What Are Kernel-Mode Rootkits?
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Advance Dynamic Malware Analysis Using Api Hooking
www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume – 5 Issue -03 March, 2016 Page No. 16038-16040 Advance Dynamic Malware Analysis Using Api Hooking Ajay Kumar , Shubham Goyal Department of computer science Shivaji College, University of Delhi, Delhi, India [email protected] [email protected] Abstract— As in real world, in virtual world also there are type of Analysis is ineffective against many sophisticated people who want to take advantage of you by exploiting you software. Advanced static analysis consists of reverse- whether it would be your money, your status or your personal engineering the malware’s internals by loading the executable information etc. MALWARE helps these people into a disassembler and looking at the program instructions in accomplishing their goals. The security of modern computer order to discover what the program does. Advanced static systems depends on the ability by the users to keep software, analysis tells you exactly what the program does. OS and antivirus products up-to-date. To protect legitimate users from these threats, I made a tool B. Dynamic Malware Analysis (ADVANCE DYNAMIC MALWARE ANAYSIS USING API This is done by watching and monitoring the behavior of the HOOKING) that will inform you about every task that malware while running on the host. Virtual machines and software (malware) is doing over your machine at run-time Sandboxes are extensively used for this type of analysis. The Index Terms— API Hooking, Hooking, DLL injection, Detour malware is debugged while running using a debugger to watch the behavior of the malware step by step while its instructions are being processed by the processor and their live effects on I. -
HTTP Cookie - Wikipedia, the Free Encyclopedia 14/05/2014
HTTP cookie - Wikipedia, the free encyclopedia 14/05/2014 Create account Log in Article Talk Read Edit View history Search HTTP cookie From Wikipedia, the free encyclopedia Navigation A cookie, also known as an HTTP cookie, web cookie, or browser HTTP Main page cookie, is a small piece of data sent from a website and stored in a Persistence · Compression · HTTPS · Contents user's web browser while the user is browsing that website. Every time Request methods Featured content the user loads the website, the browser sends the cookie back to the OPTIONS · GET · HEAD · POST · PUT · Current events server to notify the website of the user's previous activity.[1] Cookies DELETE · TRACE · CONNECT · PATCH · Random article Donate to Wikipedia were designed to be a reliable mechanism for websites to remember Header fields Wikimedia Shop stateful information (such as items in a shopping cart) or to record the Cookie · ETag · Location · HTTP referer · DNT user's browsing activity (including clicking particular buttons, logging in, · X-Forwarded-For · Interaction or recording which pages were visited by the user as far back as months Status codes or years ago). 301 Moved Permanently · 302 Found · Help 303 See Other · 403 Forbidden · About Wikipedia Although cookies cannot carry viruses, and cannot install malware on 404 Not Found · [2] Community portal the host computer, tracking cookies and especially third-party v · t · e · Recent changes tracking cookies are commonly used as ways to compile long-term Contact page records of individuals' browsing histories—a potential privacy concern that prompted European[3] and U.S. -
E Cost of Ad Blocking Pagefair and Adobe 2015 Ad Blocking Report
!e cost of ad blocking PageFair and Adobe 2015 Ad Blocking Report Introduction In the third annual ad blocking report, PageFair, with the help of Adobe, provides updated data on the scale and growth of ad blocking so"ware usage and highlights the global and regional economic impact associated with it. Additionally, this report explores the early indications surrounding the impact of ad blocking within the mobile advertising space and how mobile will change the ad blocking landscape. Table of Contents 3. Key insights 8. Effect of ad blocking by industry 13. A"erword 4. Global ad blocking growth 9. Google Chrome still the main driver of ad 14. Background 5. Usage of ad blocking so"ware in the United block growth 15. Methodology States 10. Mobile is yet to be a factor in ad blocking 16. Tables 6. Usage of ad blocking so"ware in Europe growth 17. Tables 7. !e cost of blocking ads 11. Mobile will facilitate future ad blocking growth 12. Reasons to start using an ad blocker PAGEFAIR AND ADOBE | 2015 Ad Blocking Report 2 Key Insights More consumers block ads, continuing the strong growth rates seen during 2013 and 2014. 41% YoY global growth Q2 2014 - Q2 2015 !e "ndings • Globally, the number of people using ad blocking so"ware grew by 41% year over year. • 16% of the US online population blocked ads during Q2 2015. • Ad block usage in the United States grew 48% during the past year, increasing to 45 million monthly active 45 million users (MAUs) during Q2 2015. Average MAUs in the United • Ad block usage in Europe grew by 35% during the past year, increasing to 77 million monthly active users States Q2 2015 during Q2 2015. -
