Computer Virus and Worms
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Statistical Structures: Fingerprinting Malware for Classification and Analysis
Statistical Structures: Fingerprinting Malware for Classification and Analysis Daniel Bilar Wellesley College (Wellesley, MA) Colby College (Waterville, ME) bilar <at> alum dot dartmouth dot org Why Structural Fingerprinting? Goal: Identifying and classifying malware Problem: For any single fingerprint, balance between over-fitting (type II error) and under- fitting (type I error) hard to achieve Approach: View binaries simultaneously from different structural perspectives and perform statistical analysis on these ‘structural fingerprints’ Different Perspectives Idea: Multiple perspectives may increase likelihood of correct identification and classification Structural Description Statistical static / Perspective Fingerprint dynamic? Assembly Count different Opcode Primarily instruction instructions frequency static distribution Win 32 API Observe API calls API call vector Primarily call made dynamic System Explore graph- Graph structural Primarily Dependence modeled control and properties static Graph data dependencies Fingerprint: Opcode frequency distribution Synopsis: Statically disassemble the binary, tabulate the opcode frequencies and construct a statistical fingerprint with a subset of said opcodes. Goal: Compare opcode fingerprint across non- malicious software and malware classes for quick identification and classification purposes. Main result: ‘Rare’ opcodes explain more data variation then common ones Goodware: Opcode Distribution 1, 2 ---------.exe Procedure: -------.exe 1. Inventoried PEs (EXE, DLL, ---------.exe etc) on XP box with Advanced Disk Catalog 2. Chose random EXE samples size: 122880 with MS Excel and Index totalopcodes: 10680 3, 4 your Files compiler: MS Visual C++ 6.0 3. Ran IDA with modified class: utility (process) InstructionCounter plugin on sample PEs 0001. 002145 20.08% mov 4. Augmented IDA output files 0002. 001859 17.41% push with PEID results (compiler) 0003. 000760 7.12% call and general ‘functionality 0004. -
Botnets, Cybercrime, and Cyberterrorism: Vulnerabilities and Policy Issues for Congress
Order Code RL32114 Botnets, Cybercrime, and Cyberterrorism: Vulnerabilities and Policy Issues for Congress Updated January 29, 2008 Clay Wilson Specialist in Technology and National Security Foreign Affairs, Defense, and Trade Division Botnets, Cybercrime, and Cyberterrorism: Vulnerabilities and Policy Issues for Congress Summary Cybercrime is becoming more organized and established as a transnational business. High technology online skills are now available for rent to a variety of customers, possibly including nation states, or individuals and groups that could secretly represent terrorist groups. The increased use of automated attack tools by cybercriminals has overwhelmed some current methodologies used for tracking Internet cyberattacks, and vulnerabilities of the U.S. critical infrastructure, which are acknowledged openly in publications, could possibly attract cyberattacks to extort money, or damage the U.S. economy to affect national security. In April and May 2007, NATO and the United States sent computer security experts to Estonia to help that nation recover from cyberattacks directed against government computer systems, and to analyze the methods used and determine the source of the attacks.1 Some security experts suspect that political protestors may have rented the services of cybercriminals, possibly a large network of infected PCs, called a “botnet,” to help disrupt the computer systems of the Estonian government. DOD officials have also indicated that similar cyberattacks from individuals and countries targeting economic, -
A the Hacker
A The Hacker Madame Curie once said “En science, nous devons nous int´eresser aux choses, non aux personnes [In science, we should be interested in things, not in people].” Things, however, have since changed, and today we have to be interested not just in the facts of computer security and crime, but in the people who perpetrate these acts. Hence this discussion of hackers. Over the centuries, the term “hacker” has referred to various activities. We are familiar with usages such as “a carpenter hacking wood with an ax” and “a butcher hacking meat with a cleaver,” but it seems that the modern, computer-related form of this term originated in the many pranks and practi- cal jokes perpetrated by students at MIT in the 1960s. As an example of the many meanings assigned to this term, see [Schneier 04] which, among much other information, explains