text: www.enisa.europa.eu European Union Agency For Network and Information Security

text: ENISA’s PETs Maturity Assessment Repository final | RESTRICTED | November 2018

text: Regulation (EU) 679/2016

text: of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive

text: (General Data Protection Regulation), http://eur-lex.europa.eu/legalcontent/EN/TXT/PDF/?uri=CELEX:32016R0679&from=en

text: Yoo, C.S., Moore’s law, Metcalfe’s law, and the theory of optimal interoperability, 14 Colo. Tech. L.J. 87 (2015). See, also Spulber Daniel F, Yoo, C.S., Networks in telecommunications, Cambridge University Press (2009).

text: Figure 1: Snapshot of the PETs Repository

text: https://www.enisa.europa.eu/publications/pets http://pets.enisa.europa.eu/#/repository See “Readiness Analysis for the Adoption and Evolution of PETS”(March 2016), http://pets.enisa.europa.eu/#/repository

text: Figure 2: Overview of Possible PET Maturity Level Values

text: Figure 3: Overview of the assessment process

text: Web address of the maturity assessment tool: http://pets.enisa.europa.eu/

text: Regulation (EU) 2016/679

text: of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data: https://eurlex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32016R0679

text: The Annual Privacy Forum is a series of conferences organized annually across the EU that seek to bring together privacy experts from academia, policy and the private sector. ENISA is the brand owner and the main driving entity behind the Annual Privacy Forum. See also, https://2018.privacyforum.eu IPEN is a series of workshops, organised annually by the European Data Protection Supervisor, that seek to bring together privacy experts associated with public authorities, industry, academia and civil society. The scope of the IPEN workshops is to discuss relevant challenges and developments with regard to the implementation of data protection and privacy. See, https://edps.europa.eu/data-protection/our-work/ipen/ipen-privacy-engineeringworkshop-2018_en

text: Hansen M. (2012) Top 10 Mistakes in System Design from a Privacy Perspective and Privacy Protection Goals. In: Camenisch J., Crispo B., Fischer-Hübner S., Leenes R., Russello G. (eds) Privacy and Identity Management for Life. Privacy and Identity 2011. IFIP Advances in Information and Communication Technology, vol 375. Springer, Berlin, Heidelberg https://www.iese.fraunhofer.de/en/competencies/security/ind2uce-framework.html https://privacyflag.eu

text: 16 I2P , TOR , Free Proxy servers: These 3 Protocols implement the same high-level functionality, that is anonymous communication. They should be among the test candidates to evaluate the capabilities to compare PETs using the platform. It is expected that TOR and I2P differ largely in their market readiness. At the same time, Free Proxy services most likely will contrast to the other two with regard to their quality score.

text: https://privacybydesign.foundation/irma/ https://geti2p.net/en/ https://www.torproject.org

text: https://www.linkedin.com/ https://www.researchgate.net

text: ENISA’s PETs Maturity Assessment Repository

text: final | RESTRICTED | November 2018

text: final | RESTRICTED | November 2018

text: final | RESTRICTED | November 2018

text: PROJECT FUNDING PROJECT PROJECT COORDINATOR WEBPAGE ACRONYM AGENCY DURATION

text: Architecture TAS3 31/12/2007for Securely EU FP7 KUL http://www.tas3.eu 30/12/2011 Shared

text: PrimeLife 29/02/2008- PrimeLife EU FP7 IBM http://primelife.ercim.eu 27/02/2011

text: PrivacyOS 31/05/2008- Privacy OS CIP 30/05/2010

text: Security and

text: SPION Privacy for 27/12/2012- IWT KUL Online Social 30/12/2014

text: PRIvacy &

text: Security AIT AUSTRIAN PRISMACLOUD 01/2/201- MAintaining H2020 INSTITUTE OF https://prismacloud.eu 31/7/2018 Services in the TECHNOLOGY

text: PrivacyFlag 01/5/2015- H2020 OTE https://privacyflag.eu 01/05/2018

text: SAINT NCSR 01/5/2017- H2020 https://project-saint.eu “Demokritos” 30/4/2019

text: AIT AUSTRIAN Credential Secure Cloud 01/10/2015- H2020 INSTITUTE OF https://credential.eu Identity Wallet 30/9/2018 TECHNOLOGY

text: iNFormatIon MINISTERO SUNFISCH SHaring in 01/1/2015- H2020 DELL'ECONOMIA E http://www.sunfishproject.eu federated 31/12/2017 DELLE FINANZE heterogeneous

text: private clouds

text: Coordination KATHOLIEKE ECRYPT-CSA 1/3/2015and Support H2020 UNIVERSITEIT http://www.ecrypt.eu.org 28/2/2018 Action in LEUVEN

text: final | RESTRICTED | November 2018

text: Industry to

text: Privacy-by- PRIPARE 01/10/2013– design by FP7 TRIALOG http://pripareproject.eu 30/09/2015 supporting its

text: Application in

text: transparency FUNDACIO TYPES 1//05/2015and privacy in H2020 BARCELONA http://www.types-project.eu 31/10/2017 the online MEDIA

text: Decentralised INSTITUT 2016-12-01 DECODE Citizens MUNICIPAL H2020 to 2019-12- https://decodeproject.eu Owned Data D'INFORMATICA 31 Ecosystem DE BARCELONA

text: Surveillance, OESTERREICHISCHE SurPRISE 01/2/2012- Privacy and FP7 AKADEMIE DER http://surprise-project.eu 31/1/2015 Security WISSENSCHAFTEN

text: Visual Privacy

text: Management VisiOn 1/7/2015in User Centric H2020 BUSINESS-E SPA http://www.visioneuproject.eu 30//6/2017 Open

text: Online Privacy OXFORD Enforcement, Operando COMPUTER 01/5/2015- https://www.operando.eu/servizi/ Rights H2020 CONSULTANTS 30/4/2018 notizie/ notizie_homepage.aspx Assurance and LIMITED Optimization

text: Privacy and

text: Panoramix in Networks THE UNIVERSITY 01/9/2015- http://www.panoramix- H2020 via Optimized OF EDINBURGH 31/1/2019 project.eu/

text: INESC TEC -

text: Secure and INSTITUTO DE SafeCloud 01/9/2015- Resilient Cloud H2020 ENGENHARIA DE https://www.safecloud-project.eu 31//8/2018 Architecture SISTEMAS E

text: final | RESTRICTED | November 2018

text: ORGANIZATION Industry Jolla Qwant Fsecure Fraunhofer iese Fraunhofer sit Fsecure Regulatory body EDPS ULD (Unabhängige Landeszentrum für Datenschutz) FICORA Cybersecurity Center NL NGO Humboldt Institute for Internet and Society (HIIG) EastWest Institute (EWI) Academia University of Luxemburg KUL Technische Universität Dresden (TUD) TU Darmstadt Radboud University Nijmegen (RU) UC Uni Hamburg Technical University of Madrid (UPM, Universidad Politécnica de Madrid) EU Project PrivacyFlag

text: final | RESTRICTED | November 2018

identifier: ENISA’s PETs Maturity Assessment Repository

publisher: Europeiska unionens cybersäkerhetsbyrå

sprak: en

title: ENISA’s PETs Maturity Assessment Repository

serie: rapporter

text: Populating the Platform

type: rubrik

text: FINAL RESTRICTED NOVEMBER 2018 About ENISA

text: The European Union Agency for Network and Information Security (ENISA) is a centre of network and information security expertise for the EU, its member states, the private sector and EU citizens. ENISA works with these groups to develop advice and recommendations on good practice in information security. It assists member states in implementing relevant EU legislation and works to improve the resilience of Europe’s critical information infrastructure and networks. ENISA seeks to enhance existing expertise in member states by supporting the development of cross-border communities committed to improving network and information security throughout the EU. More information about ENISA and its work can be found at www.enisa.europa.eu.

type: stycke

text: Contact

text: For queries in relation to this paper, please use isdp@enisa.europa.eu For media enquires about this paper, please use press@enisa.europa.eu.

text: Legal notice Notice must be taken that this publication represents the views and interpretations of ENISA, unless stated otherwise. This publication should not be construed to be a legal action of ENISA or the ENISA bodies unless adopted pursuant to the

text: Regulation (EU) No 526/2013

text: . This publication does not necessarily represent state-of the-art and ENISA may update it from time to time.

text: Third-party sources are quoted as appropriate. ENISA is not responsible for the content of the external sources including external websites referenced in this publication.

text: This publication is intended for information purposes only. It must be accessible free of charge. Neither ENISA nor any person acting on its behalf is responsible for the use that might be made of the information contained in this publication.

text: Copyright Notice © European Union Agency for Network and Information Security (ENISA), 2018 Reproduction is authorised provided the source is acknowledged.