The Impact of Ad-Blockers on Online Consumer Behavior
Marketing Science Institute Working Paper Series 2021 Report No. 21-119 The Impact of Ad-blockers on Online Consumer Behavior Vilma Todri “The Impact of Ad-blockers on Online Consumer Behavior” © 2021 Vilma Todri MSI Working Papers are Distributed for the benefit of MSI corporate and academic members and the general public. Reports are not to be reproduced or published in any form or by any means, electronic or mechanical, without written permission. Marketing Science Institute Working Paper Series The Impact of Ad-blockers on Online Consumer Behavior Vilma Todri Goizueta Business School, Emory University, Atlanta, GA 30322 [email protected] Digital advertising is on track to become the dominant form of advertising but ad-blocking technologies have recently emerged posing a potential threat to the online advertising ecosystem. A significant and increasing fraction of Internet users has indeed already started employing ad-blockers. However, surprisingly little is known yet about the effects of ad-blockers on consumers. This paper investigates the impact of ad- blockers on online search and purchasing behaviors by empirically analyzing a consumer-level panel dataset. Interestingly, the analyses reveal that ad-blockers have a significant effect on online purchasing behavior: online consumer spending decreases due to ad-blockers by approximately $14:2 billion a year in total. In examining the underlying mechanism of the ad-blocker effects, I find that ad-blockers significantly decrease spending for brands consumers have not experienced before, partially shifting spending towards brands they have experienced in the past. I also find that ad-blockers spur additional unintended consequences as they reduce consumers' search activities across information channels. -
Strategies of Computer Worms
304543_ch09.qxd 1/7/05 9:05 AM Page 313 CHAPTER 9 Strategies of Computer Worms “Worm: n., A self-replicating program able to propagate itself across network, typically having a detrimental effect.” —Concise Oxford English Dictionary, Revised Tenth Edition 313 304543_ch09.qxd 1/7/05 9:05 AM Page 314 Chapter 9—Strategies of Computer Worms 9.1 Introduction This chapter discusses the generic (or at least “typical”) structure of advanced computer worms and the common strategies that computer worms use to invade new target systems. Computer worms primarily replicate on networks, but they represent a subclass of computer viruses. Interestingly enough, even in security research communities, many people imply that computer worms are dramatically different from computer viruses. In fact, even within CARO (Computer Antivirus Researchers Organization), researchers do not share a common view about what exactly can be classified as a “worm.” We wish to share a common view, but well, at least a few of us agree that all computer worms are ultimately viruses1. Let me explain. The network-oriented infection strategy is indeed a primary difference between viruses and computer worms. Moreover, worms usually do not need to infect files but propagate as standalone programs. Additionally, several worms can take con- trol of remote systems without any help from the users, usually exploiting a vul- nerability or set of vulnerabilities. These usual characteristics of computer worms, however, do not always hold. Table 9.1 shows several well-known threats. Table -
Paradise Lost , Book III, Line 18
_Paradise Lost_, book III, line 18 %%%%%%%%%%%%%%%%%%%%%%%% ++++++++++Hacker's Encyclopedia++++++++ ===========by Logik Bomb (FOA)======== <http://www.xmission.com/~ryder/hack.html> ---------------(1997- Revised Second Edition)-------- ##################V2.5################## %%%%%%%%%%%%%%%%%%%%%%%% "[W]atch where you go once you have entered here, and to whom you turn! Do not be misled by that wide and easy passage!" And my Guide [said] to him: "That is not your concern; it is his fate to enter every door. This has been willed where what is willed must be, and is not yours to question. Say no more." -Dante Alighieri _The Inferno_, 1321 Translated by John Ciardi Acknowledgments ---------------------------- Dedicated to all those who disseminate information, forbidden or otherwise. Also, I should note that a few of these entries are taken from "A Complete List of Hacker Slang and Other Things," Version 1C, by Casual, Bloodwing and Crusader; this doc started out as an unofficial update. However, I've updated, altered, expanded, re-written and otherwise torn apart the original document, so I'd be surprised if you could find any vestiges of the original file left. I think the list is very informative; it came out in 1990, though, which makes it somewhat outdated. I also got a lot of information from the works listed in my bibliography, (it's at the end, after all the quotes) as well as many miscellaneous back issues of such e-zines as _Cheap Truth _, _40Hex_, the _LOD/H Technical Journals_ and _Phrack Magazine_; and print magazines such as _Internet Underground_, _Macworld_, _Mondo 2000_, _Newsweek_, _2600: The Hacker Quarterly_, _U.S. News & World Report_, _Time_, and _Wired_; in addition to various people I've consulted. -
Will Ad Blocking Break the Internet?