why Galileo was a hacker but Aristotle wasn’t. A hack is a person lacking talent or ability, as in a “hack writer.” Hack as a verb is used in contexts such as “hack the media,” “hack your brain,” and “hack your reputation.” Recently, it has also come to mean either a kludge, or the opposite of a kludge, as in a clever or elegant solution to a difficult problem. A hack also means a simple but often inelegant solution or technique. The following tentative definitions are quoted from the jargon file ([jargon 04], edited by Eric S. Raymond): 1. A person who enjoys exploring the details of programmable systems and how to stretch their capabilities, as opposed to most users, who prefer to learn only the minimum necessary. -
The Downadup Codex a Comprehensive Guide to the Threat’S Mechanics
Security Response The Downadup Codex A comprehensive guide to the threat’s mechanics. Edition 2.0 Introduction Contents Introduction.............................................................1 Since its appearance in late-2008, the Downadup worm has become Editor’s Note............................................................5 one of the most wide-spread threats to hit the Internet for a number of Increase in exploit attempts against MS08-067.....6 years. A complex piece of malicious code, this threat was able to jump W32.Downadup infection statistics.........................8 certain network hurdles, hide in the shadows of network traffic, and New variants of W32.Downadup.B find new ways to propagate.........................................10 defend itself against attack with a deftness not often seen in today’s W32.Downadup and W32.Downadup.B threat landscape. Yet it contained few previously unseen features. What statistics................................................................12 set it apart was the sheer number of tricks it held up its sleeve. Peer-to-peer payload distribution...........................15 Geo-location, fingerprinting, and piracy...............17 It all started in late-October of 2008, we began to receive reports of A lock with no key..................................................19 Small improvements yield big returns..................21 targeted attacks taking advantage of an as-yet unknown vulnerability Attempts at smart network scanning...................23 in Window’s remote procedure call (RPC) service. Microsoft quickly Playing with Universal Plug and Play...................24 released an out-of-band security patch (MS08-067), going so far as to Locking itself out.................................................27 classify the update as “critical” for some operating systems—the high- A new Downadup variant?......................................29 Advanced crypto protection.................................30 est designation for a Microsoft Security Bulletin. -
Post-Mortem of a Zombie: Conficker Cleanup After Six Years Hadi Asghari, Michael Ciere, and Michel J.G
Post-Mortem of a Zombie: Conficker Cleanup After Six Years Hadi Asghari, Michael Ciere, and Michel J.G. van Eeten, Delft University of Technology https://www.usenix.org/conference/usenixsecurity15/technical-sessions/presentation/asghari This paper is included in the Proceedings of the 24th USENIX Security Symposium August 12–14, 2015 • Washington, D.C. ISBN 978-1-939133-11-3 Open access to the Proceedings of the 24th USENIX Security Symposium is sponsored by USENIX Post-Mortem of a Zombie: Conficker Cleanup After Six Years Hadi Asghari, Michael Ciere and Michel J.G. van Eeten Delft University of Technology Abstract more sophisticated C&C mechanisms that are increas- ingly resilient against takeover attempts [30]. Research on botnet mitigation has focused predomi- In pale contrast to this wealth of work stands the lim- nantly on methods to technically disrupt the command- ited research into the other side of botnet mitigation: and-control infrastructure. Much less is known about the cleanup of the infected machines of end users. Af- effectiveness of large-scale efforts to clean up infected ter a botnet is successfully sinkholed, the bots or zom- machines. We analyze longitudinal data from the sink- bies basically remain waiting for the attackers to find hole of Conficker, one the largest botnets ever seen, to as- a way to reconnect to them, update their binaries and sess the impact of what has been emerging as a best prac- move the machines out of the sinkhole. This happens tice: national anti-botnet initiatives that support large- with some regularity. The recent sinkholing attempt of scale cleanup of end user machines. -
A Taxonomy of Computer Worms ∗