text: Table of Contents

text: Executive Summary 5

text: 1. Introduction 6 Background 6 Scope and objectives 7 Outline 7

text: 2. ENISA’s PETs Maturity Assessment Repository 8 The notion of state-of-the-art in PETs 8 2.1.1 Network effect 9 The Pets Maturity Assessment Repository 10 2.2.1 The current implementation 13

text: 3. Approaching test users and populating the platform 14 Purpose of the proposed approach 14 3.1.1 Test aims 14 Stakeholders and test users 15 3.2.1 Test users 15 3.2.2 Approaching prospective users 16 3.2.3 Targeted Events 16 Selection Criteria PETs 16 3.3.1 Selecting test cases to test the platform software and evaluation method 16 3.3.2 Selecting PETs to populate the platform – Criteria 17 3.3.3 Selected Test Candidates 17

text: 4. Observations from the test phase and user feedback 19 Communication strategy 19 Concept of the PETs repository 19 Design and technical aspects of the platform 19

text: 5. Recommendations for Next Steps 21 Communication Strategy 21 5.1.1 Duration 21 5.1.2 Social networks 21 5.1.3 Dedicated events 22 5.1.4 PR expert consultancy 22 Solving usability issues 22 Distribution strategy 23

text: Annex A: Marketing efforts 24 Annex B: List of projects and possible use cases 26 Annex C: List of stakeholders 28

text: Executive Summary

text: Despite the apparent availability of knowledge about different privacy enhancing methods, tools and technologies, it is still hard to select the most appropriate one. It is even harder to compare and justify which solution is the best for a particular problem, IT environment or user advancement level. Therefore, there is a need for standardisation and centralisation of Privacy Enhancing Technologies (PET) knowledge, as well as for a widely-accepted methodology for the evaluation of such technologies. The common adoption of a PETs maturity assessment methodology and a unified way to describe a particular PET would improve the situation significantly.

text: ENISA started in 2016 the development of a web application prototype, called the “PET maturity assessment online repository” (hereinafter ‘PETs repository’ or ‘PETs platform’) following the recommendations made by a comprehensive methodology for PETs developed the previous years. This platform aims at providing an IT service, which will facilitate the formation of community that is able to maintain a repository of PETs assessments and a tool that will support maturity assessment methodology by implementing a systematic collaborative process.

text: Therefore, this report reflects the plan to formulate such a community, which would support the establishment of the PETs repository and would help in the testing of the maturity assessment methodology and the platform itself, as well as the experiences gained during the effort.

text: Moreover, the report shows that, in the framework of the six-month project period and despite a specific planning towards community building, the update of the PETs repository was rather low. This was due to several reasons, including communication strategy, technical implementation, as well as the overall approach taken.

text: In particular, considering feedback and observations throughout the 6-month project period, we come to the following conclusions and recommendations:

text:  Taking into account the network effect principles, it was concluded that the initial population of such a platform will take quite a long period. It is recommended that a different framework than a project to be used to further create the community (e.g. direct engagement of specific experts in the field).  User feedback indicated that a clear branding of the platform would improve the soft trust factors. It is recommended that a clear entity is adopted as owner of the platform or that the platform is integrated in ENISA’s corporate identity.  User feedback also indicated that design and other technical aspects might have also affected the platform’s uptake. It is recommended that, if the PETs repository is to be further promoted, more effort to be put on its technical implementation and maintenance.

text: This report is an internal ENISA document that, based on the aforementioned conclusions, aims to support further decision making within ENISA with regard to the PETs repository.

text: 1. Introduction Background

text: For these reasons, in 2015 ENISA developed a comprehensive methodology for PETs maturity assessment. Under this study, the following recommendation was made:

text: “A community portal should be established that is used to publish tools and their assessment results. The European Commission should facilitate the forming of the portal”.

text: Following this recommendation, ENISA started in 2016 the development of a web application prototype, called the “PET maturity assessment online repository” (hereinafter ‘PETs repository’). This work was finalised in 2017 with an updated version of the tool (a test platform is available under http://pets.enisa.europa.eu). This tool aims at providing an IT service, which will facilitate the formation of a community that is able to maintain a repository of PETs assessments and a tool that will support maturity assessment methodology by implementing a systematic collaborative process.

text: Following the PETs repository development and update, one of the key challenges identified is the community building around this tool. In particular, it was considered of upmost importance not only to disseminate relevant information, but also to actively engage relevant stakeholders in the use and promotion of the tool (as evaluators, PETs providers or simple users of the tool). In this way, the tool can pave the way towards establishing a reliable repository of technologies, which can also support data controllers in the adoption of technical and organisational measures, as stipulated in articles 25 and 32 of the General Data Protection Regulation (GDPR) .

text: Against this background, ENISA decided under its 2018 work-programme to continue this work and particularly focus on community building and testing of the PETs repository, in co-operation with relevant stakeholders. As ENISA is expected to provide guidance on aspects of network and information security policy in the EU, it is logical that addressing particular areas of interest in designated policy areas including privacy and data protection is a reasonable extension of its work and it meets stakeholder requirements. The expected outcome of this work is that greater understanding by means of analysis can be reached and that gaps can be identified in a way that, if shared with institutional and private stakeholders, suitable measures can be put in place. As a result, stakeholders interested in network and information security

text: measures concerning PETs, can get better control and enhance their ability to mitigate successfully the risks identified.

text: Scope and objectives

text: The project’s overall scope was to promote the ENISA’s PETs repository (and underlying PETs maturity assessment methodology) by:

text:  Engaging the privacy community into its use, and  Providing a plan for its future enhancement and wider adoption.

text: In order to engage the privacy community, a list of stakeholders would form an essential part of the project, together with their engagement in the population of the PETs repository with a number of specific use cases. The final scope would be to present an updated PETs repository populated with new content.

text: In order to achieve the aforementioned objectives, ENISA established a direct contract with the University of Luxembourg that has proven expertise on the subject matter.

text: The present report aims at detailing the outcomes of the project vis ā vis the aforementioned objectives.

text: Note: this is an internal ENISA document that aims to support decision making within ENISA with regard to the future of the PETs repository. The document will not be published on the ENISA website.

text: Outline

text: In the remainder of this report, the proposed approach to form a PETs maturity assessment community to test ENISA’s platform is further examined and analysed.

text: After an initial presentation of ENISA’s PETs maturity assessment repository (Chapter 2), the analysis sets off with the selection criteria to determine which experts should be approached and which test cases should be used (Chapter 3). Moreover, the main outcomes of this exercise and the feedback of the approached experts is summarized (Chapter 4). A proposal for potential approaches is further suggested in a way that future work can be laid out (Chapter 5).

text: The report closes with a proposed roadmap that aims at providing new directions for the future of this line of work in relation to PET assessments. Parties to be involved in such work include ENISA of course, but representatives of the PETs community can also be seen as contributors thereto. The report also includes an estimate of the needed effort to accomplish the desired outcomes. Should ENISA choose to pursue this course it would be important to carefully choose its stakeholders that are willing and able to contribute further. Clearly, the strategic orientation of such an activity needs to be carefully assessed prior to any concrete action being taken within the network and information security boundaries.

text: 2. ENISA’s PETs Maturity Assessment Repository

text: In an effort to put the project into context, in this Chapter the legal framework and relevant requirements are first briefly sketched; then the purpose of the PETs maturity assessment concept and web platform is presented, together with its main functionalities (as developed in the context of past ENISA’s projects). Since this presentation is a broad outline of the project, this report also makes available a number of relevant references for the reader new to the topic.

text: The notion of state-of-the-art in PETs

text: In its Art. 25, the GDPR mandates that controllers of data processing consider, among others, the technological state of the art when defining means for data processing and during the data processing itself. While the state of the art is also mentioned in Art. 32 on security of processing and in Recitals 78 and 83, a definition comparable to those in Art. 4 e.g. personal data or processing is missing.

text: Furthermore, the requirement to employ state-of- the-art technologies to protect personal data is a conditional one and it depends on the dynamics of technology and business processes in any given assessment period. Clearly, the legislator had an interest in retaining options open to accommodate improvements over time, rather than setting a deterministic level of security that would become obsolete over time. According to Art. 25 and Art. 32, state-of- the-art technologies should be balanced against the ‘costs of implementation, the nature, scope, context and purposes of the processing as well as the risks [...] and severity for the rights and freedoms of natural persons’ posed by the processing.

text: Controllers and processors in charge to ensure compliance with the GDPR have to determine which stateof- the-art solutions to consider depending on their means. This is so far a challenging task due to several factors, among them there are 1) a missing definition of what the state-of- the-art, entails 2) the unavailability of ample guidance and case law on this matter, and 3) a lack of experience, as the GDPR is a legislative instrument that only recently (25 May 2018) started applying. Moreover, with no administratively set body in charge to establish the state-of- the-art, eventually the European Court of Justice much like Courts in the MS, are likely to be asked to determine on a case-by-case basis the minimum requirements concerning the state-of- the-art. A first step in this direction would be a clear formal process to determine a state-of- the-art repository with regard to available technological solutions.

