Symantec Internet Security Threat Report
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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. -
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. -
Undergraduate Report
UNDERGRADUATE REPORT Attack Evolution: Identifying Attack Evolution Characteristics to Predict Future Attacks by MaryTheresa Monahan-Pendergast Advisor: UG 2006-6 IINSTITUTE FOR SYSTEMSR RESEARCH ISR develops, applies and teaches advanced methodologies of design and analysis to solve complex, hierarchical, heterogeneous and dynamic problems of engineering technology and systems for industry and government. ISR is a permanent institute of the University of Maryland, within the Glenn L. Martin Institute of Technol- ogy/A. James Clark School of Engineering. It is a National Science Foundation Engineering Research Center. Web site http://www.isr.umd.edu Attack Evolution 1 Attack Evolution: Identifying Attack Evolution Characteristics To Predict Future Attacks MaryTheresa Monahan-Pendergast Dr. Michel Cukier Dr. Linda C. Schmidt Dr. Paige Smith Institute of Systems Research University of Maryland Attack Evolution 2 ABSTRACT Several approaches can be considered to predict the evolution of computer security attacks, such as statistical approaches and “Red Teams.” This research proposes a third and completely novel approach for predicting the evolution of an attack threat. Our goal is to move from the destructive nature and malicious intent associated with an attack to the root of what an attack creation is: having successfully solved a complex problem. By approaching attacks from the perspective of the creator, we will chart the way in which attacks are developed over time and attempt to extract evolutionary patterns. These patterns will eventually -
Exploring Corporate Decision Makers' Attitudes Towards Active Cyber
Protecting the Information Society: Exploring Corporate Decision Makers’ Attitudes towards Active Cyber Defence as an Online Deterrence Option by Patrick Neal A Dissertation Submitted to the College of Interdisciplinary Studies in Partial Fulfilment of the Requirements for the Degree of DOCTOR OF SOCIAL SCIENCES Royal Roads University Victoria, British Columbia, Canada Supervisor: Dr. Bernard Schissel February, 2019 Patrick Neal, 2019 COMMITTEE APPROVAL The members of Patrick Neal’s Dissertation Committee certify that they have read the dissertation titled Protecting the Information Society: Exploring Corporate Decision Makers’ Attitudes towards Active Cyber Defence as an Online Deterrence Option and recommend that it be accepted as fulfilling the dissertation requirements for the Degree of Doctor of Social Sciences: Dr. Bernard Schissel [signature on file] Dr. Joe Ilsever [signature on file] Ms. Bessie Pang [signature on file] Final approval and acceptance of this dissertation is contingent upon the candidate’s submission of the final copy of the dissertation to Royal Roads University. The dissertation supervisor confirms to have read this dissertation and recommends that it be accepted as fulfilling the dissertation requirements: Dr. Bernard Schissel[signature on file] Creative Commons Statement This work is licensed under the Creative Commons Attribution-NonCommercial- ShareAlike 2.5 Canada License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/2.5/ca/ . Some material in this work is not being made available under the terms of this licence: • Third-Party material that is being used under fair dealing or with permission. • Any photographs where individuals are easily identifiable. Contents Creative Commons Statement............................................................................................ -
CONTENTS in THIS ISSUE Fighting Malware and Spam
MARCH 2008 Fighting malware and spam CONTENTS IN THIS ISSUE 2 COMMENT EVASIVE ACTION Home (page) renovations Pandex has attracted very little attention from the media and generated little 3 NEWS discussion between malware Botherders herded researchers and among the 29A folds general populace. Chandra Prakash and Adam Thomas provide an overview of the Pandex operation and take an in-depth look at VIRUS PREVALENCE TABLE 3 the underlying code that has allowed this malware to evade detection for so long. 4 MALWARE ANALYSIS page 4 Pandex: the botnet that could PACKING A PUNCH In the fi nal part of the series on exepacker 9 FEATURE blacklisting, Robert Neumann takes a look at how all the processing and analysis techniques are put Exepacker blacklisting part 3 into practice in a real-life situation. page 9 15 CONFERENCE REPORT AVG TURNS 8 Black Hat DC and CCC 24C3 John Hawes gets his hands on a preview version of the latest offering from AVG. 18 PRODUCT REVIEW page 18 AVG Internet Security 8 22 END NOTES & NEWS This month: anti-spam news and events, and Ken Simpson considers the implications of rising spam volume despite increasing accuracy of content fi lters. ISSN 1749-7027 COMMENT ‘It is hoped that within all sizes of business. It is hoped that the comment facility will promote discussion among visitors and that the comment facility in some cases the more knowledgeable of VB’s readers will promote will be able to guide and assist those less well versed in discussion among the complexities of anti-malware technologies. -
GQ: Practical Containment for Measuring Modern Malware Systems
