SciTransfer
Organization

STICHTING THE SHADOWSERVER FOUNDATION EUROPE

Nonprofit operating one of Europe's largest internet threat monitoring networks, providing free malware and botnet intelligence feeds to CERTs and network operators.

NGO / AssociationsecurityNLSMENo active H2020 projects
H2020 projects
2
As coordinator
0
Total EC funding
€1.9M
Unique partners
18
What they do

Their core work

Shadowserver Foundation Europe operates one of the world's most extensive passive internet threat monitoring infrastructures — a global network of darknets, honeypots, sandboxes, and sensors that continuously collect data on botnets, malware campaigns, and malicious traffic. They process this data and distribute free remediation feeds to network operators, CERTs, ISPs, and national cybersecurity agencies, enabling organizations worldwide to detect compromised systems on their networks at no cost. In H2020 projects, they function as the bridge between academic research and live operational threat data — bringing real-world malicious traffic datasets and sensor infrastructure that no university lab can replicate. Their nonprofit community-benefit model sets them apart from commercial threat intelligence vendors: the data flows freely to those who can act on it.

Core expertise

What they specialise in

Internet threat sensor infrastructure (darknets, honeypots, sandboxes)primary
2 projects

SISSDEN was built around deploying a large sensor network for new threat data feeds, curated datasets, and long-term botnet tracking.

Malware analysis and botnet trackingprimary
1 project

SISSDEN explicitly targeted improved malware analysis and long-term botnet tracking as core deliverables.

Cyber threat intelligence feeds and community sharingprimary
2 projects

Both projects reference free remediation feeds and curated datasets distributed for community benefit, which mirrors Shadowserver's core operational mission.

SOC and CSIRT decision support toolingsecondary
1 project

SOCCRATES focused on monitoring and response workflows for SOC and CSIRT operators, incorporating business impact modelling and course-of-action recommendations.

AI and machine learning for threat predictionemerging
1 project

SOCCRATES introduced AI/ML-driven threat prediction and attack defence graph analysis, marking a shift toward automated intelligence processing.

Evolution & trajectory

How they've shifted over time

Early focus
Internet threat sensor infrastructure and feeds
Recent focus
Operational threat intelligence for SOC and CSIRT

In the earlier period (SISSDEN, 2016–2019), the focus was squarely on infrastructure: building and operating the sensor network itself — honeypots, sandboxes, darknets — and generating raw threat feeds for community distribution. The work was about collection scale and data quality. By the later project (SOCCRATES, 2019–2022), the emphasis shifted downstream toward operational use of that data: how do SOC analysts and CSIRTs actually respond to what the sensors detect? This brought in business impact modelling, attack defence graphs, and AI-driven prediction — applying intelligence rather than just gathering it.

Shadowserver Europe is moving from raw data provider toward integrated intelligence partner — future collaborations will likely involve automated threat response pipelines, AI-driven incident prioritization, and tooling directly embedded into security operations workflows.

Collaboration profile

How they like to work

Role: infrastructure_providerReach: European12 countries collaborated

Shadowserver Europe participates exclusively as a specialist partner, never as project coordinator — consistent with an organization whose value lies in contributing unique operational infrastructure rather than managing research consortia. Despite only two projects, they engaged 18 distinct partners across 12 countries, indicating comfort with large, diverse European consortia. They are a sought-after contributor: partners come to them for the one thing no one else can provide — live, large-scale internet threat data from a trusted nonprofit source.

Across two projects, Shadowserver Europe built connections with 18 unique partners in 12 countries — a notably broad network for such a small project portfolio, pointing to high demand for their data infrastructure across European security research groups. No geographic concentration is visible from the data, reflecting their pan-European threat monitoring mandate.

Why partner with them

What sets them apart

Shadowserver Foundation is one of the few organizations in Europe that operates genuine large-scale passive internet monitoring infrastructure as a nonprofit — this is not a commercial intelligence product, but a community service, which gives their data a credibility and accessibility that vendor feeds lack. For a consortium, they offer something irreplaceable: access to continuously updated, real-world botnet and malware telemetry that would take years and millions to build independently. No other H2020 participant brings both the operational scale and the community-neutral positioning that Shadowserver does in the cybersecurity space.

Notable projects

Highlights from their portfolio

  • SISSDEN
    The largest-funded project (EUR 1.5M) and the one that most directly maps to Shadowserver's core mission — deploying a pan-European sensor network for malware and botnet tracking with freely distributed remediation feeds.
  • SOCCRATES
    Marks a strategic pivot toward operationalizing threat intelligence for SOC and CSIRT teams, introducing AI/ML and business impact modelling — signalling where Shadowserver's research agenda is heading.
Cross-sector capabilities
Digital infrastructure and network operationsAI and machine learning applied to threat dataPublic sector cybersecurity and critical infrastructure protection
Analysis note: Only 2 projects in the dataset, which limits statistical confidence. However, Shadowserver Foundation is a well-established and distinctive organization in the global cybersecurity community — the project keywords align precisely with their known real-world mission, so the qualitative profile is reliable despite the thin project count. Confidence is capped at 3 due to limited H2020 data volume, not due to ambiguity about their work.