text: Technology, and as such the state-of- the-art, is the subject of continuous research by public and private actors and it evolves in time. As a result, compliance considering the state-of- the-art emerges as a moving target. Emerging new technology may increase the risk of data breaches throughout the life time of a product or service. For instance, the availability of faster and cheaper computing resources may allow attackers to break encryption methods, which were considered secure at a certain moment in time. To ensure a constant low risk level of data breaches, the encryption of already encrypted data must be strengthened over time considering the current state-of-the-art.

text: One can also expect interferences with intellectual property law and competition law. For instance, consider a state-of-the-art privacy engineering tool that is proprietary and only offered by a single vendor to competitors under abusive conditions. With a legal requirement to deploy state of the art technology, this situation can be compared to expensive patented products (e.g. pharmaceuticals providing the only cure available for certain diseases). Only in addition those competitors that are unable or unwilling to adapt to the state-of-the-art proprietary or non- proprietary privacy enhancing tool may face market or even legal risks for their practices.

text: To balance the efforts towards data protection and risks for data breaches, but also for the privacy risk assessment, the risk must be measured and warranted in the first place. Standardisation and privacy design patterns may simplify this difficult task. Then, even the automation of a risk assessment may be eventually feasible. Risk assessment automation would also benefit the continuous re-assessment of risks throughout the life time of a product or service.

text: 2.1.1 Network effect

text: From a different standpoint, a PETs platform can be seen as leveraging on the network effect. A test user enrolling and submitting his or her sample PET product demonstrates a positive external impact. The immediate interest is to solve one’s own problem, being mainly confined to seeking feedback on the PET product itself. At a secondary level however, value is equally created for other users. This value is associated with the type of feedback recorded, with the opening up of the features and/or code of the PETs tool as well as by the sheer participation in an exchange platform. This last feature gives the certainty and/or expectation of value that can be created by simply tapping into the intellectual resources of the participants, being their analytical capabilities and their interest in providing feedback. The model is not substantially different from those created in the telephone network systems; the approach follows on the footsteps of social networks that work similarly and increase in value and prominence for each member as more users enroll.

text: In other words, and in terms put by Metcalfe’s Law the number of potential connections on a network increases quadratically with the number of nodes. Expanding the number of potential connections increases the value of a network and in line with Metcalfe’s Law the growth in network size will be economically beneficial.

text: In the platform paradigm the key components are (a) users (b) PETs submitted (c) a format of PETs that can be processed by humans, even with the support of tools. Therefore a positive value effect can be expected when there is an increase in either (a) or (b). There is need of course to meet condition (c) to facilitate reviews and assessments. It is to be expected that as the network becomes more valuable for its enrolled users then more users will join. This can be conditioned with the relative smallish size of the PET community. In any case, however the sheer increase in numbers is likely to result in positive feedback loops that can increase the value of the platform as a whole.

text: So far, different concepts and methodologies exist that make it possible to break down legal high-level requirements to low-level software requirements to be implemented, using for example privacy enhancing tools residing or stored in shared repositories. To this end, there is a need to further streamline, complete and ease such approaches. Without extensive guidance and ready-to-use building blocks, small and medium enterprises with no or small research and development teams may struggle to consider the stateof-the-art.

text: The Pets Maturity Assessment Repository

text: To build and maintain such a repository, a broadly accepted methodology for the evaluation of PETs has been singled out as a necessary precondition. The common adoption of the PETs maturity assessment methodology and a unified way to describe a particular PET would improve the situation significantly. To this end, ENISA developed a comprehensive methodology for PETs maturity assessment and developed a web application prototype, called the “PET maturity assessment online repository”.

text: Error! Reference source not found. shows the current repository including some of the introduced test cases. For the Maturity level, a two-dimensional scale has been proposed that informs about technology readiness and privacy enhancement quality: i.e. PET maturity. We therefore determine “PET maturity” as a result calculated from a “technology readiness” and a “privacy enhancement quality” scale.

text: Readiness level of a PET expresses whether a PET can be deployed in practice at a large scale, or whether it can only be used within a research project to build upon to advance the state of the art in privacy protection. Readiness level indicates the amount of effort, i.e. time, money, etc., still needed to allow the PET to be used in practice with a positive cost benefit balance. We favoured the following set of readiness levels over a linear scale to ensure comprehensibility .

text:  Idea. Lowest level of readiness. The PET has been proposed as an idea in an informal fashion, e.g. written as a blog post, discussed at a conference, described in a white paper or technical report.  Research. The PET is a serious object of rigorous scientific study. At least one, preferably more, academic paper(s) have been published in the scientific literature, discussing the PET in detail and at least arguing its correctness and security and privacy properties.  Proof-of-concept. The PET has been implemented, and can be tested for certain properties, such as computational complexity, protection properties, etc., i.e. “Running code” is available, but no actual application of the PET in practice, involving real users, exists, nor is the implementation feature complete.  Pilot. The PET is or has recently been used in practice in at least a small-scale pilot application with real users. The scope of application, and the user base may have been restricted, e.g. to power users, students, etc.  Product. The highest readiness level. The PET has been incorporated in one or more generally available products that have been or are being used in practice by a significant number of users. The user group is not a priori restricted by the developers.  Outdated. The PET is not used anymore, e.g., because the need for the PET has faded, because it is depending on another technology that is not maintained anymore, or because there are better PETs that have superseded that PET.

text: The quality of a PET is not only determined by its readiness. In fact, several PETs at the same readiness level may have varying levels of quality. For this reason, nine quality characteristics, namely protection, trust assumptions, side effects, reliability, operability, performance efficiency, maintainability, transferability and scope are defined.

text: While each of these characteristics is relevant for a PET independent of its readiness level, the indicators that determine the score for each of the characteristics do depend on the readiness level. For example, the quality of a rolled out product depends on how well it is supported by a help desk, code updates, etc. These indicators are irrelevant for research level PETs. Here, the quality is determined by the quality of the re-search, e.g. the ranking of the venues in which the research is published.

text: For each of these nine characteristics, a PET can receive a score in the range {−− (very poor) − (poor) 0 (satisfactory) + (good) ++ (very good)}. The overall quality level also utilises this five-value scale, and is comprised of the nine individual scores, according to a specific quality evaluation function.

text: The scales for readiness and quality defined above allow us to define the real scale we are interested in: a scale for PET maturity. In fact, this overall scale is simply the combination of the readiness level superscripted by the quality level. So for example, a PET with readiness level and quality + has an overall PET maturity level of +. Thus, the total set of potential PET maturity values spans from −− and ++ to −− and ++. The full set of possible values is illustrated in Figure 2.

text: In order to introduce PETs and perform assessments, this platform needs to be populated with experts who are prepared to share their work and experience in a way that PET products improve as a result of interaction among peers. This many-to-many relationship has been thought to be powerful as much as it is capable of stimulating innovation. While learning by doing (i.e. exchanging data on PETs) is a valid expectation), learning by seeing how others work and how they reason about their own PETs is deemed to be powerful. This is likely to provide new impetus to PET tool development and slingshot the performance, quality and ability to meet regulatory requirements of PETs hosted on the platform, to higher levels. A method-driven approach provides a suitable basis to reflect formal regulatory requirements on the proposed PET tools as well as on the platform and render familiar the peer platform members with compliance requirements. This way peers become more confident on their individual abilities to build robust and compliant products that meet user expectations thus raising the overall level of performance vis-à-vis the regulatory framework in place.

text: Figure 3 provides an overview of the assessment process that need to be carried out in the platform. Test users need to define targets of assessment based on products they submit for review. Test users also need to select the board of experts to provide such assessments. It goes without saying that test users are

text: equally expected to render themselves available to act as members of the board of experts of the platform and share their expertise with their peers.

text: 2.2.1 The current implementation

text: The platform made available by ENISA provides an interface to define PETs as a target of assessment. The assessor can provide descriptions and initial sources of evidence. Furthermore, they can issue individual invitations to participants (i/e/ peers) to become members of the board of experts. The experts then are permitted to concurrently assess a PET and submit their opinion. Until then, the system supports the assessor to keep experts unaware of the intermediate results of each other. This ensures a higher level of opinion, which nevertheless can further be subjected to feedback as it is shared among all expert reviewers. Furthermore, the platform keeps full documentation and logs all interactions that allow for a high level of transparency to be enjoyed among peers.

