Topic updates

14 November 2025
Submissions to call HORIZON-CL3-2025-02-CS-ECCC

The call HORIZON-CL3-2025-02-CS-ECCC closed on 12 November 2025.

A total of 265 proposals has been submitted under this call, distributed per topics as follows:

HORIZON-CL3-2025-02-CS-ECCC-01 - Generative AI for Cybersecurity applications: 73 proposals

The evaluation of these proposals will be organized in Q1-2026.

27 June 2025
Updates regarding the call HORIZON-CL3-2025-02-CS-ECCC Annexes

As mentioned in the Work Programme document under the call HORIZON-CL3-2025-02-CS-ECCC topics Eligibility conditions, in order to achieve the expected outcomes, and safeguard the Union’s strategic assets, interests, autonomy, and security, participation in this topic is limited to legal entities established in specific countries.

Furthermore, in order to guarantee the protection of the strategic interests of the Union and its Member States, entities established in an eligible country as described in the Topic Eligibility conditions, but which are directly or indirectly controlled by a non-eligible country or by a non-eligible country entity, shall not participate in the action.

In this context the applicants are requested to fill in the Annex - Ownership Control Declaration.

This request applies to all the HORIZON-CL3-2025-02-ECCC topics excepting the topic HORIZON-CL3-2025-02-ECCC-03.

Generative AI for Cybersecurity applications

TOPIC ID: HORIZON-CL3-2025-02-CS-ECCC-01

Type of grant: Call for proposals

General information

Programme:

Call: Indirectly Managed Action by the ECCC (HORIZON-CL3-2025-01-IM-01)

Type of action: HORIZON-RIA HORIZON Research and Innovation Actions

Type of MGA: HORIZON Action Grant Budget-Based [HORIZON-AG]

Status: Forthcoming

Deadline model: single-stage

Planned Opening Date: 12 June 2025

Deadline dates: 12 November 2025 17:00 (Brussels time)

Topic description

Expected Outcome:

Projects will develop technologies, tools, processes that reinforce cybersecurity using AI technological components, in particular Generative AI, in line with relevant EU policy, legal and ethical requirements.

Proposals should address at least one of the following expected outcomes:

• Developing, training and testing of Generative AI models for monitoring, detection, response and self-healing capabilities in digital processes, and systems against cyberattacks, including adversarial AI attacks.
• Development of Generative AI tools and technologies for continuous monitoring, compliance and automated remediation. These should consider legal aspects of EU and national regulation as well as ethical and privacy aspects.

Scope:

The use of Artificial intelligence is becoming indispensable with applications where massive data is involved. Understanding all implications for cybersecurity requires deeper analysis and further research and innovation.

Generative AI presents both opportunities and challenges in the field of cybersecurity. This topic supports the research on new opportunities brought by Generative AI for Cybersecurity applications, to develop, train and test AI models to scale up detection of threats and vulnerabilities, enhance response time, cope with the large quantities of data involved, and automate process and decision-making support; for example by generating reports from threat intelligence data, suggesting and writing detection rules, threat hunts, and queries for the Security information and event management (SIEM), creating management, audit and compliance reports and reverse engineering malware.

Proposals addressing expected outcome a)

(a) (i) Advanced threat and anomaly detection and analysis: Current cybersecurity tools may struggle to keep pace with the evolving tactics of cyber attackers. Developing, training and testing of Generative AI models can be used to analyse large volumes of data and accurately identify anomalies and deviations from normal patterns of behaviour, enabling more effective threat detection, analysis and response.

Tools should also support cybersecurity professionals as they may struggle to detect and respond to threats posed by generative AI, particularly as these systems become more sophisticated and difficult to distinguish from genuine human activity.

(a) (ii) Adaptive security measures: Cybersecurity tools often rely on static rules and signatures to detect threats, making them less effective against new and evolving attack methods. In addition, many cybersecurity tools still rely on manual intervention for threat response, which can be time-consuming and ineffective. Generative AI, through development, training, finetuning and testing of Generative AI models can support these tools to adapt and respond to emerging threats in real-time, improving overall security posture.

(a) (iii) Enhanced authentication and access control: The use of AI technologies could improve resilience of authentication and access control systems to unauthorized access and credential theft, making it more difficult for unauthorized users to gain access to sensitive information or systems.

Proposals addressing expected outcome b)

(b) (i) Development of tools powered by Generative AI that analyse and facilitate the Application of the national and EU regulation in digital systems, in particular the Artificial Intelligence Act, the Directive on measures for a high common level of cybersecurity across the Union (NIS2) and the Cyber Resilience Act.

(b) (ii) Adaptation to a dynamic environment. Companies, public sector and organisations face an ever-changing environment which makes keeping up with compliance towards cybersecurity rules challenging. On one hand there’s a variety of rules applicable at sectorial, national or European level to be considered. On the other, change management and updates in ICT systems in organisations is frequent. Addressing both facets with tools powered with Generative AI brings the potential for a compliance continuum within organisations otherwise limited in time when driven by human intervention only.

All proposals are expected to respect Trustworthy and Responsible AI principles^[1] and data privacy.

All proposals should demonstrate the EU added value by fostering the development of EU technology, the use of open-source technologies when technically and economically feasible, the exploitation of available EU data (Data Spaces, EOSC, federated data etc)

Proposals should define key performance indicators (KPI), with baseline targets to measure progress and to demonstrate how the proposed work will bring significant advancement to the state-of-the-art. All technologies and tools developed should be appropriately documented, to support take-up and replicability. Participation of SMEs is encouraged.

Proposals are expected to pay special attention to the Intellectual Property dimension of the results. The usability of the outcomes and results once the project is finished will be closely assessed.

[1] https://research-and-innovation.ec.europa.eu/news/all-research-and-innovation-news/guidelines-responsible-use-generative-ai-research-developed-european-research-area-forum-2024-03-20_en

https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence

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