A Taxonomy of Computer Worms ∗ † ‡ § ¶ Nicholas Vern Stuart Robert Weaver Paxson Staniford Cunningham UC Berkeley ICSI Silicon Defense MIT Lincoln Laboratory ABSTRACT 1. INTRODUCTION To understand the threat posed by computer worms, it is A computer worm is a program that self-propagates across necessary to understand the classes of worms, the attackers a network exploiting security or policy flaws in widely-used who may employ them, and the potential payloads. This pa- services. They are not a new phenomenon, having first per describes a preliminary taxonomy based on worm target gained widespread notice in 1988 [16]. discovery and selection strategies, worm carrier mechanisms, We distinguish between worms and viruses in that the worm activation, possible payloads, and plausible attackers latter infect otherwise non-mobile files and therefore require who would employ a worm. some sort of user action to abet their propagation. As such, viruses tend to propagate more slowly. They also have more Categories and Subject Descriptors mature defenses due to the presence of a large anti-virus industry that actively seeks to identify and control their D.4.6 [Operating Systems]: Security and Protection—In- spread. vasive Software We note, however, that the line between worms and viruses is not all that sharp. In particular, the contagion worms General Terms discussed in Staniford et al [47] might be considered viruses Security by the definition we use here, though not of the traditional form, in that they do not need the user to activate them, but Keywords instead they hide their spread in otherwise unconnected user activity. Thus, for ease of exposition, and for scoping our computer worms, mobile malicious code, taxonomy, attack- analysis, we will loosen our definition somewhat and term ers, motivation malicious code such as contagion, for which user action is not central to activation, as a type of worm. -
Automatic Classifying of Mac OS X Samples
Automatic Classifying of Mac OS X Samples Spencer Hsieh, Pin Wu and Haoping Liu Trend Micro Inc., Taiwan TREND MICRO LEGAL DISCLAIMER The information provided herein is for general information Contents and educational purposes only. It is not intended and should not be construed to constitute legal advice. The information contained herein may not be applicable to all situations and may not reflect the most current situation. Nothing contained herein should be relied on or acted 4 upon without the benefit of legal advice based on the particular facts and circumstances presented and nothing Introduction herein should be construed otherwise. Trend Micro reserves the right to modify the contents of this document at any time without prior notice. Translations of any material into other languages are intended solely as a convenience. Translation accuracy 6 is not guaranteed nor implied. If any questions arise related to the accuracy of a translation, please refer to Mac OS X Samples Dataset the original language official version of the document. Any discrepancies or differences created in the translation are not binding and have no legal effect for compliance or enforcement purposes. 10 Although Trend Micro uses reasonable efforts to include accurate and up-to-date information herein, Trend Micro makes no warranties or representations of any kind as Classification of Mach-O Files to its accuracy, currency, or completeness. You agree that access to and use of and reliance on this document and the content thereof is at your own risk. Trend Micro disclaims all warranties of any kind, express or implied. 11 Neither Trend Micro nor any party involved in creating, producing, or delivering this document shall be liable for any consequence, loss, or damage, including direct, Malware Families indirect, special, consequential, loss of business profits, or special damages, whatsoever arising out of access to, use of, or inability to use, or in connection with the use of this document, or any errors or omissions in the content 15 thereof. -
Analyzing Android Adware