text: After the individual assessments, the assessor needs to reach consensus on the PET with the support of all experts that have contributed to the assessment. The platform supports the assessor to aggregate the different expert opinions and indicates conflicts. Eventually, the consensus conclusion is published as an assessment and can be searched and consulted by the consumers of the platform, primarily the peer that has submitted the tool for assessment as well as others who may be in the future interested by a particular tool. An additional feature is that the platform can be used to keep full records of all products along with their consensus assessment reports that have been submitted over time. This feature is likely to provide an additional value point as over time progress can be analysed and benchmarked while the progress made can enhance the collective ability of PETs experts to determine the state-of-the-art.

text: Such a platform is likely to be seen as a contributing element to the state-of-art as it is perceived, analysed, and evaluated overtime, helping to form a technology view that is proportionate and in line with the expectations set in the legal framework as determined in the GDPR. This platform can provide the quantitative and factual basis upon which the appraisal of the state-of-art is determined; clearly the impact for legal opinion and judgement can be boosted with the successful implementation of a service based on this platform.

text: 3. Approaching test users and populating the platform

text: In this Chapter, the approach followed in order to achieve the project’s objectives is described. In particular, the aims, stakeholders and specific selection criteria are discussed in more detail. A list of relevant use cases for populating the platform is also presented.

text: Purpose of the proposed approach 3.1.1 Test aims

text: As described under Subsection 2.2.1, a prototype of a web platform for the proposed maturity assessment method has been implemented. This platform is currently available online . Tests during the development stage have demonstrated that the platform is suitably stable for a test phase and that it can be tested with a larger, more realistic user group. It must be added here that development has been carried out while full documentation of the various stages remained a standing goal. This clearly adds to the quality of the software produced, which allows for easy tracking of actions taken and changes should particular practices be deemed to be insufficient for the shifting goals of the platform.

text: By populating the platform with experts and evaluations, the aims are to:

text:  Evaluate usability  Understand user requirements  Collect user feedback for the purpose of improving the implementation  Understand market needs  Fine tune the parameters of the approach proposed  Allow for additional features or methods to be further integrated in the platform to render it more usable and effective.

text: To achieve these aims, a first step is to resolve bootstrap issues. If a community platform is populated it means that it meets user demand. If there is user demand for such a service offered by means of a platform it will be easy to attract new members and fuel the intellectual content of the platform. The critical element is to start attracting the first users on the platform. New entrants of an unknown and previously untested system are likely to influence their choices by giving consideration to perceived benefits. The dilemma is to make a proportionally larger effort while the expected positive effects are very limited in the short run and they can only pick up in the long term. As adoption costs for early users are likely to be high and the benefits are expected to be low, the platform needs to appeal to select groups of users likely to tilt their choice in favour of opting for using the platform. Hence, targeting enthusiasts, researchers and privacy advocates to overcome this mismatch seemed like a reasonable goal to pursue. In Annex C there is preliminary list of organizations that have been duly informed of the benefits and the functionality of the platform and they are expected to act as ambassadors in favor of others using the platform.

text: Feedback from test users has been collected through face-to-face meetings, conversations and emails. User feedback ranged from concrete feedback discussing features, usability and general feedback of the marked need of the platform. Moreover, some users have raised security concerns with regards to the

text: current implementation. At this stage, it is logical to make clear that the current state of implementation of this platform does not aspire to meet commercial grade application levels of security and it merely provides a proof of concept in an effort to stimulate interest in the next phase of the feasibility assessment and gain feedback on possible shortcomings and opportunities. The results of these discussions are further summarized in Chapter 4.

text: Moreover, the platform has been presented at conferences and meetings to further understand Market needs. Conferences were selected opportunistically with a view to retain costs low. Conferences present an interesting forum to present and share information on this platform while seeking feedback of knowledgeable people in the field. Such parties may also act as possible target audience to populate the platform with the peers required.

text: Lastly, another important element was to test and fine-tune the evaluation method. The method depends on several parameters such as the evaluation criteria and their importance for the final evaluation results. For the time being, these parameters are set by educated guesses of the authors and implementers of the platform. However, they need to be fine-tuned in such a way that the evaluation results become intuitive.

text: Stakeholders and test users

text: The question of stakeholders for a platform that aims at PETs far exceeds the members of the discreet community that mostly deals with PETs from a technology and compliance point of view. Expert users can indeed benefit from an exchange platform. However, the fall out of their work and the potential of leveraging upon networks of users to improve PETs can exponentially serve and benefit all stakeholders that may have an interest in PET technologies. This potentially includes the entire internet enabled population in a specific jurisdiction.

text: 3.2.1 Test users

text: It must be highlighted, that on the outset, the following user groups were identified as being key for the test users’ composition:

text:  PETs providers: their role is to make information about PETs available within the ENISA’s platform.  Evaluators: their role is to provide maturity assessments for different PETs through the tool.  Users: data controllers, DPAs, researchers or other interested users who can use the platform to get information about the state-of-the-art on PETs. The above groups can be mapped to software developers, IT professionals in the field of PETs, and Regulatory bodies. In the following paragraphs, we shortly describe their use cases on the platform.

text: Regulatory Bodies: In Europe, national data protection authorities are appointed to implement and enforce data protection law, and to offer guidance, see GDPR chapter VI, especially

text: article 57

text: . An up to date and maintained repository of PETs will be a resource to provide guidance with regards to state-of-theart technical protection measures for personal data. The repository will further support DPAs to assess if measures in place are indeed proportional to the assets at stake.

text: Privacy Professionals: IT experts with a focus on privacy and data protection develop and research new protection measures. The platform will provide them with a tool to perform assessments and further understand market needs.

text: Software and Service Developers (IT Industry): IT experts working on new application and services that handle and operate on personal data can use the repository as a knowledge source. This will create a more transparent and competitive market of PETs. Moreover, by defining targets of assessments, IT professionals might put their ideas at challenge to demonstrate market need.

text: 3.2.2 Approaching prospective users

text: In order to attract prospective test users, the platform is hosted under a subdomain of ENISA in an effort to leverage on a given community or stakeholders that have a firm interest in security and privacy as well as on the brand of a specialised EU Agency. Moreover, a leaflet describing the platform was created, which describes shortly the aim and functionality of the platform (Annex A).

text: For the direct and indirect communication with the stakeholders, the following means were created: the platform itself under an easy to remember address, a leaflet and 2 functional mailboxes pets@uni.lu and pets@enisa.europa.eu. Further on, some first contacts were followed up by email and calls.

text: Moreover, those that agreed to co-operate, especially users that introduced test cases received follow-up calls for feedback. The outcome of these follow-ups can be found in Section 4.1.

text: 3.2.3 Targeted Events

text: In order to target the above listed test users, we presented the idea and platform at scientific events. The approach was mainly opportunistic, i.e. the work in this field was presented as a discussion point included in a related presentation. However, dedicated efforts were taken at the Annual Privacy Forum 2018 , in which members of the target audience where directly approached to show “hands on” the current implementation of the tool. Further, a short presentation of the tool was presented in the IPEN workshop .

text: Selection Criteria PETs

text: Targets of assessment were selected in order to test the platform. In this section, we shortly describe examples of PETs that could be assessed with regards to their maturity. Given the above aims for our test, two sets of criteria to select test cases arose, i.e. for testing the platform software and evaluation method, and for populating and attracting more users to build a community.

text: 3.3.1 Selecting test cases to test the platform software and evaluation method

text: In the first category the following aims should be reached:

text:  Ensuring code coverage, and  Ensuring evaluation results coverage.

text: Various quality and readiness levels: PETs need to be selected for broad functionality and code coverage. Hence, for testing purposes, test candidates of possible low protection levels and technology readiness levels are needed. This leads to the need of variance in expected maturity and quality, including legacy PETs and a sort of Zero PET to reach low-quality ratings.

text: 3.3.2 Selecting PETs to populate the platform – Criteria

text: Going beyond the mere software test, selected PETs need to be of a certain general interest. In this category, we summarize criteria that help to select targets of assessment, which are attractive for future users of the platform. Since adding interesting PETs will increase the utility of the platform for future users.

text: Diversity in privacy protection goals: The classical CIA information security protection goals, i.e. confidentiality (C), integrity (I) and availability (A), have been extended for privacy protection. Hansen et.al proposed unlinkability, transparency and intervenability as additional concepts for the construction of PETs. The authors define Unlinkability as separating data and processes, transparency as adequate level of clarity in the relevant data processing and intervenability as the possibility for parties to involve in the relevant process.

text: The scientific PETs community until recently focused on unlikability goal as can be seen in the large number of publications with regard to anonymous communication, electronic voting, private search and private search. In order to cover all protection goals we selected the following application areas:

text:  Anonymous communication  Privacy friendly access control  Transparency tools

text: High maturity level: Often developers are challenged with the question which technology to use. To attract these user groups, the platform needs to provide an extensive repository of mature PETs that provide a high protection level as well as a high readiness level.

