Part 2 of Examples of Malicious Computer Programs
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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. -
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 -
Synthesizing Near-Optimal Malware Specifications from Suspicious
Synthesizing Near-Optimal Malware Specifications from Suspicious Behaviors Somesh Jha∗, Matthew Fredrikson∗, Mihai Christodoresu†, Reiner Sailer‡, Xifeng Yan§ ∗University of Wisconsin–Madison, †Qualcomm Research Silicon Valley, ‡IBM T.J Watson Research Center, §University of California–Santa Barbara Abstract—Behavior-based detection techniques are a promis- and errors. ing solution to the problem of malware proliferation. However, We make the observation that behavioral specifications they require precise specifications of malicious behavior that do not result in an excessive number of false alarms, while still are best viewed as a form of discriminative specification.A remaining general enough to detect new variants before tradi- discriminative specification describes the unique properties tional signatures can be created and distributed. In this paper, of a given class, in contrast to the properties exhibited by we present an automatic technique for extracting optimally discriminative specifications a second mutually-exclusive class. This paper presents an , which uniquely identify a class automated technique that combines program analysis, graph of programs. Such a discriminative specification can be used by a behavior-based malware detector. Our technique, based mining, and stochastic optimization to synthesize malware on graph mining and stochastic optimization, scales to large behavior specifications. We represent program behaviors as classes of programs. When this work was originally published, graphs that are mined for discriminative patterns. As there the technique yielded favorable results on malware targeted are many ways in which malware can accomplish the same towards workstations (~86% detection rates on new malware). goal, we use these patterns as building blocks for construct- We believe that it can be brought to bear on emerging malware- based threats for new platforms, and discuss several promising ing discriminative specifications that are general across vari- avenues for future work in this direction. -
Cyber Warfare a “Nuclear Option”?
CYBER WARFARE A “NUCLEAR OPTION”? ANDREW F. KREPINEVICH CYBER WARFARE: A “NUCLEAR OPTION”? BY ANDREW KREPINEVICH 2012 © 2012 Center for Strategic and Budgetary Assessments. All rights reserved. About the Center for Strategic and Budgetary Assessments The Center for Strategic and Budgetary Assessments (CSBA) is an independent, nonpartisan policy research institute established to promote innovative thinking and debate about national security strategy and investment options. CSBA’s goal is to enable policymakers to make informed decisions on matters of strategy, secu- rity policy and resource allocation. CSBA provides timely, impartial, and insight- ful analyses to senior decision makers in the executive and legislative branches, as well as to the media and the broader national security community. CSBA encour- ages thoughtful participation in the development of national security strategy and policy, and in the allocation of scarce human and capital resources. CSBA’s analysis and outreach focus on key questions related to existing and emerging threats to US national security. Meeting these challenges will require transforming the national security establishment, and we are devoted to helping achieve this end. About the Author Dr. Andrew F. Krepinevich, Jr. is the President of the Center for Strategic and Budgetary Assessments, which he joined following a 21-year career in the U.S. Army. He has served in the Department of Defense’s Office of Net Assessment, on the personal staff of three secretaries of defense, the National Defense Panel, the Defense Science Board Task Force on Joint Experimentation, and the Defense Policy Board. He is the author of 7 Deadly Scenarios: A Military Futurist Explores War in the 21st Century and The Army and Vietnam. -
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 -
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. -
Computer Security CS 426 Lecture 15
Computer Security CS 426 Lecture 15 Malwares CS426 Fall 2010/Lecture 15 1 Trapdoor • SttitittSecret entry point into a system – Specific user identifier or password that circumvents normal security procedures. • Commonlyyy used by developers – Could be included in a compiler. CS426 Fall 2010/Lecture 15 2 Logic Bomb • Embedded in legitimate programs • Activated when specified conditions met – E.g., presence/absence of some file; Particular date/time or particular user • When triggered, typically damages system – Modify/delete files/disks CS426 Fall 2010/Lecture 15 3 Examppgle of Logic Bomb • In 1982 , the Trans-Siber ian Pipe line inc iden t occurred. A KGB operative was to steal the plans fhititdtltditfor a sophisticated control system and its software from a Canadian firm, for use on their Siberi an pi peli ne. The CIA was tippe d o ff by documents in the Farewell Dossier and had the company itlibbithinsert a logic bomb in the program for sabotage purposes. This eventually resulted in "the most monu mental non-nu clear ex plosion and fire ever seen from space“. CS426 Fall 2010/Lecture 15 4 Trojan Horse • Program with an overt Example: Attacker: (expected) and covert effect Place the following file cp /bin/sh /tmp/.xxsh – Appears normal/expected chmod u+s,o+x /tmp/.xxsh – Covert effect violates security policy rm ./ls • User tricked into executing ls $* Trojan horse as /homes/victim/ls – Expects (and sees) overt behavior – Covert effect performed with • Victim user’s authorization ls CS426 Fall 2010/Lecture 15 5 Virus • Self-replicating -
MODELING the PROPAGATION of WORMS in NETWORKS: a SURVEY 943 in Section 2, Which Set the Stage for Later Sections
942 IEEE COMMUNICATIONS SURVEYS & TUTORIALS, VOL. 16, NO. 2, SECOND QUARTER 2014 Modeling the Propagation of Worms in Networks: ASurvey Yini Wang, Sheng Wen, Yang Xiang, Senior Member, IEEE, and Wanlei Zhou, Senior Member, IEEE, Abstract—There are the two common means for propagating attacks account for 1/4 of the total threats in 2009 and nearly worms: scanning vulnerable computers in the network and 1/5 of the total threats in 2010. In order to prevent worms from spreading through topological neighbors. Modeling the propa- spreading into a large scale, researchers focus on modeling gation of worms can help us understand how worms spread and devise effective defense strategies. However, most previous their propagation and then, on the basis of it, investigate the researches either focus on their proposed work or pay attention optimized countermeasures. Similar to the research of some to exploring detection and defense system. Few of them gives a nature disasters, like earthquake and tsunami, the modeling comprehensive analysis in modeling the propagation of worms can help us understand and characterize the key properties of which is helpful for developing defense mechanism against their spreading. In this field, it is mandatory to guarantee the worms’ spreading. This paper presents a survey and comparison of worms’ propagation models according to two different spread- accuracy of the modeling before the derived countermeasures ing methods of worms. We first identify worms characteristics can be considered credible. In recent years, although a variety through their spreading behavior, and then classify various of models and algorithms have been proposed for modeling target discover techniques employed by them.