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Sascha Fahl

Publications and source records attributed to Sascha Fahl.

15 recordsLinked to original sources

An Analysis of the Security, Usability, and Automation Capabilities of Password Update Processes on Top-Ranked Websites

Password updates are a critical part of the password lifecycle and are recommended following exposure of reused passwords or suspected compromise. However, password update processes are often cumbersome, require manual password creation, and involve inconsistent website workflows that hinder reliable automation by password managers. In this work, we conduct the first in-depth, systematic analysis of 111 password update processes deployed on top-ranked websites. We provide novel insights into their overall security, usability, and automation capabilities, and contribute to authentication security research by improving the understanding of password update processes. Websites often deploy highly diverse, complex, and confusing password update processes that are not supported by password managers. Processes are often challenging to use, and end-users struggle to transfer experience and knowledge across websites. Notably, security measures designed to enhance security often hinder password manager automation. We conclude our work by discussing our findings and giving recommendations for web developers, the web standardization community, and security researchers.

cs.CR

From Paranoia to Compliance: The Bumpy Road of System Hardening Practices on Stack Exchange

Hardening computer systems against cyberattacks is crucial for security. However, past incidents illustrated, that many system operators struggle with effective system hardening. Hence, many computer systems and applications remain insecure. So far, the research community lacks an in-depth understanding of system operators motivation, practices, and challenges around system hardening. With a focus on practices and challenges, we qualitatively analyzed 316 Stack Exchange (SE) posts related to system hardening. We find that access control and deployment-related issues are the most challenging, and system operators suffer from misconceptions and unrealistic expectations. Most frequently, posts focused on operating systems and server applications. System operators were driven by the fear of their systems getting attacked or by compliance reasons. Finally, we discuss our research questions, make recommendations for future system hardening, and illustrate the implications of our work.

cs.CR

"That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation

As generative AI is increasingly contributing to the spread of deceptively realistic misinformation, lawmakers have introduced regulations requiring the disclosure of AI-generated content. However, it is unclear if labels reduce the risk of users falling for AI-generated misinformation. To address this research gap, we study the effect of labels on users' perception and the implications of mislabeling, focusing on AI-generated images. We first explored users' opinions and expectations of labels using five focus groups. Although participants were wary of practical implementations, they considered labeling helpful in identifying AI-generated images and avoiding deception. Second, we conducted a survey with 1354 participants to assess how labels affect users' ability to recognize misinformation. While labels reduced participants' belief in false claims supported by AI-generated images, we found evidence of overreliance, leading to unintended side effects: Participants were more susceptible to false claims accompanied by human-made images, and were more hesitant to believe true claims illustrated with labeled AI-generated images.

cs.CR

Analyzing Challenges in Deployment of the SLSA Framework for Software Supply Chain Security

In 2023, Sonatype reported a 200\% increase in software supply chain attacks, including major build infrastructure attacks. To secure the software supply chain, practitioners can follow security framework guidance like the Supply-chain Levels for Software Artifacts (SLSA). However, recent surveys and industry summits have shown that despite growing interest, the adoption of SLSA is not widespread. To understand adoption challenges, \textit{the goal of this study is to aid framework authors and practitioners in improving the adoption and development of Supply-Chain Levels for Software Artifacts (SLSA) through a qualitative study of SLSA-related issues on GitHub}. We analyzed 1,523 SLSA-related issues extracted from 233 GitHub repositories. We conducted a topic-guided thematic analysis, leveraging the Latent Dirichlet Allocation (LDA) unsupervised machine learning algorithm, to explore the challenges of adopting SLSA and the strategies for overcoming these challenges. We identified four significant challenges and five suggested adoption strategies. The two main challenges reported are complex implementation and unclear communication, highlighting the difficulties in implementing and understanding the SLSA process across diverse ecosystems. The suggested strategies include streamlining provenance generation processes, improving the SLSA verification process, and providing specific and detailed documentation. Our findings indicate that some strategies can help mitigate multiple challenges, and some challenges need future research and tool enhancement.

cs.CE

How the Future Works at SOUPS: Analyzing Future Work Statements and Their Impact on Usable Security and Privacy Research