text: 3.3.3 Selected Test Candidates

text: Given the above selection criteria, we selected the above candidates for evaluation (Annex B).

text: Fraunhofer INDUCE: is a security framework for data usage control in industrial environments. It supports the fine granular implementation of a need to know principle. INDUCE is a highly consumable framework with several implementations on a large scale. This framework was selected to be evaluated with the possible outcome of a “Product”.

text: PrivacyFlag: this was selected as an EU research project produced several Prototypes and proofs of concept. The PrivacyFlag browser add on aims to support users in deciding if a webpage is trustworthy and secure. The PrivacyFlag mobile app helps end users to rate apps and public IoT implementations to assess their privacy impact. Other results help users to make better use of the anonymous communication tool TOR (EUTOR) and help to understand Website finger printing, a new technique to break anonymity in

text: anonymous communication networks. These prototypes were selected to cover the range from research idea to pilot.

text: IRMA: It offers privacy-friendly authentication based on attributes. This product allows the user to reveal only relevant properties for the given service. The ecosystem is grouped around mobile app on the users’ phone. IRMA provides an extensive user-base in the Netherlands, but is not very much know outside of its Dutch ecosystem. Moreover, it is not clear what its future business model could be. These facts make it being an interesting test candidate for the differentiation between prototype and pilot.

text: 4. Observations from the test phase and user feedback

text: The community-building phase of the project was initiated in June 2018 and lasted until September 2018. Despite the definition of a specific approach (Chapter 3), the uptake on the platform has been generally slow. Indeed, in October 2018 only a few use cases were integrated in the platform, while the user community has not been significantly active. To this end, we collected feedback by unstructured (phone) interviews or received feedback by mail. Almost all contacted potential test users did give their feedback in various levels of detail.

text: In the following Sections, we describe the main observations with regard to the low uptake, as well as relevant user feedback.

text: Communication strategy

text: As a first observation, focusing only on directly targeting potential test users turned out to be very time consuming and we experienced a relatively low response rate.

text: Especially considering the expectation that testers and future users will contribute without monetary compensation, the advertising time of 4 month was rather short. Many of the contacted experts did in fact promise to contribute but were asking for a time-frame of 3 to 6 month. This can be seen also in the uptake for the first contributions: several experts from the first round of contact did indeed contribute after a reminder in the last round.

text: Concept of the PETs repository

text: Primed users were always convinced that a community driven tool that helps to create and maintain a state of the art repository of PETs is very much needed and helpful. See, e.g. the report of Privacy Engineering Research and the GDPR Workshop: A Trans-Atlantic Initiative . However, the present implementation received some critique.

text: A very common feedback was that the website does not clearly address the target audience. The explanation should not be hidden in a PDF, but needs to be on the webpage as a short “about” page. The challenge will be to welcome the target audiences. Maybe with a welcome page including a first selfassessment, dividing the three main target groups. Another remark often made to this end was “If I would have stumbled upon it on the web without your intervention, I would have clicked away in seconds.”

text: Even users that did not stumble upon this first impression struggled with the concept of expert and assessor. They found it hard to distinguish the two concepts. This contributed also to the impression that introducing assessments is time consuming (noted by 2 experts that opted not to contribute).

text: Design and technical aspects of the platform

text: Another aspect that was relevant to low uptake was the design and other technical aspects of the PETs repository.

text: To start with, many users were surprised that the platform was not clearly branded. Often the question was raised why it was not ENISA or EU branded. Apparently, that would have had a major impact on the general trust in the service. Some users recognized the Google Material Design, which lowered their trust

text: in the service. The tabular structure was another design issue. Many users did not notice without help that the next step could be performed by clicking on the next the tab. Here, a wizard like GUI would have helped, according to these users.

text: Moreover, several users were taking issue at the fact that the web service is unprotected (no use of TLS). Most test users accepted the explanation that the platform is a prototype with clear aims what to test. However, at least one expert expressed that these concerns made them not to contribute further. Among these critical users, someone also did some testing of the registration form and seems to be credibly sure that it is not hardened against SQL-injection attacks.

text: It should be noted, however, that ENISA had made clear in all communications with experts that this platform was only a test bed (so as to start the whole project) and not the final tool, which would clearly be adequately protected and secured.

text: 5. Recommendations for Next Steps

text: The experience of the 6 months attempt to promote and populate an existing community platform for that matter taught us that a community approach turns out to be hard to implement and that design and implementation do affect the trust in such a tool, even for a test.

text: Moreover, we believe that we observed a reverse network effect. That is for early adapters a community approach displays little to no utility, but rather high efforts in understanding how to use the platform, which inhibits the adoption.

text: To overcome these two aspects, we recommend to leverage existing communities, implement a social media strategy and create tangible advertisement material. Next to this, the feedback of test users indicates further that the security but also the branding of the platform would be important aspects to build further trust.

text: In this section, we map out future activities and recommend future steps. We enrich this road map with rough cost estimations in terms of person month and durations.

text: Communication Strategy

text: As already mentioned, it has been determined that focusing only on directly targeting potential test users was a very time consuming exercise, which also led to a low response rate.

text: 5.1.1 Duration

text: A longer duration period could probably enhance user contribution, taking into consideration that the short time frame was one of the reasons for slow uptake. Since we still believe that direct contact with relevant test users and early adapters is key, it is recommended that ENISA could set up a permanent contact point for these relevant key contacts.

text: Needed effort. Running such a permanent contact point would need some sort of regular newsletter (quarterly) to remind the community of the platform. The effort in person month is highly depending on the success of the platform. Given that content for a newsletter can be provided by related efforts, we would expect 1 day/ per newsletter entry.

text: 5.1.2 Social networks

text: Beside the maintenance of direct contacts, we further believe that platform owner and stakeholders are recommended to leverage the existing social networks for a viral marketing approach. For a concrete effort estimation see section 5.1.4.

text: Moreover, stakeholders are recommended to research opportunities with platforms like SourceForge i.e. a platform that supports the open source community to develop and distribute software. Open questions with regard to them: can a maturity assessment be integrated in the platform, and can the community be motivated to support systematic maturity assessments. Moreover, the success of this effort depends on the usability and utility of the platform (see section 5.2).

text: Needed effort. It is hard to estimate how much effort the first contact with such platforms is. After first contact, the effort should be marginal.

text: 5.1.3 Dedicated events

text: For a future version, ENISA could organize a “Road Show” to promote the platform. For this, 5 to 10 relevant events should be selected to be present with a booth and advertisement material.

text: Needed effort. Given existing advertisement material, per event 1 person week is needed to prepare such a booth (contacting event, trip, logistics). Further, the financial effort w.r.t. to registration and sponsorship fees can vary largely. Typical sponsorships for small events start at €2,000. Furthermore, several events close to the community might be willing to give away free space. However, high-end events might cost €10,000.

text: 5.1.4 PR expert consultancy

text: Expert consultancy in PR is recommended for both before sketched ideas.

text: Social media channels: In order to reach out to a larger community social media channels need to be created and maintained. For the target audience, focus should be on professional communities such as 19 20 LinkedIn and research focused communities such as ResearchGate . Moreover, twitter could be used for communication to the general public.

text: Advertisement material: In order to support the “Road Show” physical advertisement material needs to be created. Here a one-page folder and a poster should be the first step. Moreover, short presentations with voice over on how to use the platform from the three typical rolls should be created as short advertisement videos. According to the above sketched feedback, it is important to stress, that these material should create a common graphical identity for the platform and its advertisement.

text: Needed Effort: Creating a LinkedIn topical page and a ResearchGate project can be done with the existing material in a short period, e.g., 1 person week. Note the existence of these pages only is valuable if they are maintained.

text: Creating a graphical identity for the project is most likely a rather big effort. However, synergies might emerge if ENISA takes the decision to take the platform under the umbrella of their cooperated identity.

text: Solving usability issues

text: As already mentioned, another aspect that might have led to a suboptimal performance is the current look and feel and usability of the PETs maturity assessment platform.

text: A frequent remark was the stale design and the lack of branding. Given an exciting corporate identity or a graphical identity for the publication from above, the existing platform needs to be modified to implement it. Moreover, this will also improve the perceived trust in the platform.

text: Needed Effort: An update of the current look and feel should be possible in a rather short time, i.e. two to three person-month. However, an accurate estimation needs an assessment of the current source base.

text: Improving security and security hardening of the platform is another parameter that should be considered. This requirement is of course essential if the platform goes in production, but, as users indicated, it may play an important role also in the test phase.