GQ: Practical Containment for Measuring Modern Malware Systems Christian Kreibich Nicholas Weaver Chris Kanich ICSI & UC Berkeley ICSI & UC Berkeley UC San Diego [email protected] [email protected] [email protected] Weidong Cui Vern Paxson Microsoft Research ICSI & UC Berkeley [email protected] [email protected] Abstract their behavior, sometimes only for seconds at a time (e.g., to un- Measurement and analysis of modern malware systems such as bot- derstand the bootstrapping behavior of a binary, perhaps in tandem nets relies crucially on execution of specimens in a setting that en- with static analysis), but potentially also for weeks on end (e.g., to ables them to communicate with other systems across the Internet. conduct long-term botnet measurement via “infiltration” [13]). Ethical, legal, and technical constraints however demand contain- This need to execute malware samples in a laboratory setting ex- ment of resulting network activity in order to prevent the malware poses a dilemma. On the one hand, unconstrained execution of the from harming others while still ensuring that it exhibits its inher- malware under study will likely enable it to operate fully as in- ent behavior. Current best practices in this space are sorely lack- tended, including embarking on a large array of possible malicious ing: measurement researchers often treat containment superficially, activities, such as pumping out spam, contributing to denial-of- sometimes ignoring it altogether. In this paper we present GQ, service floods, conducting click fraud, or obscuring other attacks a malware execution “farm” that uses explicit containment prim- by proxying malicious traffic. -
Flow-Level Traffic Analysis of the Blaster and Sobig Worm Outbreaks in an Internet Backbone
Flow-Level Traffic Analysis of the Blaster and Sobig Worm Outbreaks in an Internet Backbone Thomas Dübendorfer, Arno Wagner, Theus Hossmann, Bernhard Plattner ETH Zurich, Switzerland [email protected] DIMVA 2005, Wien, Austria Agenda 1) Introduction 2) Flow-Level Backbone Traffic 3) Network Worm Blaster.A 4) E-Mail Worm Sobig.F 5) Conclusions and Outlook © T. Dübendorfer (2005), TIK/CSG, ETH Zurich -2- 1) Introduction Authors Prof. Dr. Bernhard Plattner Professor, ETH Zurich (since 1988) Head of the Communication Systems Group at the Computer Engineering and Networks Laboratory TIK Prorector of education at ETH Zurich (since 2005) Thomas Dübendorfer Dipl. Informatik-Ing., ETH Zurich, Switzerland (2001) ISC2 CISSP (Certified Information System Security Professional) (2003) PhD student at TIK, ETH Zurich (since 2001) Network security research in the context of the DDoSVax project at ETH Further authors: Arno Wagner, Theus Hossmann © T. Dübendorfer (2005), TIK/CSG, ETH Zurich -3- 1) Introduction Worm Analysis Why analyse Internet worms? • basis for research and development of: • worm detection methods • effective countermeasures • understand network impact of worms Wasn‘t this already done by anti-virus software vendors? • Anti-virus software works with host-centric signatures Research method used 1. Execute worm code in an Internet-like testbed and observe infections 2. Measure packet-level traffic and determine network-centric worm signatures on flow-level 3. Extensive analysis of flow-level traffic of the actual worm outbreaks captured in a Swiss backbone © T. Dübendorfer (2005), TIK/CSG, ETH Zurich -4- 1) Introduction Related Work Internet backbone worm analyses: • Many theoretical worm spreading models and simulations exist (e.g. -
Workaround for Welchia and Sasser Internet Worms in Kumamoto University
Workaround for Welchia and Sasser Internet Worms in Kumamoto University Yasuo Musashi, Kenichi Sugitani,y and Ryuichi Matsuba,y Center for Multimedia and Information Technologies, Kumamoto University, Kumamoto 860-8555 Japan, E-mail: [email protected], yE-mail: [email protected], yE-mail: [email protected] Toshiyuki Moriyamaz Department of Civil Engineering, Faculty of Engineering, Sojo University, Ikeda, Kumamoto 860-0081 Japan, zE-mail: [email protected] Abstract: The syslog messages of the iplog-2.2.3 packet capture in the DNS servers in Ku- mamoto University were statistically investigated when receiving abnormal TCP packets from PC terminals infected with internet worms like W32/Welchia and/or W32/Sasser.D worms. The inter- esting results are obtained: (1) Initially, the W32/Welchia worm-infected PC terminals for learners (920 PCs) considerably accelerates the total W32/Welchia infection. (2) We can suppress quickly the W32/Sasser.D infection in our university when filtering the access between total and the PC terminal’s LAN segments. Therefore, infection of internet worm in the PC terminals for learners should be taken into consideration to suppress quickly the infection. Keywords: Welchia, Sasser, internet worm, system vulnerability, TCP port 135, TCP port 445, worm detection 1. Introduction defragmentation, TCP stream reassembling (state- less/stateful), and content matcher (detection engine). Recent internet worms (IW) are mainly categorized The other is iplog[11], a packet logger that is not so into two types, as follows: one is a mass-mailing-worm powerful as Snort but it is slim and light-weighted so (MMW) which transfers itself by attachment files of that it is useful to get an IP address of the client PC the E-mail and the other is a system-vulnerability- terminal. -
Shoot the Messenger: IM Worms Infectionvectors.Com June 2005
Shoot the Messenger: IM Worms infectionvectors.com June 2005 Overview Instant Messaging (IM) has rapidly gained popularity, making it an attractive medium for malware coders. However, without the universal interoperation of email, instant messaging worms have so far been much slower to propagate and gain widespread success compared to their SMTP-based cousins. As such, the amount of attention (and development) they have received from malware authors is significantly less than the mass mailer worms. Nonetheless, IM-based malware is a threat to all organizations and should be addressed by both policy and technical safeguards. IM-founded malware carries the same potential for compromising data as any other malcode (and has adopted the tactics of more successful varieties exceptionally quickly). This paper examines the development and importance of IM worms. Messaging Overview Instant messaging generically refers to real-time text communications between two or more clients (although, it is important to note many new services such as video and voice are available through these clients). Generally, messages are passed from a client to a server and vice versa. Some IM clients are capable of transmitting files between one another without a central server (once a communications channel is established) and can allow for a remarkable degree of command execution. This is represented simply below: Messaging Server Presence data transferred to clients from servers. Message/file transfer. Compatible Clients Shoot the Messenger: IM Worms 2 IM protocols range from relatively simple to quite complex and generally include some form of “presence” detection and notification (the ability to indicate whether a contact is online at any given time). -
