough around the edges, with simplistic parsing logic and redundant comments suggesting machine-generated code. The tools were embedded throughout the workflow rather than just used for occasional scripting. CJ Moses, CISO at Amazon, noted: "The volume and variety of custom tooling would typically indicate a well-resourced development team. Instead, a single actor or very small group generated this entire toolkit through AI-assisted development."
Attack patterns and defense
The attackers tended to abandon targets that put up resistance and move on to softer ones, emphasizing volume over finesse. Activity was geographically opportunistic rather than tightly targeted, with victims across Europe, Asia, Africa, and Latin America. Some compromises may have enabled access to managed service providers or larger shared environments, amplifying downstream risk.
AWS emphasized that basic security hygiene would have prevented most compromises:
- Keep management interfaces off the public internet
- Enforce multi-factor authentication
- Avoid password recycling
The findings follow recent warnings from Google about criminals increasingly integrating generative AI directly into operations, including using Gemini AI for reconnaissance, target profiling, phishing, and malware development.
📖 Read the full source: HN AI Agents
👀 See Also

Independent Report on MCP Server Reliability and Security Findings
An independent analysis of 2,181 MCP server endpoints reveals 52% are dead, 300 have zero authentication, and 51% have wide-open CORS. The report includes methodology and a testing tool.

OpenClaw security patches fix QR code credential exposure and plugin auto-load vulnerabilities
OpenClaw released two security patches addressing critical vulnerabilities: QR codes embedded permanent gateway credentials without expiry, and plugins auto-loaded from cloned repos without user confirmation. Version 2026.3.12 fixes both issues.

AI-Built Apps Are Fragile: Why Small Changes Break Data Isolation and Permissions
Developers report that AI-generated apps (via Claude Code, Cursor) silently break login, permissions, and data isolation when small changes are made, because AI models lack understanding of original system intent like ownership rules.

MCPwner AI Pentesting Tool Finds Multiple 0-Day Vulnerabilities in OpenClaw
MCPwner, an MCP server that orchestrates AI agents for automated penetration testing, identified several critical 0-day vulnerabilities in OpenClaw including environment variable injection, permission bypass, and information disclosure flaws that standard scanners missed.