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Schwachstellenanalyse Reverse Engineering Von Android Apps

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Schwachstellenanalyse Reverse Engineering Von Android Apps

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Author : Daniel Szameitat
language : de
Publisher: GRIN Verlag
Release Date : 2014-10-08

Schwachstellenanalyse Reverse Engineering Von Android Apps written by Daniel Szameitat and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-08 with Computers categories.

Studienarbeit aus dem Jahr 2014 im Fachbereich Informatik - IT-Security, Hochschule Aalen, Sprache: Deutsch, Abstract: Diese Arbeit beschäftigt sich mit dem Auffinden von Schwachstellen in Android Apps. Der Leser dieser Arbeit soll in die Lage versetzt werden, die Sicherheit einer App beurteilen zu können. Damit richtet sich diese Arbeit vorrangig an Android Administratoren und Entwickler. Die beschriebenen Techniken sollten nur aus Eigenentwicklungen angewandt werden. Die Arbeit gliedert sich in vier logische Abschnitte. Am Anfang stehen Informationen zum Umgang mit Android und dem Google Play Store. Diese Informationen sind Grundlagen, welche wichtig für alle nachfolgenden Themen sind. Danach werden einige Schwachstellen, die häufig in Android Apps vorkommen, aufgezeigt und am praktischen Beispiel erläutert. Die letzten zwei Abschnitte stellen den Kern dieser Arbeit da, indem sie beschreiben, wie solche Schwachstellen gefunden werden können. In Abschnitt drei wird prinzipiell gezeigt, wie eine App aufgebaut ist und wie Quelltext aus einer App gewonnen wird. Der letzte Teil der Arbeit geht auf konkrete Analysetechniken ein. Insgesamt wird so der aktuelle Stand der Technik für Sicherheitsanalysen von Android beschrieben.

Schwachstellenanalyse Reverse Engineering Von Android Apps

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Author : Daniel Szameitat
language : de
Publisher: GRIN Verlag
Release Date : 2014-10-08

Mobile App Reverse Engineering

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Author : Abhinav Mishra
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-05-27

Mobile App Reverse Engineering written by Abhinav Mishra and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-27 with Computers categories.

Delve into the world of mobile application reverse engineering, learn the fundamentals of how mobile apps are created and their internals, and analyze application binaries to find security issues Key Features • Learn the skills required to reverse engineer mobile applications • Understand the internals of iOS and Android application binaries • Explore modern reverse engineering tools such as Ghidra, Radare2, Hopper, and more Book Description Mobile App Reverse Engineering is a practical guide focused on helping cybersecurity professionals scale up their mobile security skills. With the IT world's evolution in mobile operating systems, cybercriminals are increasingly focusing their efforts on mobile devices. This book enables you to keep up by discovering security issues through reverse engineering of mobile apps. This book starts with the basics of reverse engineering and teaches you how to set up an isolated virtual machine environment to perform reverse engineering. You'll then learn about modern tools such as Ghidra and Radare2 to perform reverse engineering on mobile apps as well as understand how Android and iOS apps are developed. Next, you'll explore different ways to reverse engineer some sample mobile apps developed for this book. As you advance, you'll learn how reverse engineering can help in penetration testing of Android and iOS apps with the help of case studies. The concluding chapters will show you how to automate the process of reverse engineering and analyzing binaries to find low-hanging security issues. By the end of this reverse engineering book, you'll have developed the skills you need to be able to reverse engineer Android and iOS apps and streamline the reverse engineering process with confidence. What you will learn • Understand how to set up an environment to perform reverse engineering • Discover how Android and iOS application packages are built • Reverse engineer Android applications and understand their internals • Reverse engineer iOS applications built using Objective C and Swift programming • Understand real-world case studies of reverse engineering • Automate reverse engineering to discover low-hanging vulnerabilities • Understand reverse engineering and how its defense techniques are used in mobile applications Who this book is for This book is for cybersecurity professionals, security analysts, mobile application security enthusiasts, and penetration testers interested in understanding the internals of iOS and Android apps through reverse engineering. Basic knowledge of reverse engineering as well as an understanding of mobile operating systems like iOS and Android and how mobile applications work on them are required.

Decompiling Android

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Author : Godfrey Nolan
language : en
Publisher: Apress
Release Date : 2012-09-12

Decompiling Android written by Godfrey Nolan and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-12 with Computers categories.