text: Needed Effort: Implementing basic measures such as TLS and encryption of the user database should be easy. However, the maintenance of an acceptable security level including hardening of the system against injection attacks will become a continuous effort. It is very hard to estimate an expected effort without an analysis of the existing code bas. We estimate 1 person month for this analysis.

text: Besides performing the above improvements to the existing code base of the platform, it might be worth of investigating to use as starting point an implementation of another existing platform that implements support for a peer review process.

text: Distribution strategy

text: In the retro perspective, the slow uptake needs to be interpreted as a reverse network effect, i.e. since a community platform becomes exponentially more attractive in relation to the number of active users; a platform with little or no users has very low utility for its first adapters. This also explains the odd situation that many experts in the PETs and data protection community indeed expressed their interest in the project, but in the end where not among the early adapters.

text: Our distribution strategy was to this end not fit for the purpose. Relying only on the platform itself and promotion during conferences to some extend hindered the spread. Moreover, relying only on a specific contractor proved to have certain limitations in terms of community building. An alternative approach could be to directly engage specific key stakeholders (e.g. from the list in Annex C), who can immediately act as users of the PETs platform and further disseminate it to their communities.

text: Furthermore, a future effort needs to interlink the platform with social networks. However, this can leverage the existing general-purpose networks like Facebook, Twitter or Linked in. Moreover, it needs to be explored if and how it could be possible to interlink or even integrate such a platform with existing open source platforms such as source forge.

text: Annex A: Marketing efforts

text: A leaflet was created to distribute it during events.

text: Annex B: List of projects and possible use cases Annex C: List of stakeholders

text: ENISA

text: European Union Agency for Network and Information Security 1 Vasilissis Sofias Marousi 151 24, Attiki, Greece

text: Heraklion Office

text: Science and Technology Park of Crete (ITE) Vassilika Vouton, 700 13, Heraklion, Greece

text: 1 Vasilissis Sofias Str, Maroussi 151 24, Attiki, Greece Tel: +30 28 14 40 9710 info@enisa.europa.eu www.enisa.europa.eu


text: Agamemnonos 14 | Chalandri 15231 | Attiki | Greece | info@enisa.europa.eu | www.enisa.europa.eu

text: The European Union Agency for Cybersecurity, ENISA, is the Union’s agency dedicated to achieving a high common level of cybersecurity across Europe. Established in 2004 and strengthened by the EU Cybersecurity Act, the European Union Agency for Cybersecurity contributes to EU cyber policy, enhances the trustworthiness of ICT products, services and processes with cybersecurity certification schemes, cooperates with Member States and EU bodies, and helps Europe prepare for the cyber challenges of tomorrow. Through knowledge sharing, capacity building and awareness raising, the Agency works together with its key stakeholders to strengthen trust in the connected economy, to boost resilience of the Union’s infrastructure, and, ultimately, to keep Europe’s society and citizens digitally secure. More information about ENISA and its work can be found here: www.enisa.europa.eu.

text: For contacting the authors please use info@enisa.europa.eu For media enquiries about this paper, please use press@enisa.europa.eu.

text: ENISA would like to acknowledge the valuable insights received from the EU CSIRTs Network, EU-CyCLONe, the ENISA Advisory Group, the ENISA Cyber Partnership Programme, industry representatives, the open-source community and academia.

text: This publication represents the views and interpretations of ENISA, unless stated otherwise. It does not endorse a regulatory obligation of ENISA or of ENISA bodies pursuant to

text: Regulation (EU) 2019/881

text: . ENISA has the right to alter, update or remove the publication or any of its contents. It is intended for information purposes only and must be accessible free of charge. All references to it or its use as a whole or in part must contain ENISA as its source. Third-party sources are quoted as appropriate. ENISA is not responsible or liable for the content of the external sources including external websites referenced in this publication. Neither ENISA nor any person acting on its behalf is responsible for the use that might be made of the information contained in this publication. ENISA maintains its intellectual property rights in relation to this publication.

text: © European Union Agency for Cybersecurity (ENISA), 2026 Unless otherwise noted, the reuse of this document is authorised under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed, provided appropriate credit is given and any changes are indicated. Copyright for the image on the cover and on pages 5 - 9 - 11: © Shutterstock For any use or reproduction of elements that are not owned by the European Union Agency for Cybersecurity, permission may need to be sought directly from the respective rightholders.

text: English PDF Web TP-01-26-015-EN-N 978-92-9204-801-3 2314-9434 10.2824/9549088

text: DATE VERSION MODIFICATION

text: May 2026 0 Internal draft 8 May 2026 1.1 Shared with EU-CyCLONe and CSIRTs Network 29 May 2026 1.2 Feedback integrated from CSIRTs Network and EU-CyCLONe 11 June 2026 1.3 Further integration of comments from EU-CyCLONe 17 June 2026 2 Proofread and graphic design Discussion and feedback from ENISA Management Board 18-19 June 2026 3 Minor edits Shared under embargo with the Management Board, ENISA NLO, AG, CSIRTs Network, EU-CyCLONe and CPP.

text: ENISA’s view on Cybersecurity in the Frontier AI Era 3

text: https://aisle.com/blog/ai-cybersecurity-after-mythos-the-jagged-frontier (accessed 18 June 2026) 2 https://suzulabs.com/suzu-labs-blog/mean-time-to-exploit-has-gone-negative.-security-strategy-has-to-change (accessed 18 June 2026)

text: ENISA’s view on Cybersecurity in the Frontier AI Era 5

text: https://securitybrief.com.au/story/ai-fuelled-cyber-attacks-now-steal-data-in-72-minutes (accessed 18 June 2026) 4 https://zerodayclock.com/ (accessed 18 June 2026) 5 https://www.ncsc.nl/nieuws/anthropics-frontiermodel-mythos-vraagt-om-directe-actie (accessed 18 June 2026)

text: ENISA’s view on Cybersecurity in the Frontier AI Era 7

text: Original (NL/machine translated): Behandel dit niet als “volgende trend”, maar als structurele verschuiving in het tempo van aanvallen én verdediging. 7 https://cert.europa.eu/blog/ai-vulnerability-discovery-defenders-must-adapt (accessed 18 June 2026) 8 Centre for Cybersecurity Belgium (CCB) – Food for thought: The Cybersecurity Revolution in the Age of Frontier AI

text: ENISA - Economics of vulnerability disclosure (accessed 18 June 2026) 10 Patch Diffing | CVE North Stars (accessed 18 June 2026)

text: ENISA’s view on Cybersecurity in the Frontier AI Era 9

text: https://www.darkreading.com/application-security/ai-led-remediation-crisis-prompts-hackerone-pause-bug-bounties (accessed 18 June 2026)

text: Palo Alto Networks, 2025 Unit 42 Global Incident Response Report (accessed 18 June 2026) 13 ENISA – Technical Implementation Guidance (accessed 18 June 2026)

text: ENISA’s view on Cybersecurity in the Frontier AI Era 11

text: ENISA’s view on Cybersecurity in the Frontier AI Era 13

text: Article 55 of the EU AI Act requires providers placing general-purpose AI models with systemic risk on the EU market to assess and mitigate those risks, regardless of where they are based. Through the GPAI Code of Practice, providers commit to identifying systemic risks, including large-scale cyberattack risks, applying safety and cybersecurity measures across the model lifecycle, and reporting relevant information and evaluation results to the European AI Office. These rules have applied since 2 August 2025 and will be enforced from 2 August 2026, with the Office empowered to investigate compliance, require mitigation measures, impose fines of up to 3% of global annual turnover and, in extreme cases, restrict, withdraw, or recall models from the EU market.