San Jose State University SJSU ScholarWorks Master's Projects Master's Theses and Graduate Research Spring 2018 Analyzing Android Adware Supraja Suresh San Jose State University Follow this and additional works at: https://scholarworks.sjsu.edu/etd_projects Part of the Computer Sciences Commons Recommended Citation Suresh, Supraja, "Analyzing Android Adware" (2018). Master's Projects. 621. DOI: https://doi.org/10.31979/etd.7xqe-kdft https://scholarworks.sjsu.edu/etd_projects/621 This Master's Project is brought to you for free and open access by the Master's Theses and Graduate Research at SJSU ScholarWorks. It has been accepted for inclusion in Master's Projects by an authorized administrator of SJSU ScholarWorks. For more information, please contact [email protected]. Analyzing Android Adware A Project Presented to The Faculty of the Department of Computer Science San Jose State University In Partial Fulfillment of the Requirements for the Degree Master of Science by Supraja Suresh May 2018 ○c 2018 Supraja Suresh ALL RIGHTS RESERVED The Designated Project Committee Approves the Project Titled Analyzing Android Adware by Supraja Suresh APPROVED FOR THE DEPARTMENTS OF COMPUTER SCIENCE SAN JOSE STATE UNIVERSITY May 2018 Dr. Mark Stamp Department of Computer Science Dr. Katerina Potika Department of Computer Science Fabio Di Troia Department of Mathematics ABSTRACT Analyzing Android Adware by Supraja Suresh Most Android smartphone apps are free; in order to generate revenue, the app developers embed ad libraries so that advertisements are displayed when the app is being used. Billions of dollars are lost annually due to ad fraud. In this research, we propose a machine learning based scheme to detect Android adware based on static and dynamic features. -
The Botnet Chronicles a Journey to Infamy
The Botnet Chronicles A Journey to Infamy Trend Micro, Incorporated Rik Ferguson Senior Security Advisor A Trend Micro White Paper I November 2010 The Botnet Chronicles A Journey to Infamy CONTENTS A Prelude to Evolution ....................................................................................................................4 The Botnet Saga Begins .................................................................................................................5 The Birth of Organized Crime .........................................................................................................7 The Security War Rages On ........................................................................................................... 8 Lost in the White Noise................................................................................................................. 10 Where Do We Go from Here? .......................................................................................................... 11 References ...................................................................................................................................... 12 2 WHITE PAPER I THE BOTNET CHRONICLES: A JOURNEY TO INFAMY The Botnet Chronicles A Journey to Infamy The botnet time line below shows a rundown of the botnets discussed in this white paper. Clicking each botnet’s name in blue will bring you to the page where it is described in more detail. To go back to the time line below from each page, click the ~ at the end of the section. 3 WHITE -
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. -
A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics
UNIVERSIDAD POLITECNICA´ DE MADRID ESCUELA TECNICA´ SUPERIOR DE INGENIEROS INFORMATICOS´ A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics PH.D THESIS Platon Pantelis Kotzias Copyright c 2019 by Platon Pantelis Kotzias iv DEPARTAMENTAMENTO DE LENGUAJES Y SISTEMAS INFORMATICOS´ E INGENIERIA DE SOFTWARE ESCUELA TECNICA´ SUPERIOR DE INGENIEROS INFORMATICOS´ A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF: Doctor of Philosophy in Software, Systems and Computing Author: Platon Pantelis Kotzias Advisor: Dr. Juan Caballero April 2019 Chair/Presidente: Marc Dasier, Professor and Department Head, EURECOM, France Secretary/Secretario: Dario Fiore, Assistant Research Professor, IMDEA Software Institute, Spain Member/Vocal: Narseo Vallina-Rodriguez, Assistant Research Professor, IMDEA Networks Institute, Spain Member/Vocal: Juan Tapiador, Associate Professor, Universidad Carlos III, Spain Member/Vocal: Igor Santos, Associate Research Professor, Universidad de Deusto, Spain Abstract of the Dissertation Potentially unwanted programs (PUP) are a category of undesirable software that, while not outright malicious, can pose significant risks to users’ security and privacy. There exist indications that PUP prominence has quickly increased over the last years, but the prevalence of PUP on both consumer and enterprise hosts remains unknown. Moreover, many important aspects of PUP such as distribution vectors, code signing abuse, and economics also remain unknown. In this thesis, we empirically and sys- tematically analyze in both breadth and depth PUP abuse, prevalence, distribution, and economics. We make the following four contributions. First, we perform a systematic study on the abuse of Windows Authenticode code signing by PUP and malware.