Decompiling Android looks at the the reason why Android apps can be decompiled to recover their source code, what it means to Android developers and how you can protect your code from prying eyes. This is also a good way to see how good and bad Android apps are constructed and how to learn from them in building your own apps. This is becoming an increasingly important topic as the Android marketplace grows and developers are unwittingly releasing the apps with lots of back doors allowing people to potentially obtain credit card information and database logins to back-end systems, as they don’t realize how easy it is to decompile their Android code. In depth examination of the Java and Android class file structures Tools and techniques for decompiling Android apps Tools and techniques for protecting your Android apps

Android Security

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Author : Anmol Misra
language : en
Publisher: CRC Press
Release Date : 2013-04-08

Android Security written by Anmol Misra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-08 with Computers categories.

Android Security: Attacks and Defenses is for anyone interested in learning about the strengths and weaknesses of the Android platform from a security perspective. Starting with an introduction to Android OS architecture and application programming, it will help readers get up to speed on the basics of the Android platform and its security issues. Explaining the Android security model and architecture, the book describes Android permissions, including Manifest permissions, to help readers analyze applications and understand permission requirements. It also rates the Android permissions based on security implications and covers JEB Decompiler. The authors describe how to write Android bots in JAVA and how to use reversing tools to decompile any Android application. They also cover the Android file system, including import directories and files, so readers can perform basic forensic analysis on file system and SD cards. The book includes access to a wealth of resources on its website: www.androidinsecurity.com. It explains how to crack SecureApp.apk discussed in the text and also makes the application available on its site. The book includes coverage of advanced topics such as reverse engineering and forensics, mobile device pen-testing methodology, malware analysis, secure coding, and hardening guidelines for Android. It also explains how to analyze security implications for Android mobile devices/applications and incorporate them into enterprise SDLC processes. The book’s site includes a resource section where readers can access downloads for applications, tools created by users, and sample applications created by the authors under the Resource section. Readers can easily download the files and use them in conjunction with the text, wherever needed. Visit www.androidinsecurity.com for more information.

Android Security

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Author : Anmol Misra
language : en
Publisher:
Release Date : 2016

Android Security written by Anmol Misra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Android (Electronic resource) categories.

Android Security: Attacks and Defenses is for anyone interested in learning about the strengths and weaknesses of the Android platform from a security perspective. Starting with an introduction to Android OS architecture and application programming, it will help readers get up to speed on the basics of the Android platform and its security issues. Explaining the Android security model and architecture, the book describes Android permissions, including Manifest permissions, to help readers analyze applications and understand permission requirements. It also rates the Android permissions based on security implications and covers JEB Decompiler. The authors describe how to write Android bots in JAVA and how to use reversing tools to decompile any Android application. They also cover the Android file system, including import directories and files, so readers can perform basic forensic analysis on file system and SD cards. The book includes access to a wealth of resources on its website: www.androidinsecurity.com. It explains how to crack SecureApp.apk discussed in the text and also makes the application available on its site. The book includes coverage of advanced topics such as reverse engineering and forensics, mobile device pen-testing methodology, malware analysis, secure coding, and hardening guidelines for Android. It also explains how to analyze security implications for Android mobile devices/applications and incorporate them into enterprise SDLC processes. The book's site includes a resource section where readers can access downloads for applications, tools created by users, and sample applications created by the authors under the Resource section. Readers can easily download the files and use them in conjunction with the text, wherever needed. Visit www.androidinsecurity.com for more information.

Stateful Detection Of Stealthy Behaviors In Android Apps

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Author : Mohsin Junaid
language : en
Publisher:
Release Date : 2019

Stateful Detection Of Stealthy Behaviors In Android Apps written by Mohsin Junaid and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Computer crimes categories.

