Imagine having a digital security guard that not only spots intruders but also automatically fixes the broken locks they used to get in. It uses smart AI to read security reports and learn how hackers behave before they even strike. This helps critical systems stay running even when under a sophisticated attack.
Cybersecurity teams are overwhelmed by complex, AI-powered attacks and the tedious task of manually finding and fixing code vulnerabilities. Existing tools often lack the speed and automation needed to protect critical infrastructure in real-time.
A suite of AI tools including AI4FIX for automated code correction, AI4VULN for vulnerability identification, AI4SIM for attack simulation, and AI4CTI for threat intelligence extraction using LLMs.
If you are a power grid operator dealing with AI-powered attacks on infrastructure — this project developed a system that detects and mitigates these threats to ensure electricity keeps flowing. It uses AI to increase resilience in critical energy sectors.
If you are a banking provider dealing with vulnerabilities in your mobile apps — this project developed AI4FIX and AI4VULN that automatically identify and fix flaws in the source code. This ensures banking applications can autonomously adapt to face AI-powered attacks.
If you are a hospital network dealing with cyber-physical attacks on medical devices — this project developed a resilience ecosystem that protects critical hospital services. It helps operators manage dynamic responses to advanced threats.
Based on available project data, no specific pricing or commercial cost models are mentioned; the project was funded by an EU contribution of EUR 3,998,413.
Yes, the project was validated in three large-scale scenarios: the energy sector, banking applications, and hospital services.
Based on available project data, specific licensing terms are not provided, but the project involved 12 industry partners, including 8 SMEs.
The system includes response automation services to optimize the orchestration of security protections and leverages Large Language Models to extract knowledge from open security advisories.
Yes, the project specifically adhered to EU policy, legal, and ethical requirements for AI, focusing on explainability and fairness.
The consortium is heavily industry-driven, with 12 out of 15 partners coming from the commercial sector (80% industry ratio). The presence of 8 SMEs suggests the technology is designed for commercial viability and agility, rather than just academic research, with a geographical spread across 7 EU countries.
Contact Fundacion Tecnalia Research & Innovation in Spain
Contact us to connect with the AI4CYBER industrial partners for licensing.