Extending knowledge by identifying and investigating valuable research questions and problems is a core function of research. Research publications often suggest avenues for future work to extend and build upon their results. Considering these suggestions can contribute to developing research ideas that build upon previous work and produce results that tie into existing knowledge. Usable security and privacy researchers commonly add future work statements to their publications. However, our community lacks an in-depth understanding of their prevalence, quality, and impact on future research. Our work aims to address this gap in the research literature. We reviewed all 27 papers from the 2019 SOUPS proceedings and analyzed their future work statements. Additionally, we analyzed 978 publications that cite any paper from SOUPS 2019 proceedings to assess their future work statements' impact. We find that most papers from the SOUPS 2019 proceedings include future work statements. However, they are often unspecific or ambiguous, and not always easy to find. Therefore, the citing publications often matched the future work statements' content thematically, but rarely explicitly acknowledged them, indicating a limited impact. We conclude with recommendations for the usable security and privacy community to improve the utility of future work statements by making them more tangible and actionable, and avenues for future work.

cs.CR

Using AI Assistants in Software Development: A Qualitative Study on Security Practices and Concerns

Following the recent release of AI assistants, such as OpenAI's ChatGPT and GitHub Copilot, the software industry quickly utilized these tools for software development tasks, e.g., generating code or consulting AI for advice. While recent research has demonstrated that AI-generated code can contain security issues, how software professionals balance AI assistant usage and security remains unclear. This paper investigates how software professionals use AI assistants in secure software development, what security implications and considerations arise, and what impact they foresee on secure software development. We conducted 27 semi-structured interviews with software professionals, including software engineers, team leads, and security testers. We also reviewed 190 relevant Reddit posts and comments to gain insights into the current discourse surrounding AI assistants for software development. Our analysis of the interviews and Reddit posts finds that despite many security and quality concerns, participants widely use AI assistants for security-critical tasks, e.g., code generation, threat modeling, and vulnerability detection. Their overall mistrust leads to checking AI suggestions in similar ways to human code, although they expect improvements and, therefore, a heavier use for security tasks in the future. We conclude with recommendations for software professionals to critically check AI suggestions, AI creators to improve suggestion security and capabilities for ethical security tasks, and academic researchers to consider general-purpose AI in software development.

cs.CR

"Make Them Change it Every Week!": A Qualitative Exploration of Online Developer Advice on Usable and Secure Authentication

Usable and secure authentication on the web and beyond is mission-critical. While password-based authentication is still widespread, users have trouble dealing with potentially hundreds of online accounts and their passwords. Alternatives or extensions such as multi-factor authentication have their own challenges and find only limited adoption. Finding the right balance between security and usability is challenging for developers. Previous work found that developers use online resources to inform security decisions when writing code. Similar to other areas, lots of authentication advice for developers is available online, including blog posts, discussions on Stack Overflow, research papers, or guidelines by institutions like OWASP or NIST. We are the first to explore developer advice on authentication that affects usable security for end-users. Based on a survey with 18 professional web developers, we obtained 406 documents and qualitatively analyzed 272 contained pieces of advice in depth. We aim to understand the accessibility and quality of online advice and provide insights into how online advice might contribute to (in)secure and (un)usable authentication. We find that advice is scattered and that finding recommendable, consistent advice is a challenge for developers, among others. The most common advice is for password-based authentication, but little for more modern alternatives. Unfortunately, many pieces of advice are debatable (e.g., complex password policies), outdated (e.g., enforcing regular password changes), or contradicting and might lead to unusable or insecure authentication. Based on our findings, we make recommendations for developers, advice providers, official institutions, and academia on how to improve online advice for developers.

cs.CR

"We've Disabled MFA for You": An Evaluation of the Security and Usability of Multi-Factor Authentication Recovery Deployments