The Blaster Worm: Then and Now
Worms The Blaster Worm: Then and Now The Blaster worm of 2003 infected at least 100,000 Microsoft Windows systems and cost millions in damage. In spite of cleanup efforts, an antiworm, and a removal tool from Microsoft, the worm persists. Observing the worm’s activity can provide insight into the evolution of Internet worms. MICHAEL n Wednesday, 16 July 2003, Microsoft and continued to BAILEY, EVAN Security Bulletin MS03-026 (www. infect new hosts COOKE, microsoft.com/security/incident/blast.mspx) more than a year later. By using a wide area network- FARNAM O announced a buffer overrun in the Windows monitoring technique that observes worm infection at- JAHANIAN, AND Remote Procedure Call (RPC) interface that could let tempts, we collected observations of the Blaster worm DAVID WATSON attackers execute arbitrary code. The flaw, which the during its onset in August 2003 and again in August 2004. University of Last Stage of Delirium (LSD) security group initially This let us study worm evolution and provides an excel- Michigan uncovered (http://lsd-pl.net/special.html), affected lent illustration of a worm’s four-phase life cycle, lending many Windows operating system versions, including insight into its latency, growth, decay, and persistence. JOSE NAZARIO NT 4.0, 2000, and XP. Arbor When the vulnerability was disclosed, no known How the Blaster worm attacks Networks public exploit existed, and Microsoft made a patch avail- The initial Blaster variant’s decompiled source code re- able through their Web site. The CERT Coordination veals its unique behavior (http://robertgraham.com/ Center and other security organizations issued advisories journal/030815-blaster.c). -
Computer Viruses, in Order to Detect Them
Behaviour-based Virus Analysis and Detection PhD Thesis Sulaiman Amro Al amro This thesis is submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy Software Technology Research Laboratory Faculty of Technology De Montfort University May 2013 DEDICATION To my beloved parents This thesis is dedicated to my Father who has been my supportive, motivated, inspired guide throughout my life, and who has spent every minute of his life teaching and guiding me and my brothers and sisters how to live and be successful. To my Mother for her support and endless love, daily prayers, and for her encouragement and everything she has sacrificed for us. To my Sisters and Brothers for their support, prayers and encouragements throughout my entire life. To my beloved Family, My Wife for her support and patience throughout my PhD, and my little boy Amro who has changed my life and relieves my tiredness and stress every single day. I | P a g e ABSTRACT Every day, the growing number of viruses causes major damage to computer systems, which many antivirus products have been developed to protect. Regrettably, existing antivirus products do not provide a full solution to the problems associated with viruses. One of the main reasons for this is that these products typically use signature-based detection, so that the rapid growth in the number of viruses means that many signatures have to be added to their signature databases each day. These signatures then have to be stored in the computer system, where they consume increasing memory space. Moreover, the large database will also affect the speed of searching for signatures, and, hence, affect the performance of the system. -
Chapter 3: Viruses, Worms, and Blended Threats
Chapter 3 Chapter 3: Viruses, Worms, and Blended Threats.........................................................................46 Evolution of Viruses and Countermeasures...................................................................................46 The Early Days of Viruses.................................................................................................47 Beyond Annoyance: The Proliferation of Destructive Viruses .........................................48 Wiping Out Hard Drives—CIH Virus ...................................................................48 Virus Programming for the Masses 1: Macro Viruses...........................................48 Virus Programming for the Masses 2: Virus Generators.......................................50 Evolving Threats, Evolving Countermeasures ..................................................................51 Detecting Viruses...................................................................................................51 Radical Evolution—Polymorphic and Metamorphic Viruses ...............................53 Detecting Complex Viruses ...................................................................................55 State of Virus Detection.........................................................................................55 Trends in Virus Evolution..................................................................................................56 Worms and Vulnerabilities ............................................................................................................57