skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: CRYLOGGER: Detecting Crypto Misuses Dynamically
Cryptographic (crypto) algorithms are the essential ingredients of all secure systems: crypto hash functions and encryption algorithms, for example, can guarantee properties such as integrity and confidentiality. Developers, however, can misuse the application programming interfaces (API) of such algorithms by using constant keys and weak passwords. This paper presents CRYLOGGER, the first open-source tool to detect crypto misuses dynamically. CRYLOGGER logs the parameters that are passed to the crypto APIs during the execution and checks their legitimacy offline by using a list of crypto rules. We compare CRYLOGGER with CryptoGuard, one of the most effective static tools to detect crypto misuses. We show that our tool complements the results of CryptoGuard, making the case for combining static and dynamic approaches. We analyze 1780 popular Android apps downloaded from the Google Play Store to show that CRYLOGGER can detect crypto misuses on thousands of apps dynamically and automatically. We reverse-engineer 28 Android apps and confirm the issues flagged by CRYLOGGER. We also disclose the most critical vulnerabilities to app developers and collect their feedback.  more » « less
Award ID(s):
1764000
PAR ID:
10244215
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Proceedings of the IEEE Symposium on Security and Privacy
Volume:
1
ISSN:
1063-9578
Page Range / eLocation ID:
160-177
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; (, IEEE Transactions on Software Engineering)
    Cryptographic (crypto) API misuses often cause security vulnerabilities, so static and dynamic analyzers were recently proposed to detect such misuses. These analyzers differ in strengths and weaknesses, and they can miss bugs. Motivated by the inherent limitations of existing analyzers, we study runtime verification (RV) as an alternative for crypto API misuse detection. RV monitors program runs against formal specifications and was shown to be effective and efficient for amplifying the bug-finding ability of software tests. We focus on the popular JCA crypto API and write 22 RV specifications based on expert-validated rules in a static analyzer. We monitor these specifications while running tests in five benchmarks. Lastly, we compare the accuracy of our RV-based approach, RVSec, with those of three state-of-the-art crypto API misuses detectors: CogniCrypt, CryptoGuard, and CryLogger. RVSec has higher accuracy in four benchmarks and is on par with CryptoGuard in the fifth. Overall, RVSec achieves an average F1 measure of 95%, compared with 83%, 78%, and 86% for CogniCrypt, CryptoGuard, and CryLogger, respectively. We show that RV is effective for detecting crypto API misuses and highlight the strengths and limitations of these tools. We also discuss how static and dynamic analysis can complement each other for detecting crypto API misuses. 
    more » « less
  2. ; ; ; ; (, ACM Transactions on Software Engineering and Methodology)
    Android is a highly fragmented platform with a diverse set of devices and users. To support the deployment of apps in such a heterogeneous setting, Android has introduceddynamic delivery—a new model of software deployment in which optional, device- or user-specific functionalities of an app, calledDynamic Feature Modules (DFMs), can be installed, as needed, after the app’s initial installation. This model of app deployment, however, has exacerbated the challenges of properly testing Android apps. In this article, we first describe the results of an extensive study in which we formalized a defect model representing the various conditions under which DFM installations may fail. We then presentDeltaDroid—a tool aimed at assisting the developers with validating dynamic delivery behavior in their apps by augmenting their existing test suite. Our experimental evaluation using real-world apps corroboratesDeltaDroid’s ability to detect many crashes and unexpected behaviors that the existing automated testing tools cannot reveal. 
    more » « less
  3. ; ; ; ; (, IEEE Transactions on Software Engineering)
    Several studies showed that misuses of cryptographic APIs are common in real-world code (e.g., Apache projects and Android apps). There exist several open-sourced and commercial security tools that automatically screen Java programs to detect misuses. To compare their accuracy and security guarantees, we develop two comprehensive benchmarks named CryptoAPI-Bench and ApacheCryptoAPI-Bench. CryptoAPI-Bench consists of 181 unit test cases that cover basic cases, as well as complex cases, including interprocedural, field sensitive, multiple class test cases, and path sensitive data flow of misuse cases. The benchmark also includes correct cases for testing false-positive rates. The ApacheCryptoAPI-Bench consists of 121 cryptographic cases from 10 Apache projects. We evaluate four tools, namely, SpotBugs, CryptoGuard, CrySL, and another tool (anonymous) using both benchmarks. We present their performance and comparative analysis. The ApacheCryptoAPI-Bench also examines the scalability of the tools. Our benchmarks are useful for advancing state-of-the-art solutions in the space of misuse detection. 
    more » « less
  4. ; ; ; ; (, Proceedings of the 27th USENIX Security Symposium)
    Mobile application security has been one of the major areas of security research in the last decade. Numerous application analysis tools have been proposed in response to malicious, curious, or vulnerable apps. However, existing tools, and specifically, static analysis tools, trade soundness of the analysis for precision and performance, and are hence soundy. Unfortunately, the specific unsound choices or flaws in the design of these tools are often not known or well-documented, leading to a misplaced confidence among researchers, developers, and users. This paper proposes the Mutation-based soundness evaluation (µSE) framework, which systematically evaluates Android static analysis tools to discover, document, and fix, flaws, by leveraging the well-founded practice of mutation analysis. We implement µSE as a semi-automated framework, and apply it to a set of prominent Android static analysis tools that detect private data leaks in apps. As the result of an in-depth analysis of one of the major tools, we discover 13 undocumented flaws. More importantly, we discover that all 13 flaws propagate to tools that inherit the flawed tool. We successfully fix one of the flaws in cooperation with the tool developers. Our results motivate the urgent need for systematic discovery and documentation of unsound choices in soundy tools, and demonstrate the opportunities in leveraging mutation testing in achieving this goal. 
    more » « less
  5. ; ; ; ; (, ACM Transactions on Privacy and Security)
    Mobile application security has been a major area of focus for security research over the course of the last decade. Numerous application analysis tools have been proposed in response to malicious, curious, or vulnerable apps. However, existing tools, and specifically, static analysis tools, trade soundness of the analysis for precision and performance and are hence sound y . Unfortunately, the specific unsound choices or flaws in the design of these tools is often not known or well documented, leading to misplaced confidence among researchers, developers, and users. This article describes the Mutation-Based Soundness Evaluation (μSE) framework, which systematically evaluates Android static analysis tools to discover, document, and fix flaws, by leveraging the well-founded practice of mutation analysis. We implemented μSE and applied it to a set of prominent Android static analysis tools that detect private data leaks in apps. In a study conducted previously, we used μSE to discover 13 previously undocumented flaws in FlowDroid, one of the most prominent data leak detectors for Android apps. Moreover, we discovered that flaws also propagated to other tools that build upon the design or implementation of FlowDroid or its components. This article substantially extends our μSE framework and offers a new in-depth analysis of two more major tools in our 2020 study; we find 12 new, undocumented flaws and demonstrate that all 25 flaws are found in more than one tool, regardless of any inheritance-relation among the tools. Our results motivate the need for systematic discovery and documentation of unsound choices in soundy tools and demonstrate the opportunities in leveraging mutation testing in achieving this goal. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email