The number of smartphones has increased greatly during the last few years. Among the popular mobile operating systems (such as iOS and Android) installed on these devices, Android captures most of the mobile market share. This also puts Android OS in a spotlight to attract malware attacks. A recent study shows that for the last two years, more than ∼99% of the mobile malware targeted Android OS [1]. Examples of such attacks are leakage of privacy-sensitive data available on the devices (such as phone number, contacts, photos, and SMS and call logs), recording audio and video files, silently making phone calls in the background, and encrypting device files. Many of them are profit-oriented (i.e., sending SMS to premium rate numbers can cause unexpected higher monthly bills for the users). Driven by the rich profit, the malware attacks are also becoming stealthier over time to maximize the long-term payoffs. A stealthy attack typically takes extra precautionary measures to stay undetected for a longer period of time. There are two types of stealthy attacks based on how stealth is achieved: (1) Type 1 attacks use hidden or uncommon program flows of Android apps to exhibit their malicious behaviors. (2) Type 2 attacks launch additional actions to hide their intended malicious behaviors. For example, the infamous Android.HeHe malware [2] carefully takes three actions to silently block incoming phone calls: that is, it mutes ringer just before the incoming call is notified on the device, blocks the phone call, and unmutes the ringer after call blocking. To combat such attacks, researchers have developed numerous techniques based on static analysis. Static analysis detects malicious behaviors by analyzing the app code without execution. It represents program logic in some model (such as a control flow graph)and analyzes the model to detect possible attacks. The effectiveness of a static analysis tool relies on three key elements: (i) the app model representing app behaviors, (ii) the attack model representing attack behaviors, and (iii) the attack detection algorithm which analyzes the app model. If any of the models and/or the algorithm is inadequate, then sophisticated attacks such as stealthy attacks discussed above cannot be detected. To this end, this dissertation develops methods to accurately model app and attack behaviors, and, based on those models, improves analysis algorithms to effectively detect malicious behaviors inAndroid apps. More specifically, the dissertation proposes two static analysis frameworks called Dexteroid and StateDroid to achieve these goals. The former identifies many hidden program flows and based on them, analyzes Android apps to detect malicious behaviors including type 1 stealthy attacks. The latter focuses on modeling of malware attacks and developing analysis techniques to detect the attacks such as type 2 stealthy attacks. Dexteroid identifies hidden program flows in Android apps by performing reverse engineering on life cycle models of Android components. The components are building blocks of Android apps and life cycle models describe components' behaviors. Dexteroid represents the reverse-engineered life cycle models as state machines and drives from the mall program flows which consist of component callback methods. The callback methods are analyzed to detect malicious behaviors, including those that are launched through hidden program flows. A prototype of Dexteroid is implemented as a static taint analysis tool. A novel implementation of taint analysis which maintains up to date values and states of program variables through symbol tables allows Dexteroid to detect many attacks with high accuracy. Current implementation detects two attacks: (1) leakage of private information, and (2) sending SMS to premium-rate numbers. Evaluation results on a Google Play and Genome Malware apps show that the proposed framework is effective and efficient in terms of precision, recall, and execution time. StateDroid focuses on detecting type 2 stealthy attacks which typically execute multiple actions to launch and hide their malicious behaviors. To detect them, the framework presents novel techniques, based on state machines, to construct accurate attack behaviors. An attack, represented by an attack state machine (ASM), has states and transitions; state represents status of the attack, and transition represents the executed action. The framework first detects actions of an attack, and then uses them with an ASM to detect the attack. Given an Android app as an input, StateDroid performs fine-grained static analysis and reports various detected stealthy behaviors (in one pass), including but not limited to sending SMS message, blocking phone call, removing app icon from launcher menu, recording an audio or video file, and setting device ringer to silent mode. A prototype of StateDroid framework is implemented, and evaluated extensively with ground truth dataset,1505 Google Play apps, and 1369 malicious apps including 94 notorious ransom ware apps. The experimental results demonstrate the efficacy and generality of StateDroid. The success of StateDroid will enable broader adoptions of formal methods in cyber defense.

The Android Malware Handbook

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Author : Qian Han
language : en
Publisher: No Starch Press
Release Date : 2023-11-07

The Android Malware Handbook written by Qian Han and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-07 with Computers categories.

Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system. This groundbreaking guide to Android malware distills years of research by machine learning experts in academia and members of Meta and Google’s Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today. Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud. You’ll: Dive deep into the source code of real malware Explore the static, dynamic, and complex features you can extract from malware for analysis Master the machine learning algorithms useful for malware detection Survey the efficacy of machine learning techniques at detecting common Android malware categories The Android Malware Handbook’s team of expert authors will guide you through the Android threat landscape and prepare you for the next wave of malware to come.

Tools For Program Understanding And Reverse Engineering Of Mobile Applications

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Author : Tuan Anh Nguyen
language : en
Publisher:
Release Date : 2017

Tools For Program Understanding And Reverse Engineering Of Mobile Applications written by Tuan Anh Nguyen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Application software categories.

