EuRepoC Data


We offer these databases in three different variants within the CSV downloads. 


Primary Dataset

The primary dataset contains one cyber incident per row and is best suited for all general purposes. The other two datasets are best suited for academics with more specific research interests.


Attribution Dataset

These attribution-based datasets focus on heterogeneity in attributions and therefore contain columns for all attributions that have been coded by EuRepoC. 


Receiver Dataset

These receiver-based datasets focus on the multitude of receivers which were targeted in cyber incidents. For each cyber incident, all receiver countries are referenced in columns and additional columns contain detailed information on the receiver(s).

EuRepoC Global Database 1.0

This overall dataset of EuRepoC contains all coded cyber incidents, regardless of the identified attackers or victims. It thus represents the central "data lake" from which all other data-based analysis products of the project are fed. The dataset, spanning from 2000 to the present, is based on the interdisciplinary, continuously-evaluated, and improved EuRepoC Codebook.

EuRepoC Global Database 1.0 (CSV)

EuRepoC EU Database 1.0

To specifically record and analyse the “cyber threat environment” within or in relation to the European Union, EuRepoC offers an additional EU-focused dataset. It is part of the overall dataset but concentrates on cyber incidents with at least one EU member state among the victims, from 2000 to the present. This allows for the comparison of the international and the regional European cyber conflict landscape.

HD-CY.CON Global Database 1.0

As a predecessor project of EuRepoC, a separate cyber conflict dataset, HD-CY.CON 1.0, was created at Heidelberg University from 2019 to 2021. This dataset, spanning 2000 to 2019, was integrated into EuRepoC and was refined and extended in terms of the coding scheme applied. This was achieved particularly through the increased interdisciplinarity of the coding manual and the increased automated data collection and processing.