Multi-Factor Authentication is intended to strengthen the security of password-based authentication by adding another factor, such as hardware tokens or one-time passwords using mobile apps. However, this increased authentication security comes with potential drawbacks that can lead to account and asset loss. If users lose access to their additional authentication factors for any reason, they will be locked out of their accounts. Consequently, services that provide Multi-Factor Authentication should deploy procedures to allow their users to recover from losing access to their additional factor that are both secure and easy-to-use. In this work, we investigate the security and user experience of Multi-Factor Authentication recovery procedures, and compare their deployment to descriptions on help and support pages. We first evaluate the official help and support pages of 1,303 websites that provide Multi-Factor Authentication and collect documented information about their recovery procedures. Second, we select a subset of 71 websites, create accounts, set up Multi-Factor Authentication, and perform an in-depth investigation of their recovery procedure security and user experience. We find that many websites deploy insecure Multi-Factor Authentication recovery procedures and allowed us to circumvent and disable Multi-Factor Authentication when having access to the accounts' associated email addresses. Furthermore, we commonly observed discrepancies between our in-depth analysis and the official help and support pages, implying that information meant to aid users is often either incorrect or outdated. Based on our findings, we provide recommendations for best practices regarding Multi-Factor Authentication recovery.

cs.CR

Pushed by Accident: A Mixed-Methods Study on Strategies of Handling Secret Information in Source Code Repositories

Version control systems for source code, such as Git, are key tools in modern software development. Many developers use services like GitHub or GitLab for collaborative software development. Many software projects include code secrets such as API keys or passwords that need to be managed securely. Previous research and blog posts found that developers struggle with secure code secret management and accidentally leaked code secrets to public Git repositories. Leaking code secrets to the public can have disastrous consequences, such as abusing services and systems or making sensitive user data available to attackers. In a mixed-methods study, we surveyed 109 developers with version control system experience. Additionally, we conducted 14 in-depth semi-structured interviews with developers who experienced secret leakage in the past. 30.3% of our participants encountered code secret leaks in the past. Most of them face several challenges with secret leakage prevention and remediation. Based on our findings, we discuss challenges, such as estimating the risks of leaked secrets, and the needs of developers in remediating and preventing code secret leaks, such as low adoption requirements. We conclude with recommendations for developers and source code platform providers to reduce the risk of secret leakage.

cs.CR

Privacy Rarely Considered: Exploring Considerations in the Adoption of Third-Party Services by Websites

Modern websites frequently use and embed third-party services to facilitate web development, connect to social media, or for monetization. This often introduces privacy issues as the inclusion of third-party services on a website can allow the third party to collect personal data about the website's visitors. While the prevalence and mechanisms of third-party web tracking have been widely studied, little is known about the decision processes that lead to websites using third-party functionality and whether efforts are being made to protect their visitors' privacy. We report results from an online survey with 395 participants involved in the creation and maintenance of websites. For ten common website functionalities we investigated if privacy has played a role in decisions about how the functionality is integrated, if specific efforts for privacy protection have been made during integration, and to what degree people are aware of data collection through third parties. We find that ease of integration drives third-party adoption but visitor privacy is considered if there are legal requirements or respective guidelines. Awareness of data collection and privacy risks is higher if the collection is directly associated with the purpose for which the third-party service is used.

cs.HC

"Please help share!": Security and Privacy Advice on Twitter during the 2022 Russian Invasion of Ukraine

The Russian Invasion of Ukraine in early 2022 resulted in a rapidly changing (cyber) threat environment. This changing environment incentivized the sharing of security advice on social media, both for the Ukrainian population, as well as against Russian cyber attacks at large. Previous research found a significant influence of online security advice on end users. We collected 8,920 tweets posted after the Russian Invasion of Ukraine and examined 1,228 in detail, including qualitatively coding 232 relevant tweets and 140 linked documents for security and privacy advice. We identified 221 unique pieces of advice which we divided into seven categories and 21 subcategories, and advice targeted at individuals or organizations. We then compared our findings to those of prior studies, finding noteworthy similarities. Our results confirm a lack of advice prioritization found by prior work, which seems especially detrimental during times of crisis. In addition, we find offers for individual support to be a valuable tool and identify misinformation as a rising threat in general and for security advice specifically.