Mobile software development is evolving rapidly. Software development includes computer programing, documenting, testing and bug fixing processes. These processes need a detail understanding of the application logic which often requires reverse-engineering their artifacts. My thesis identifies and addresses the following three problems in mobile software development, specifically in program understanding and reverse-engineering for mobile application development. (1) There is no graphical on-phone debugger. (2) The second problem is that mobile software programmers have to manually re-implement the conceptual screen drawings or sketches of graphical artists in code, which is cumbersome and expensive. (3) Companies try to ”go mobile” (by developing mobile apps). To do that understanding the high level business of their current legacy software systems is necessary but challenging. To address these three challenges, this dissertation introduces the following three innovations. (1) GROPG is the first graphical on-phone debugger. GROPG makes debugging mobile apps more convenient and productive than existing textbased on-phone debuggers. (2) REMAUI is a mobile digital screenshot and sketch reverse-engineering tool. REMAUI makes developing mobile user interface code easier. (3) RengLaDom is a legacy application reverse-engineering tool. RengLaDom can infer domain concepts from legacy source code. Specifically, (1) debugging mobile phone applications is hard, as current debugging techniques either require multiple computing devices or do not support graphical debugging. To address this problem we present GROPG, the first graphical on-phone debugger. We implement GROPG for Android and perform a preliminary evaluation on third-party applications. Our experiments suggest that GROPG can lower the overall debugging time of a comparable text-based on-phone debugger by up to 2/3. (2) Second, when developing the user interface code of a mobile application, a big gap exists between the sketches and digital conceptual drawings of graphic artists and working user interface code. Currently, programmers bridge this gap manually, by re-implementing the sketches and drawings in code, which is cumbersome and expensive. To bridge this gap, this dissertation introduces the first technique to automatically reverse engineer mobile application user interfaces from UI sketches, digital conceptual drawings, or screenshots (REMAUI). In our experiments on third party inputs, REMAUI's inferred runtime user interface hierarchies closely resembled the user interface runtime UI hierarchies of the applications that produced REMAUI's inputs. Further, the resulting screenshots closely resembled REMAUI's inputs and overall runtime was below one minute. (3) Finally, a promising approach to understanding the business functions implemented by a large-scale legacy application is to reverse engineer the full application code with all its complications into a high-level abstraction such as a design document that can focus exclusively on important domain concepts. Although much progress has been made, we encountered the following two problems. (a) Existing techniques often cannot distinguish between code that carries interesting domain concepts and code that merely provides low-level implementation services. (b) For an evaluation, given that design documents are typically not maintained throughout program development, how can we judge if the domain model inferred by a given technique is of a high quality? We address these problems by re-examining the notion of domain models in object-oriented development and encoding our understanding in a novel lightweight reverse engineering technique that pinpoints those program classes that likely carry domain concepts. We implement our techniques in a RengLaDom prototype tool for Java and compare how close our inferred domain models are to existing domain models. Given the lack of traditional domain models, we propose to use for such evaluation existing object-relational data persistence mappings (ORM), which map program classes to a relational database schema. The original application engineers carefully designed such mappings, consider them valuable, and maintain them as part of the application. After manually removing such OR mappings from open-source applications, our RengLaDom technique was able to reverse engineer domain models that are much closer to the original ORM domain models than the models produced by competing approaches, regardless of the particular ORM framework used. Additional experiments indicate that RengLaDom's ability to infer better domain models extends to a variety of non-ORM applications.

Android Malware Detection Through Permission And App Component Analysis Using Machine Learning Algorithms

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Author : Keyur Milind Kulkarni
language : en
Publisher:
Release Date : 2018

Android Malware Detection Through Permission And App Component Analysis Using Machine Learning Algorithms written by Keyur Milind Kulkarni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Android (Electronic resource) categories.

Improvement in technology has inevitably altered the tactic of criminals to thievery. In recent times, information is the real commodity and it is thus subject to theft as any other possessions: cryptocurrency, credit card numbers, and illegal digital material are on the top. If globally available platforms for smartphones are considered, the Android open source platform (AOSP) emerges as a prevailing contributor to the market and its popularity continues to intensify. Whilst it is beneficiary for users, this development simultaneously makes a prolific environment for exploitation by immoral developers who create malware or reuse software illegitimately acquired by reverse engineering. Android malware analysis techniques are broadly categorized into static and dynamic analysis. Many researchers have also used feature-based learning to build and sustain working security solutions. Although Android has its base set of permissions in place to protect the device and resources, it does not provide strong enough security framework to defend against attacks. This thesis presents several contributions in the domain of security of Android applications and the data within these applications. First, a brief survey of threats, vulnerability and security analysis tools for the AOSP is presented. Second, we develop and use a genre extraction algorithm for Android applications to check the availability of those applications in Google Play Store. Third, an algorithm for extracting unclaimed permissions is proposed which will give a set of unnecessary permissions for applications under examination. Finally, machine learning aided approaches for analysis of Android malware were adopted. Features including permissions, APIs, content providers, broadcast receivers, and services are extracted from benign (~2,000) and malware (5,560) applications and examined for evaluation. We create feature vector combinations using these features and feed these vectors to various classifiers. Based on the evaluation metrics of classifiers, we scrutinize classifier performance with respect to specific feature combination. Classifiers such as SVM, Logistic Regression and Random Forests spectacle a good performance whilst the dataset of combination of permissions and APIs records the maximum accuracy for Logistic Regression.

Schwachstellenanalyse Reverse Engineering Von Android Apps

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