TEStabiliTy pAttern-driven weB appLication sEcurity and privacy testing

Informations projet

TESTABLE

N° de convention de subvention: 101019206

DOI

10.3030/101019206

Projet clôturé

Date de signature de la CE 20 Avril 2021

Date de début 1 Septembre 2021

Date de fin 31 Août 2024

Financé au titre de

• Secure societies - Protecting freedom and security of Europe and its citizens

Coût total

€ 4 835 135,00

Contribution de l’UE

€ 4 835 135,00

Coordonné par

CISPA - HELMHOLTZ-ZENTRUM FUR INFORMATIONSSICHERHEIT GGMBH
Germany

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Documents, reports (22)

Dissemination and Exploitation Progress Report, Year 1

Intermediate report on the dissemination activities performed during the first year of the project ie T82 T83 and T84

Final Report on Privacy Testing Solutions

This deliverable will describe and present the performance evaluation of the final privacy testing solutions of T4.2.

Dissemination and Exploitation Progress Report, Year 2

Intermediate report on the dissemination activities performed during the second year of the project, i.e., T8.2, T8.3, and T8.4.

Pattern Discovery Evaluation Report

Final report on T6.1.

Large Scale Assessment of Publicly Available Case Studies

Final report on T7.2.

Analysis of Requirements

Final report on the progress on T21

Initial set of Case Studies

Final report on T71

Definition of the Scope of Privacy Testing

This deliverable will report on T41 and it will provide a comprehensive description of the required privacy patterns that need to be considered in privacy testing by taking into account both the existing solutions and the elements that are missing

Initial Set of Testability Patterns

Intermediate report on the progress of T22

Security and Privacy Mitigation Report

Final report on T6.3.

Final Report on Techniques to Increase Testability

Final report on T3.2.

Preliminary Report on Techniques to Increase Testability

Intermediate report on the progress of T3.2.

Intermediate Report on AI/ML Testing Solutions

This deliverable will describe and present the initial performance evaluation of the interim AI/ML testing solutions of T5.2.

Testability Improvement Report

Final report on T6.2.

Definition of the Scope of AI/ML Testing

This deliverable will report on T51 and it will provide a comprehensive description of the required patterns that need to be considered in AIML testing by taking into account both the existing solutions and the elements that are missing

Final Dissemination and Exploitation Report

Final dissemination deliverable, which includes the plan for exploitation and the report of the standardization activities, i.e., T8.2, T8.3, and T8.4.

Final Report on AI/ML Testing Solutions

This deliverable will describe and present the performance evaluation of the final AI/ML testing solutions of T5.2.

Report on Security and Privacy Indicators

Intermediate report on the progress of T2.3.

Report on Security Testing Building Block Techniques

Report on T31

Final Report on Testability Patterns

Final report on the progress of T2.2.

Intermediate Report on Privacy Testing Solutions

This deliverable will describe and present the intial performance evaluation of the interim privacy testing solutions of T4.2.

Initial Assessment of Publicly Available Case Studies

Intermediate report on the progress on T7.2.

Websites, patent fillings, videos etc. (1)

Web Site and Digital Presence

Creation and setup of the projects website and social platform accounts for digital presence T81

Publications

Conference proceedings (27)

Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors

Auteurs: Biagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio
Publié dans: Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2024
Éditeur: ACM
DOI: 10.1145/3605764.3623920

FUZZILLI: Fuzzing for JavaScript JIT Compiler Vulnerabilities

Auteurs: Samuel Groß, Simon Koch, Lukas Bernhard, Thorsten Holz, Martin Johns
Publié dans: Proceedings 2023 Network and Distributed System Security Symposium, 2023
Éditeur: Internet Society
DOI: 10.14722/ndss.2023.24290

Poster: The Risk of Insufficient Isolation of Database Transactions in Web Applications

Auteurs: Simon Koch, Malte Wessels, David Klein, Martin Johns
Publié dans: Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, Numéro 202, 2024, Page(s) 3576-3578
Éditeur: ACM
DOI: 10.1145/3576915.3624394

Keeping Privacy Labels Honest

Auteurs: Simon Koch (Technische Universität Braunschweig, Institute for Application Security), Malte Wessels (Technische Universität Braunschweig, Institute for Application Security), Benjamin Altpeter (Datenanfragen.de e. V.), Madita Olvermann (Technische Universität Braunschweig, Industrial/Organizational and Social Psychology), Martin Johns (Technische Universität Braunschweig, Institute for Applica
Publié dans: Proceedings on Privacy Enhancing Technologies Symposium, Numéro Volume: 2022 Numéro: 4, 2022, Page(s) Pages: 486–506
Éditeur: Privacy Enhancing Technologies Board
DOI: 10.56553/popets-2022-0119