NBER WORKING PAPER SERIES WILL AD BLOCKING BREAK THE INTERNET? Ben Shiller Joel Waldfogel Johnny Ryan Working Paper 23058 http://www.nber.org/papers/w23058 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 January 2017 Johnny Ryan is an employee of PageFair, a firm that measures the extent of ad blocking and offers ad-recovery technologies that enable publishers to display ads in a manner that adblockers cannot block. Neither Shiller nor Waldfogel has received any compensation for the research in the paper. PageFair was allowed to review the paper for accuracy but did not have control over the paper's findings nor conclusions. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2017 by Ben Shiller, Joel Waldfogel, and Johnny Ryan. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Will Ad Blocking Break the Internet? Ben Shiller, Joel Waldfogel, and Johnny Ryan NBER Working Paper No. 23058 January 2017 JEL No. L81,L82 ABSTRACT Ad blockers allow Internet users to obtain information without generating ad revenue for site owners; and by 2016 they were used by roughly a quarter of site visitors. Given the ad-supported nature of much of the web, ad blocking poses a threat to site revenue and, if revenue losses undermine investment, a possible threat to consumers' access to appealing content. -
Tangled Web : Tales of Digital Crime from the Shadows of Cyberspace
TANGLED WEB Tales of Digital Crime from the Shadows of Cyberspace RICHARD POWER A Division of Macmillan USA 201 West 103rd Street, Indianapolis, Indiana 46290 Tangled Web: Tales of Digital Crime Associate Publisher from the Shadows of Cyberspace Tracy Dunkelberger Copyright 2000 by Que Corporation Acquisitions Editor All rights reserved. No part of this book shall be reproduced, stored in a Kathryn Purdum retrieval system, or transmitted by any means, electronic, mechanical, pho- Development Editor tocopying, recording, or otherwise, without written permission from the Hugh Vandivier publisher. No patent liability is assumed with respect to the use of the infor- mation contained herein. Although every precaution has been taken in the Managing Editor preparation of this book, the publisher and author assume no responsibility Thomas Hayes for errors or omissions. Nor is any liability assumed for damages resulting from the use of the information contained herein. Project Editor International Standard Book Number: 0-7897-2443-x Tonya Simpson Library of Congress Catalog Card Number: 00-106209 Copy Editor Printed in the United States of America Michael Dietsch First Printing: September 2000 Indexer 02 01 00 4 3 2 Erika Millen Trademarks Proofreader Benjamin Berg All terms mentioned in this book that are known to be trademarks or ser- vice marks have been appropriately capitalized. Que Corporation cannot Team Coordinator attest to the accuracy of this information. Use of a term in this book should Vicki Harding not be regarded as affecting the validity of any trademark or service mark. Design Manager Warning and Disclaimer Sandra Schroeder Every effort has been made to make this book as complete and as accurate Cover Designer as possible, but no warranty or fitness is implied. -
Discontinued Browsers List
Discontinued Browsers List Look back into history at the fallen windows of yesteryear. Welcome to the dead pool. We include both officially discontinued, as well as those that have not updated. If you are interested in browsers that still work, try our big browser list. All links open in new windows. 1. Abaco (discontinued) http://lab-fgb.com/abaco 2. Acoo (last updated 2009) http://www.acoobrowser.com 3. Amaya (discontinued 2013) https://www.w3.org/Amaya 4. AOL Explorer (discontinued 2006) https://www.aol.com 5. AMosaic (discontinued in 2006) No website 6. Arachne (last updated 2013) http://www.glennmcc.org 7. Arena (discontinued in 1998) https://www.w3.org/Arena 8. Ariadna (discontinued in 1998) http://www.ariadna.ru 9. Arora (discontinued in 2011) https://github.com/Arora/arora 10. AWeb (last updated 2001) http://www.amitrix.com/aweb.html 11. Baidu (discontinued 2019) https://liulanqi.baidu.com 12. Beamrise (last updated 2014) http://www.sien.com 13. Beonex Communicator (discontinued in 2004) https://www.beonex.com 14. BlackHawk (last updated 2015) http://www.netgate.sk/blackhawk 15. Bolt (discontinued 2011) No website 16. Browse3d (last updated 2005) http://www.browse3d.com 17. Browzar (last updated 2013) http://www.browzar.com 18. Camino (discontinued in 2013) http://caminobrowser.org 19. Classilla (last updated 2014) https://www.floodgap.com/software/classilla 20. CometBird (discontinued 2015) http://www.cometbird.com 21. Conkeror (last updated 2016) http://conkeror.org 22. Crazy Browser (last updated 2013) No website 23. Deepnet Explorer (discontinued in 2006) http://www.deepnetexplorer.com 24. Enigma (last updated 2012) No website 25. -
A Malware Analysis and Artifact Capture Tool Dallas Wright Dakota State University