cs.CR

(Un)informed Consent: Studying GDPR Consent Notices in the Field

Since the adoption of the General Data Protection Regulation (GDPR) in May 2018 more than 60 % of popular websites in Europe display cookie consent notices to their visitors. This has quickly led to users becoming fatigued with privacy notifications and contributed to the rise of both browser extensions that block these banners and demands for a solution that bundles consent across multiple websites or in the browser. In this work, we identify common properties of the graphical user interface of consent notices and conduct three experiments with more than 80,000 unique users on a German website to investigate the influence of notice position, type of choice, and content framing on consent. We find that users are more likely to interact with a notice shown in the lower (left) part of the screen. Given a binary choice, more users are willing to accept tracking compared to mechanisms that require them to allow cookie use for each category or company individually. We also show that the wide-spread practice of nudging has a large effect on the choices users make. Our experiments show that seemingly small implementation decisions can substantially impact whether and how people interact with consent notices. Our findings demonstrate the importance for regulation to not just require consent, but also provide clear requirements or guidance for how this consent has to be obtained in order to ensure that users can make free and informed choices.

cs.HC

A Large Scale Investigation of Obfuscation Use in Google Play

Android applications are frequently plagiarized or repackaged, and software obfuscation is a recommended protection against these practices. However, there is very little data on the overall rates of app obfuscation, the techniques used, or factors that lead to developers to choose to obfuscate their apps. In this paper, we present the first comprehensive analysis of the use of and challenges to software obfuscation in Android applications. We analyzed 1.7 million free Android apps from Google Play to detect various obfuscation techniques, finding that only 24.92% of apps are obfuscated by the developer. To better understand this rate of obfuscation, we surveyed 308 Google Play developers about their experiences and attitudes about obfuscation. We found that while developers feel that apps in general are at risk of plagiarism, they do not fear theft of their own apps. Developers also self-report difficulties applying obfuscation for their own apps. To better understand this, we conducted a follow-up study where the vast majority of 70 participants failed to obfuscate a realistic sample app even while many mistakenly believed they had been successful. Our findings show that more work is needed to make obfuscation tools more usable, to educate developers on the risk of their apps being reverse engineered, their intellectual property stolen, their apps being repackaged and redistributed as malware and to improve the health of the overall Android ecosystem.

cs.CR

Studying the Impact of Managers on Password Strength and Reuse

Despite their well-known security problems, passwords are still the incumbent authentication method for virtually all online services. To remedy the situation, end-users are very often referred to password managers as a solution to the password reuse and password weakness problems. However, to date the actual impact of password managers on password security and reuse has not been studied systematically. In this paper, we provide the first large-scale study of the password managers' influence on users' real-life passwords. From 476 participants of an online survey on users' password creation and management strategies, we recruit 170 participants that allowed us to monitor their passwords in-situ through a browser plugin. In contrast to prior work, we collect the passwords' entry methods (e.g., human or password manager) in addition to the passwords and their metrics. Based on our collected data and our survey, we gain a more complete picture of the factors that influence our participants' passwords' strength and reuse. We quantify for the first time that password managers indeed benefit the password strength and uniqueness, however, also our results also suggest that those benefits depend on the users' strategies and that managers without password generators rather aggravate the existing problems.

cs.CR

Stack Overflow Considered Harmful? The Impact of Copy&Paste on Android Application Security

Online programming discussion platforms such as Stack Overflow serve as a rich source of information for software developers. Available information include vibrant discussions and oftentimes ready-to-use code snippets. Anecdotes report that software developers copy and paste code snippets from those information sources for convenience reasons. Such behavior results in a constant flow of community-provided code snippets into production software. To date, the impact of this behaviour on code security is unknown. We answer this highly important question by quantifying the proliferation of security-related code snippets from Stack Overflow in Android applications available on Google Play. Access to the rich source of information available on Stack Overflow including ready-to-use code snippets provides huge benefits for software developers. However, when it comes to code security there are some caveats to bear in mind: Due to the complex nature of code security, it is very difficult to provide ready-to-use and secure solutions for every problem. Hence, integrating a security-related code snippet from Stack Overflow into production software requires caution and expertise. Unsurprisingly, we observed insecure code snippets being copied into Android applications millions of users install from Google Play every day. To quantitatively evaluate the extent of this observation, we scanned Stack Overflow for code snippets and evaluated their security score using a stochastic gradient descent classifier. In order to identify code reuse in Android applications, we applied state-of-the-art static analysis. Our results are alarming: 15.4% of the 1.3 million Android applications we analyzed, contained security-related code snippets from Stack Overflow. Out of these 97.9% contain at least one insecure code snippet.

cs.CR