Testability Tarpits: the Impact of Code Patterns on the Security Testing of Web Applications

Auteurs: Feras Al Kassar, Giulia Clerici, Luca Compagna, Davide Balzarotti, Fabian Yamaguchi
Publié dans: Proceedings 2022 Network and Distributed System Security Symposium, 2023
Éditeur: Internet Society
DOI: 10.14722/ndss.2022.24150

Hand Sanitizers in the Wild: A Large-scale Study of Custom JavaScript Sanitizer Functions

Auteurs: Klein, David and Barber, Thomas and Bensalim, Souphiane and Stock, Ben and Johns, Martin
Publié dans: EuroS&P IEEE European Symposium on Security and Privacy, 2022
Éditeur: IEEE
DOI: 10.1109/eurosp53844.2022.00023

General Data Protection Runtime: Enforcing Transparent GDPR Compliance for Existing Applications

Auteurs: David Klein, Benny Rolle, Thomas Barber, Manuel Karl, Martin Johns
Publié dans: Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2024, Page(s) 3343-3357
Éditeur: ACM
DOI: 10.1145/3576915.3616604

Domain and Website Attribution beyond WHOIS

Auteurs: Silvia Sebastián, Raluca-Georgia Diugan, Juan Caballero, Iskander Sanchez-Rola, Leyla Bilge
Publié dans: Annual Computer Security Applications Conference, 2023, Page(s) 124-137
Éditeur: ACM
DOI: 10.1145/3627106.3627190

Exploring Current and Future Research Directions on XS-Leaks through an Extended Formal Model.

Auteurs: Tom Van Goethem, Gertjan Franken, Iskander Sanchez-Rola, David Dworken, and Wouter Joosen
Publié dans: Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security (ASIA CCS '22), 2022, Page(s) 784–798
Éditeur: Association for Computing Machinery
DOI: 10.1145/3488932.3517416

Scripted Henchmen: Leveraging XS-Leaks for Cross-Site Vulnerability Detection

Auteurs: Tom Van Goethem, Iskander Sanchez-Rola, Wouter Joosen
Publié dans: 2023 IEEE Security and Privacy Workshops (SPW), Numéro 7, 2024, Page(s) 371-383
Éditeur: IEEE
DOI: 10.1109/spw59333.2023.00038

The OK Is Not Enough: A Large Scale Study of Consent Dialogs in Smartphone Applications

Auteurs: Koch, Simon; Altpeter, Benjamin; Johns, Martin
Publié dans: 32nd USENIX Security Symposium (USENIX Security 23), 2023, Page(s) 5467-5484
Éditeur: USENIX Association

When Sally Met Trackers: Web Tracking From the Users' Perspective

Auteurs: Savino Dambra, Iskander Sanchez-Rola, Leyla Bilge, Davide Balzarotti
Publié dans: 31th USENIX Security Symposium (USENIX Security 22)}, 2022, Page(s) 2189--2206, ISBN 978-1-939133-31-1
Éditeur: USENIX Association

Testability Tarpits: the Impact of Code Patterns on the Security Testing of Web Applications

Auteurs: Feras Al Kassar (SAP Security Research), Giulia Clerici (SAP Security Research), Luca Compagna (SAP Security Research), Davide Balzarotti (EURECOM), Fabian Yamaguchi (ShiftLeft Inc)
Publié dans: NDSS Symposium 2022, 2022
Éditeur: Internet Society

Poster: Analysis of User Uniqueness on LinkedIn Based on Publicly Available Non-PII

Auteurs: Ángel Merino, José González-Cabañas, Ángel Cuevas, Rubén Cuevas
Publié dans: Proceedings of the 2023 ACM on Internet Measurement Conference, 2024, Page(s) 726-727
Éditeur: ACM
DOI: 10.1145/3618257.3625000

{WHIP}: Improving Static Vulnerability Detection in Web Application by Forcing tools to Collaborate

Auteurs: Al-Kassar, Feras; Compagna, Luca; Balzarotti, Davide
Publié dans: 32nd USENIX Security Symposium (USENIX Security 23), 2023, Page(s) 6079-6096
Éditeur: USENIX Association

Unique on Facebook: formulation and evidence of (nano)targeting individual users with non-PII data

Auteurs: González-Cabañas, José ; Cuevas, Ángel ; Cuevas, Rubén ; López-Fernández, Juan ; García, David
Publié dans: ACM Internet Measurement Conference (IMC '21), 2021
Éditeur: Association for Computing Machinery
DOI: 10.1145/3487552.3487861

Analysis and Implementation of Nanotargeting on LinkedIn Based on Publicly Available Non-PII

