Helmholtz Center for Information Security
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Efficient fuzz testing leveraging input, code, and execution
Get PDFAny kind of smart testing technique must be very efficient to be competitive with random fuzz testing. State-of the-art test generators are largely inferior to random testing in real world applications. This work proposes to gather and evaluate lightweight analyses that can enable the creation of an efficient and sufficiently effective analysis-assisted fuzz tester. The analyses shall leverage information sources apart from the program under test itself, such as e.g. descriptions of the targeted input format in the form of extended context-free grammars, or hardware counters. As the main contributions, an efficient framework for building fuzzers around given analyses will be created, and with its help analyses will be identified and categorized according to their performance
How Developers Debug Software- The DBGBENCH Dataset
Get PDFHow do professional software engineers debug computer programs? In an experiment with 27 real bugs that existed in several widely used programs, we invited 12 professional software engineers, who together spent one month on localizing, explaining, and fixing these bugs. This did not only allow us to study the various tools and strategies used to debug the same set of errors. We could also determine exactly which statements a developer would localize as faults, how a developer would diagnose and explain an error, and how a developer would fix an error --- all of which software engineering researchers seek to automate. Until now, it has been difficult to evaluate the effectiveness and utility of automated debugging techniques without a user study. We publish the collected data, called DbgBench, to facilitate the effective evaluation of automated fault localization, diagnosis, and repair techniques w.r.t. the judgement of human experts
Automatically Detecting the Misuse of Secrets: Foundations, Design Principles, and Applications
Get PDFWe develop foundations and several constructions for security protocols that can automatically detect, without false positives, if a secret (such as a key or password) has been misused. Such constructions can be used, e.g., to automatically shut down compromised services, or to automatically revoke misused secrets to minimize the effects of compromise. Our threat model includes malicious agents, (temporarily or permanently) compromised agents, and clones.
Previous works have studied domain-specific partial solutions to this problem. For example, Google’s Certificate Transparency aims to provide infrastructure to detect the misuse of a certificate authority’s signing key, logs have been used for detecting endpoint compromise, and protocols have been proposed to detect cloned RFID/smart cards. Contrary to these existing approaches, for which the designs are interwoven with domain-specific considerations and which usually do not enable fully automatic response (i.e., they need human assessment), our approach shows where automatic action is possible. Our results unify, provide design rationales, and suggest improvements for the existing domain-specific solutions.
Based on our analysis, we construct several mechanisms for the detection of misuse. Our mechanisms enable automatic response, such as revoking keys or shutting down services, thereby substantially limiting the impact of a compromise. In several case studies, we show how our mechanisms can be used to substantially increase the security guarantees of a wide range of systems, such as web logins, payment systems, or electronic door locks. For example, we propose and formally verify an improved version of Cloudflare’s Keyless SSL protocol that enables key misuse detection