text: ENISA’s view on Cybersecurity in the Frontier AI Era 15

text: European Union Agency for Cybersecurity

text: Athens Office ISBN 978-92-9204-801-3 Agamemnonos 14 Chalandri 15231, Attiki, Greece

text: Brussels Office

text: Rue de la Loi 107 1049 Brussels, Belgium

amnesord: Artificial Intelligence and Next Gen Technologies

text: TLP: CLEAR

text: JULY 2026

text: ABOUT ENISA CONTACT AUTHORS ACKNOWLEDGEMENTS LEGAL NOTICE COPYRIGHT NOTICE

text: Table of contents

text: EXECUTIVE SUMMARY IMPACT ON VULNERABILITY & PATCH MANAGEMENT 11 SECURITY FUNDAMENTALS MATTER MORE THAN EVER THE WAY AHEAD: BUILDING AI-RESILIENT DEFENCES 13

text: Executive summary

text: Frontier AI models are challenging traditional To identify the appropriate response security paradigms by compressing the to the emergence of AI and its impact vulnerability management lifecycle and attack on cybersecurity, ENISA held a series of chain, from discovery to exploitation. The engagements where our stakeholders frontier model landscape is evolving rapidly; raised the following: it is expected that open-weight models may reach a similar level of capability within • there is the likelihood that attackers 9 to 12 months and that existing models will have access to exploits before when coupled with skilled security experts fixes are released (so called 1 2 can yield comparative results . While ENISA negative time-to-exploit ); acknowledges the potential benefits of these • AI amplifies challenges related to technologies to improve security, this note legacy systems and products that will aims to focus on some of the immediate and soon reach or have reached their endmid-term cybersecurity challenges. of-life and end-of-support; This note provides national competent • due to an expected increase in patch authorities in Member States and release frequency, patching may lead EU policymakers, defenders, and to an increase in service disruptions; service providers with an initial set of recommendations to support them in • open-source require a strategy to their respective roles towards developing prevent maintainers to be overloaded the necessary operational capabilities to face machine-speed threats. The with vulnerability reports; recommendations are not an all-inclusive • SMEs, part of the backbone of checklist. ENISA aims to further refine and expand these recommendations in close the EU economy, may require cooperation with Member States and EUIBAs additional support, in particular in and will align these to upcoming European terms of guidance and access to the Commission Action Plan. latest models;

text: • cybersecurity should be positioned • architectural solutions must use as a strategic use case for European an assume-breached mindset, investment in AI, as a need exists for while acknowledging that zero trust the EU-based organisations to have approaches will require a deep access to and develop their own transformational process; AI models, • Cybersecurity as Code: means • security fundamentals matter more machine-speed threats need to than ever in the age of AI; be addressed with machine-speed defences (Vulnerability Management • resources need to be shifted from as Code, Incident Response as Code, discovery to risk-based prioritisation Security by Design as Code, Security of vulnerabilities through higher-speed Architecture as Code); triage, remediation and risk reduction; • AI-driven defensive capabilities that • defensive AI tooling need to be can detect, correlate and respond to integrated into the software threats at machine speed need to be development lifecycle to support deployed, and secure by design practices; • the Cyber Resilience Act’s Single • human-gated AI workflows need be Reporting Platform must be integrated across incident response leveraged, once it is functional, to and threat modelling, by upskilling and address the challenges posed by reskilling the cybersecurity workforce; new developments.

text: Impact on Vulnerability & Patch Management

text: Over the past few years, ENISA has urged Historically, the Window of Exposure (WoE) the cybersecurity community to adapt was a manageable gap; the inherent friction its vulnerability management practices of human-led research and the manual in response to advancing AI capabilities. development of exploits provided defenders We have noted the steadily narrowing with a ‘grace period’. However, data window between vulnerability discovery synthesised by researchers shows that the and exploitation: this period has gone from delta between discovery and weaponisation years, to months, and now (potentially) to is approaching zero . hours or even minutes. Industry research underscores the urgency. Attackers can ENISA’s current capacity, as well as that weaponise new vulnerabilities within 15 of manufacturers, national CSIRTs, and minutes of disclosure, and the median time national coordinated disclosure processes, from initial access to data exfiltration has may need further reinforcement or been compressed to 72 minutes , meaning reconsideration to manage a large wave of that security operation centres (SOCs) must newly discovered vulnerabilities. further adopt automation, and explore new strategies to reduce their Mean Time The NCSC-NL noted that the speed to Detect (MTTD), Mean Time to Respond of autonomous agents eliminates the (MTTR), and Mean Time to Contain (MTTC) defender’s advantage of “private discovery”. to levels commensurate with the evolving Once a vulnerability is found by an AI agent, threat landscape. the transition to a weaponised exploit is no longer a human-led engineering project but a machine-speed computationale task. The message to organisations should be clear:

text: “Do not treat this as a “next “The EU, as an innovative trend”, but as a structural block with a high density shift in the pace of attack and of SMEs and a deeply defence ”. interconnected supply chain, is particularly sensitive to

text: Also, as CERT-EU noted :

text: the disruptions brought by Frontier AI”. “What makes the latest

text: To navigate these changes, the generation of models cybersecurity community must prepare for

text: particularly dangerous seven structural challenges derived from

text: current ENISA’s assessments:

text: is not just the volume of vulnerabilities they find. It is

text: • The Velocity Asymmetry and

text: their ability to chain findings

text: the Authority Gap. In the new

text: across multiple steps, reason environment, the primary latency is no

text: about application logic, and longer technical, but procedural. The

text: “Authority Gap” refers to the inability

text: produce exploitation paths

text: of human Change Advisory Boards

text: that previously required deep

text: (CABs) to authorise interventions specialist knowledge. This is in just the few minutes available to

text: what turns a list of individual counter autonomous exploits. Plainly,

text: it means organisations are too slow to

text: flaws into a working attack.”

text: authorise a meaningful antidote. The necessity of autonomous patching, This capability extends beyond vulnerability where the risk of an automated chaining. Frontier AI models can creatively update breaking a system or causing reason about application logic, credentials, significant downtime is statistically configurations, and API access patterns, weighed against the near-certainty of going beyond static code analysis to an AI-driven breach will be challenging. understand how applications work, and Particularly in the short-term, larger can orchestrate entire autonomous attack organisations will likely be able to campaigns from reconnaissance through establish resilient patching practices lateral movement to exfiltration, not merely quicker, while smaller ones will face discover individual vulnerabilities. challenges due to a lack of resources, security focus, and the necessary As mentioned by NCSC IE: skills.

text: • Economic Devaluation of Discovery:

text: “Now is the time to review

text: Vulnerability discovery is becoming asset inventories, prioritise increasingly industrialised, which

text: patching discipline, lowers the marginal cost of finding

text: flaws and raises the volume of

text: and assess exposure to

text: disclosures faster than many

text: unsupported components”.

text: organisations can remediate them. As an example, an industry Europe’s particular context also needs to be representative shared with ENISA acknowledged as noted by Belgium’s CCB: that their organisation used to receive a few hundred reports of possible vulnerabilities a year, of

text: which only one hundred would teams now face a challenge of scale, traditionally receive a CVE ID. that is how to audit and validate AI- However, the organisation went generated patches so that they do from about ~80 CVEs in Q1 2025 to not introduce new vulnerabilities close to 500 in Q1 2026, and then into the codebase. An additional the number jumped to about 500 burden for technical teams should be per day when they used Frontier AI- expected, as low-risk vulnerabilities enabled tools. ENISA’s analysis of can no longer be deemed harmless, vulnerability disclosure notes that as they can be chained to create disclosure economics depend on working exploits. incentives, coordination, and the • N-Day Weaponisation. Public costs borne by both researchers and vulnerability disclosure and patch defenders, making rapid triage and releases can still provide attackers remediation a more critical bottleneck with useful information, because than discovery alone. Vulnerability patch diffs and binary changes prioritisation mechanisms like the have historically enabled reverse Exploit Prediction Scoring System engineering and exploit development. (EPSS) developed by FIRST, and the ENISA’s vulnerability management Vulnerability Exploitability eXchange guidance recognises that the (VEX) can directly assist organisations exploitation window can begin before in focusing scare resources. patch deployment and that exposure • Technical Debt as an Existential often persists while organisations test, Risk. Considering legacy systems coordinate, and schedule updates. today, AI-assisted analysis and Such strategies must, however, be reverse engineering can accelerate pursued within the constraints set by code understanding and vulnerability some of the mission critical systems discovery, but this does not make deployed by Operators of Essential these systems automatically Services. In the short term, such ‘undefendable’. Further complexity organisations will need to invest in is added by the already existing proactive security measures in the backlog of vulnerabilities and technical absence of a patch and/or methods debt. System hardening, network for faster patch consumption. segmentation, security monitoring, • The Secure SDLC revolution. There and staged modernisation can is an opportunity to shift the focus still reduce risk. In addition, these from traditional vulnerability and transformational needs may push patch management towards the small and medium organisations stronger enforcement of Secure towards broader cloud adoption Software Development Life Cycle as entities look at whether the (SSDLC) practices, including more risk, operational constraints, and comprehensive assessments of maintenance burden justify continued potential vulnerabilities throughout operation versus retirement or the development process. This needs replacement. to happen across all phases of product • The Verification Bottleneck and development in order to minimise the the ‘Truth’ Crisis. While Advanced introduction of vulnerabilities from the AI models may significantly reduce outset. At the same time, integrators false positives, the sheer volume of and end users should be enabled ‘true’ reports creates a verification to detect vulnerabilities as early as bottleneck. As pointed out in its possible, particularly those arising studies, ENISA notes that the quality from combinations of configurations of vulnerability information is often and system integrations. Regarding insufficient for rapid action. Technical vulnerability detection and