Auteurs: Ángel Merino, José González-Cabañas, Ángel Cuevas, Rubén Cuevas
Publié dans: Proceedings of the CHI Conference on Human Factors in Computing Systems, Numéro 671, 2024, Page(s) 1-22
Éditeur: ACM
DOI: 10.1145/3613904.3642107

Proceedings of 45th IEEE Symposium on Security and Privacy

Auteurs: Khodayari, Soheil; Barber, Thomas; Pellegrino, Giancarlo
Publié dans: Proceedings of 45th IEEE Symposium on Security and Privacy, 2024
Éditeur: IEEE

Scamdog Millionaire: Detecting E-commerce Scams in the Wild

Auteurs: Platon Kotzias, Kevin Roundy, Michalis Pachilakis, Iskander Sanchez-Rola, Leyla Bilge
Publié dans: Annual Computer Security Applications Conference, 2023, Page(s) 29-43
Éditeur: ACM
DOI: 10.1145/3627106.3627184

SSRF vs. Developers: A Study of SSRF-Defenses in PHP Applications

Auteurs: Wessels, Malte; Koch, Simon; Pellegrino, Giancarlo; Johns, Martin
Publié dans: 33rd USENIX Security Symposium (USENIX Security 24), 2024, Page(s) 6777-6794
Éditeur: USENEX

It’s (dom) clobbering time: Attack techniques, prevalence, and defenses

Auteurs: Khodayari, Soheil; Pellegrino, Giancarlo
Publié dans: 2023 IEEE Symposium on Security and Privacy, 2023, Page(s) 1041-1058
Éditeur: IEEE

Parse Me, Baby, One More Time: Bypassing HTML Sanitizer via Parsing Differentials

Auteurs: Klein, David; Johns, Martin
Publié dans: 2024 IEEE Symposium on Security and Privacy (SP), 2024, Page(s) 173-173
Éditeur: IEEE

Robust Machine Learning for Malware Detection over Time

Auteurs: Daniele Angioni Primo;Luca DemetrioSecondo;Maura PintorPenultimo;Battista BiggioUltimo
Publié dans: 6th Italian Conference on Cybersecurity, ITASEC 2022, 2022
Éditeur: CEUR-WS

The Fault in Our Stars: An Analysis of GitHub Stars as an Importance Metric for Web Source Code

Auteurs: Koch, Simon; Klein, David; Johns, Martin
Publié dans: Workshop on Measurements, Attacks, and Defenses for the Web (MADWeb) 2024, 2024
Éditeur: iNTERNET SOCIETY

Generating Realistic Synthetic Curricula Vitae for Machine LearningApplications under Differential Privacy

Auteurs: Andrea Bruera1, Francesco Alda, Francesco Di Cerbo3
Publié dans: PROCEEDINGS - LREC 2022 Joint Workshop Language Resources and Evaluation Conference, 2022, Page(s) 53-63, ISBN 979-10-95546-96-2
Éditeur: European Language Resources Association (ELRA)

Towards Understanding and Improving Security-Relevant Web Application Logging

Auteurs: Merve Sahin, Noemi Daniele
Publié dans: Proceedings of the 19th ACM Asia Conference on Computer and Communications Security, Numéro 22, 2024, Page(s) 814-829
Éditeur: ACM
DOI: 10.1145/3634737.3637647

Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples

Auteurs: Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli
Publié dans: Advances in Neural Information Processing Systems, 2022, Page(s) 23063-23076
Éditeur: Curran Associates, Inc.

Peer reviewed articles (9)

Secure and explainable machine learning in Python

Auteurs: Maura Pintor, Luca Demetrio, Angelo Sotgiu, Marco Melis, Ambra Demontis, Battista Biggio
Publié dans: SoftwareX, Numéro 23527110, 2022, ISSN 2352-7110
Éditeur: Elsevier
DOI: 10.1016/j.softx.2022.101095

Online advertisement in a pink-colored market

Auteurs: Amir Mehrjoo, Rubén Cuevas, Ángel Cuevas
Publié dans: EPJ Data Science, Numéro 13, 2024, ISSN 2193-1127
Éditeur: Springer Nature
DOI: 10.1140/epjds/s13688-024-00473-2

A Deep Dive into the Accuracy of IP Geolocation Databases and its Impact on Online Advertising

Auteurs: Patricia Callejo, Marco Gramaglia, Rubén Cuevas, Ángel Cuevas
Publié dans: IEEE Transactions on Mobile Computing, Numéro 22, 2024, Page(s) 4359-4373, ISSN 1536-1233
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmc.2022.3166785

