KEY FACTS
Beyond the Basics: Mission, Objectives, Use Cases and Results
The project integrates attack simulation, defense optimisation, and automated response within a secure, privacy-compliant architecture to deliver scalable protection against evolving cyber threats, including those targeting AI systems.
FACTS
Duration
36 months
■
Start & End Date
Jan 1 2026 – 2028 Dec 31
■
Total Budget
5.1 M Eur
■
EU budget Contribution
3.5 M Eur
OUTCOMES
AIAGENT4CYBER delivers an advanced multi-agent AI framework that enhances real-time threat detection, improves the identification of emerging and previously unseen cyberattacks, and enables faster, more coordinated response mechanisms.
The project provides validated, scalable cybersecurity capabilities designed for critical and essential digital infrastructures, operating within a secure and privacy-compliant framework.
■
■
IMPACT
By strengthening detection, response and prevention capabilities, AIAGENT4CYBER contributes to increased operational resilience across Europe’s public sector and critical services.
The project supports a shift toward proactive, AI-driven cybersecurity, reduces exposure to evolving threats, and reinforces Europe’s strategic capacity to secure its digital infrastructure in line with EU regulatory and trust frameworks.
■
■
TARGET SECTORS
AIAGENT4CYBER supports organisations operating in high-risk and high-importance digital environments where resilience, compliance and operational continuity are critical.
Public Authorities
National, regional, and local government and public sector institutions.
Critical Infrastructure
Energy, transport, water, and telecom networks.
Essential Service Providers
National, regional, and local government and public sector institutions.
AI-Enabled &
Data-Intensive Environments
AI systems and high-performance digital infrastructures.
How We Deliver
AIAGENT4CYBER translates advanced research into operational cybersecurity capabilities through four core pillars:
The system is developed in line with EU data protection and regulatory standards and validated through real-world use cases to ensure operational readiness and resilience.
04
Trustworthy and Validated Deployment
A flexible, sector-agnostic design ensures deployment across diverse digital environments, while enabling coordinated decision-making between specialised AI agents.
03
Scalable & Collaborative Architecture
Adaptive AI-driven mechanisms support rapid containment and mitigation of incidents, reducing response times and limiting potential impact.
02
Proactive & Automated Response
A coordinated multi-agent AI framework enables continuous monitoring, anomaly detection, and real-time identification of emerging cyber risks.
01
Intelligent Threat Detection
DEMONSTRATIONS
Use Cases
Use case 1
This use case demonstrates how coordinated AI agents can autonomously assess system security and identify potential vulnerabilities before they are exploited. The approach enables continuous and adaptive security testing, helping organisations strengthen their defences against evolving cyber threats and reduce risk exposure over time.
Use case 2
This use case demonstrates how coordinated AI agents can detect and analyse malicious software in real time. By combining multiple intelligent capabilities, the system provides a comprehensive understanding of suspicious behavior and potential impact, enabling faster and more informed responses to emerging threats.
Use case 3
This use case explores how coordinated AI agents can streamline and automate incident management in cybersecurity. The system supports rapid detection, assessment and response, reducing reaction times and limiting potential impact. Through continuous learning and adaptation, it enhances resilience against evolving and emerging cyber threats.
Use case 4
This use case demonstrates how coordinated AI agents can support the early identification and assessment of security weaknesses across digital infrastructures. By enabling continuous monitoring and risk evaluation, the approach strengthens preventive capabilities and reduces exposure to potential cyber threats.
Use case 5
This use case explores how advanced AI techniques can strengthen predictive cybersecurity capabilities in complex digital environments. By combining structured knowledge modelling with intelligent pattern analysis, the approach enhances the detection of unusual behaviour and potential security risks before they escalate.