text: remediation, the objective should be from a discovery channel into a triage to move from a model based primarily bottleneck, where the limiting factor on oversight towards one based on becomes reviewer capacity rather the integration of security directly than the supply of findings. However, into development and operational according to recent ENISA discussions processes at company level. This also with industry, the last few months requires a clear focus on increasing have seen an important increase in the accessibility and adoption of AI report quality, therefore there is a relevant security technologies and large amount of ‘signal’ currently being practices, and the reskilling and reported. upskilling of the existing workforce. • The Risk of ‘Inside-Out’ Attacks: • AI-Generated Vulnerability Distinct from the vulnerability- Reports. By early 2026, AI-generated exploitation paradigm above, vulnerability reports had begun adversaries are increasingly to overwhelm parts of the open- compromising the AI and software source disclosure pipeline.A global supply chain to land inside vulnerability disclosure coordination infrastructure directly, for example and bug bounty platform paused new by arriving through a trusted Internet Bug Bounty submissions software update or a compromised after a surge of mixed-quality AI- open-source dependency. In these assisted reports, while curl shut scenarios, the attacker never needs down its CVD programme in January to breach perimeter defences as they 2026 because maintainers could not are inside the environment and only sustainably absorb the reporting need to move laterally to access and volume and noise. The underlying exfiltrate data. This threat model problem was not just volume, but demands detection and response signal dilution meaning that human strategies that go beyond perimeterreviewers were spending increasing oriented defences and assume that amounts of time separating real adversaries may already be present issues from repetitive, superficial, or within trusted environments. poorly validated submissions. That shift turns vulnerability reporting

text: Security fundamentals matter more than ever

text: Security fundamentals will not change, but against live telemetry potentially within new AI models are compressing the entire hours or minutes. Research indicates that attack lifecycle, from reconnaissance to in 75% of breaches, logging existed that lateral movement, in ways that stress-test should have flagged anomalous behaviour these fundamentals, forcing defenders, but signals were fragmented across manufacturers and service providers to different tools and not acted upon. That gap accelerate their cybersecurity initiatives. was manageable when attacks moved at human speed but at AI speed, it will become

text: 1. Vulnerability management untenable.

text: To defend against lightning-fast automated Service providers, including newly expanded cyberattacks, critical service providers may providers under the scope of NIS2, must be forced to use autonomous patching, harden operations against AI-scale threats as organisational approval is simply too such as adaptive phishing, model poisoning, slow. However, this creates a new risk: and supply-chain pivots. Risk assessments automated updates could accidentally break should blend logging and monitoring systems and cause unwanted downtime. requirements with runtime AI guards, Furthermore, verifying these AI-generated access controls, and threat intelligence patches may become a major bottleneck. sharing, to enable real-time detection System managers may face challenges and response. to build tools that can quickly check and approve these fixes without accidentally ENISA’s Technical Implementation Guidance introducing new bugs into the code. on NIS2 Risk Management reinforces this by operationalising documented risk

text: 2. Incident response frameworks, incident handling policies, supply-chain security, threat hunting For defenders, incident response becomes capabilities, processes now under pressure a race against AI-orchestrated campaigns, by the speed and autonomy of AI. with SOCs needing to validate intrusions

text: A parallel constraint is the ability of form critical part of the technology stack national authorities to absorb and act on in use. There is also the risk that Union’s incident data at scale. Mandatory incident small manufacturers will not get access reporting, combined with a broader to software/product testing capabilities scope of regulated entities, will sharply enabled by new AI models due to costs. increase reporting volumes, just as AI accelerates vulnerabilities, exploitation, and Manufacturers must adjust their product breaches. This creates a structural risk of lifecycles for compliance with the Cyber simultaneous surges in incidents exceeding Resilience Act (CRA). Developers of AI national capacity. Proactive scanning of models should train their models to be critical infrastructure by National CSIRTs structurally constrained (stronger than a becomes even more relevant. guardrail), and ensure that such models are suggesting code that is secure by In such scenarios, key questions include design/default. ENISA’s proposal for how to prioritise incidents when they machine-processable security attestations all meet regulatory thresholds, which and implementation of SBOM strategies CSIRTs structures can operate without can operationalise the CRA security prioritisation, and how sectoral CSIRTs can requirements; embed threat modelling, be supported when national capacity is least privilege, and lifecycle attestations saturated. Governments should act and from the outset. integrate industry into its crisis planning, establishing surge capacity models, 4. Talent and human capital defining clear prioritisation and escalation frameworks, and stress-testing multi- A cross-cutting challenge will be to ensure incident scenarios. that foreseen solutions will keep the human in the middle. While AI can help build

text: 3. Product Security system fasters, or defend networks better, humans will still need to understand the As the frontier AI capabilities will enable environments they assume responsibility software developers, owners and for. Cybersecurity risks related to AI will manufacturers to secure their code in require raising the level of awareness, the long run, the immediate problem is understanding and skills, across all levels of the security of legacy products and in organisations, substantially faster. particular open-source components which

text: The way ahead: building AI-resilient defences

text: Frontier AI models demand a fundamental national authorities and defenders, the shift if defenders are to achieve operational development of new frameworks and the parity with, or stay ahead of attackers reinforcement of existing platforms can through structured frameworks and more function as force multipliers. For example, adaptive practices. The recommendations correlated EUVD data can help identify below set a clear direction for what supply-chain hotspots, systemic weaknesses organisations should aim for through and vulnerability trends accelerated by AI- European coordination, national assisted discovery. CRA-related reporting enforcement and defender operations. may help validate vendor hardening claims They are neither exhaustive nor against real-world exploitability and incident mutually exclusive. patterns. When combined, over time, NIS2 incident reporting and other situational The CRA’s Single Reporting Platform awareness reports, can help close the (SRP) and EU Vulnerability Database (EUVD) gap between vulnerability disclosure to can help support the operationalisation coordinated response. of some of these recommendations. For

text: Recommendations

text: • European Level: • National Authorities:

text: – At the European level, the existing – Run AI-powered threat hunting legal frameworks, including NIS2, operations and publish CRA and the EU AI Act should be anonymised datasets from Frontier leveraged, to ensure that systemic AI simulations. risks stemming from the most – Require critical infrastructure advanced AI models are assessed operators to attest zero-trust and mitigated. To this end, it may be baselines, resilient incident useful to establish EU-wide state-ofresponse capabilities during annual the-art benchmarks for the security audits, and clear escalation paths evaluation of advanced AI models, for AI-accelerated incidents. including standardised testing against cyber ranges, exploitability – Direct government agencies and metrics, and simulations of chained critical infrastructure operators to attacks, to set a consistent bar for reduce ineffective security tooling assessing their capabilities. and complement their cybersecurity stack with AI-enabled platforms – Leverage and build on existing capable of ingesting, correlating, initiatives at European and Member and acting on threat data. State level that consider the use of future AI models for cybersecurity. – Develop common frameworks for the deployment of AI-enabled – European institutions, national security tools that prioritise human authorities, CSIRTs, regulators oversight, auditability, and humanand operators of essential gated triage for decision making. services hold cybersecurity data that could be highly valuable – Develop evaluation capacities for training, evaluating and finefor products including AItuning defensive AI systems. functionalities, in order to ensure This includes incident reports, and validate security levels to face vulnerability disclosures, telemetry, cybersecurity threats malware samples, abuse reports and sectoral threat intelligence. – Proactively scan critical Subject to strong safeguards, infrastructure components that anonymisation, access controls fall under the responsibilities of and clear legal bases, such national authorities. datasets could become a European strategic asset. They could support trusted European cyber-AI models and serve as leverage in procurement negotiations.

text: – In accordance with the AI Act and the Code of Practice for General Purpose AI, adequate risk mitigations for AI models with advanced cyber capabilities need to be identified.

text: • Defenders:

text: – Build more dynamic incident – Treat every environment as response pipelines, using AIpotentially already compromised assisted triage for real-time and extend endpoint protection telemetry validation, prioritisation, across all environments. Every and blast-radius containment, organisation should conduct an while keeping human review firmly analysis of its exposure to frontier in the loop to reliably hit 24-hour AI and deploy real-time, MLnotifications. based prevention and detection

text: on all on-premises and cloud – Transform security operations into hosts, including securing agentic a near real-time function, targeting endpoints and enterprise browsers, single-digit-minute mean-time-towhich represent critical new attack detect (MTTD) and mean-time-tosurfaces as AI agents increasingly respond (MTTR) metrics. operate autonomously on

text: endpoints and within browsers. – Accelerate zero-trust segmentation,

text: behavioural baselining, and more – Embed structured threat modelling evasion-resistant detection layers early and continuously, leveraging that assume attackers will adapt advanced AI models with precise and evolve in near real-time. context to uncover combinations

text: of weaknesses and run continuous

text: simulations against live

text: architectures, effectively turning

text: AI into an always-on support

text: capability for red teaming and

text: defensive validation.

text: ABOUT ENISA enisa.europa.eu

type: vagledning

utgivare: enisa