Overprofiling Analysis on Major Internet Players

Auteurs: Francisco Caravaca, José González-Cabañas, Ángel Cuevas, Rubén Cuevas
Publié dans: Proceedings on Privacy Enhancing Technologies, Numéro 2024, 2024, Page(s) 929-946, ISSN 2299-0984
Éditeur: Privacy Enhancing Technologies Board
DOI: 10.56553/popets-2024-0149

Estimating ideology and polarization in European countries using Facebook data

Auteurs: Francisco Caravaca, José González-Cabañas, Ángel Cuevas, Rubén Cuevas
Publié dans: EPJ Data Science, Numéro 11, 2023, ISSN 2193-1127
Éditeur: Springer Open
DOI: 10.1140/epjds/s13688-022-00367-1

Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware

Auteurs: Luca Demetrio; Battista Biggio; Fabio Roli
Publié dans: IEEE Security & Privacy, 2022, Numéro 15584046, 2022, Page(s) 77-85, ISSN 1558-4046
Éditeur: IEEE
DOI: 10.1109/msec.2022.3182356

A Black-Box Privacy Analysis of Messaging Service Providers' Chat Message Processing

Auteurs: Robin Kirchner, Simon Koch, Noah Kamangar, David Klein, Martin Johns
Publié dans: Proceedings on Privacy Enhancing Technologies, Numéro 2024, 2024, Page(s) 674-691, ISSN 2299-0984
Éditeur: Petsymposium
DOI: 10.56553/popets-2024-0099

Expanding the Measurement of Culture with a Sample of Two Billion Humans

Auteurs: Nick Obradovich, Ömer Özak, Ignacio Martín, Ignacio Ortuño-Ortín, Edmond Awad, Manuel Cebrián, Rubén Cuevas, Klaus Desmet, Iyad Rahwan, Ángel Cuevas
Publié dans: Journal of the Royal Society Interface, 2022, ISSN 1742-5689
Éditeur: The Royal Society
DOI: 10.3386/w27827

A new methodology to measure faultlines at scale leveraging digital traces

Auteurs: Amir Mehrjoo, Rubén Cuevas, Ángel Cuevas
Publié dans: EPJ Data Science, Numéro 11, 2023, ISSN 2193-1127
Éditeur: Springer Nature SharedIt
DOI: 10.1140/epjds/s13688-022-00350-w

Book chapters (1)

Learning Type Inference for Enhanced Dataflow Analysis

Auteurs: Lukas Seidel, Sedick David Baker Effendi, Xavier Pinho, Konrad Rieck, Brink van der Merwe, Fabian Yamaguchi
Publié dans: Lecture Notes in Computer Science, Computer Security – ESORICS 2023, 2024, Page(s) 184-203
Éditeur: Springer Nature Switzerland
DOI: 10.1007/978-3-031-51482-1_10

Other (5)

ModSec-Learn: Boosting ModSecurity with Machine Learning

Auteurs: Christian Scano, Giuseppe Floris, Biagio Montaruli, Luca Demetrio, Andrea Valenza, Luca Compagna, Davide Ariu, Luca Piras, Davide Balzarotti, Battista Biggio
Publié dans: Computer Science > Machine Learning, 2024
Éditeur: arXiv e-prints
DOI: 10.48550/arxiv.2406.13547

Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing

Auteurs: Daniel Gibert, Luca Demetrio, Giulio Zizzo, Quan Le, Jordi Planes, Battista Biggio
Publié dans: Computer Science > Cryptography and Security, 2024
Éditeur: arXiv e-prints
DOI: 10.48550/arxiv.2405.00392

Adversarial ModSecurity: Countering Adversarial SQL Injections with Robust Machine Learning

Auteurs: Montaruli, Biagio; Demetrio, Luca; Valenza, Andrea; Compagna, Luca; Ariu, Davide; Piras, Luca; Balzarotti, Davide; Biggio, Battista
Publié dans: Computer Science - Machine Learning, Numéro 3, 2023
Éditeur: arXiv e-prints
DOI: 10.48550/arxiv.2308.04964

Rag and roll: An end-to-end evaluation of indirect prompt manipulations in llm-based application frameworks

Auteurs: De Stefano, Gianluca; Pellegrino, Giancarlo; Schönherr, Lea
Publié dans: Computer Science > Cryptography and Security, 2024
Éditeur: arXiv e-prints
DOI: 10.48550/arxiv.2408.05025

AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples

Auteurs: Cinà, Antonio Emanuele; Rony, Jérôme; Pintor, Maura; Demetrio, Luca; Demontis, Ambra; Biggio, Battista; Ayed, Ismail Ben; Roli, Fabio
Publié dans: Computer Science > Machine Learning, 2024
Éditeur: arXiv preprint
DOI: 10.48550/arxiv.2404.19460