Dakota State University Beadle Scholar Masters Theses & Doctoral Dissertations Spring 3-2019 A Malware Analysis and Artifact Capture Tool Dallas Wright Dakota State University Follow this and additional works at: https://scholar.dsu.edu/theses Part of the Information Security Commons, and the Systems Architecture Commons Recommended Citation Wright, Dallas, "A Malware Analysis and Artifact Capture Tool" (2019). Masters Theses & Doctoral Dissertations. 327. https://scholar.dsu.edu/theses/327 This Dissertation is brought to you for free and open access by Beadle Scholar. It has been accepted for inclusion in Masters Theses & Doctoral Dissertations by an authorized administrator of Beadle Scholar. For more information, please contact [email protected]. A MALWARE ANALYSIS AND ARTIFACT CAPTURE TOOL A dissertation submitted to Dakota State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Cyber Operations March 2019 By Dallas Wright Dissertation Committee: Dr. Wayne Pauli Dr. Josh Stroschein Dr. Jun Liu ii iii Abstract Malware authors attempt to obfuscate and hide their execution objectives in their program’s static and dynamic states. This paper provides a novel approach to aid analysis by introducing a malware analysis tool which is quick to set up and use with respect to other existing tools. The tool allows for the intercepting and capturing of malware artifacts while providing dynamic control of process flow. Capturing malware artifacts allows an analyst to more quickly and comprehensively understand malware behavior and obfuscation techniques and doing so interactively allows multiple code paths to be explored. The faster that malware can be analyzed the quicker the systems and data compromised by it can be determined and its infection stopped. -
The Norman Book on Computer Viruses Ii Z the Norman Book on Computer Viruses
The Norman Book on Computer Viruses ii z The Norman Book on Computer Viruses Norman ASA is not liable for any other form of loss or damage arising from use of the documentation or from errors or deficiencies therein, including but not limited to loss of earnings. In particular, and without the limitations imposed by the licensing agreement with regard to any special use or purpose, Norman ASA will in no event be liable for loss of profits or other commercial damage including but not limited to incidental or consequential damages. The information in this document as well as the functionality of the software is subject to change without notice. No part of this documentation may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording or information storage and retrieval systems, for any purpose other than the purchaser's personal use, without the explicit written permission of Norman ASA. Contributors to The Norman Book on Viruses: Snorre Fagerland, Sylvia Moon, Kenneth Walls, Carl Bretteville Edited by Camilla Jaquet and Yngve Ness The Norman logo is a registered trademark of Norman ASA. Names of products mentioned in this documentation are either trademarks or registered trademarks of their respective owners. They are mentioned for identification purposes only. Norman documentation is Copyright © 1990-2002 Norman ASA. All rights reserved. October 2001 Copyright © 1990-2002 Norman z iii Norman Offices Norman Data Defense Systems Pty Ltd 6 Sarton Road, Clayton, Victoria, 3168 Australia. Tel: +61 3 9562 7655 Fax: +61 3 9562 9663 E-mail: [email protected] Web: http://www.norman.com.au Norman Data Defense Systems A/S Dronningensgade 23, DK-5000 Odense C, Denmark Tel. -
Detecting and Analyzing Insecure Component Integration
Taeho Kwon December 2011 Computer Science Detecting and Analyzing Insecure Component Integration Abstract Component technologies have been widely adopted for designing and engineering software ap- plications and systems, which dynamically integrate software components to achieve desired func- tionalities. Engineering software in a component-based style has significant benefits, such as im- proved programmer productivity and software reliability. To support component integration, oper- ating systems allow an application to dynamically load and use a component. Although developers have frequently utilized such a system-level mechanism, programming errors can lead to insecure component integration and serious security vulnerabilities. The security and reliability impact of component integration has not yet been much explored. This dissertation systematically investigates security issues in dynamic component integration and their impact on software security. On the conceptual level, we formulate two types of insecure component integration—unsafe component loading and insecure component usage—and present practical, scalable techniques to detect and analyze them. Our techniques operate directly on soft- ware binaries and do not require source code. On the practical level, we have used them to discover new vulnerabilities in popular, real-world software, and show that insecure component integration is prevalent and can be exploited by attackers to subvert important software and systems. Our research has had substantial practical impact and helped