Computer Viruses, in Order to Detect Them
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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 -
1.Computer Virus Reported (1) Summary for This Quarter
Attachment 1 1.Computer Virus Reported (1) Summary for this Quarter The number of the cases reported for viruses*1 in the first quarter of 2013 decreased from that of the fourth quarter of 2012 (See Figure 1-1). As for the number of the viruses detected*2 in the first quarter of 2013, W32/Mydoom accounted for three-fourths of the total (See Figure 1-2). Compared to the fourth quarter of 2012, however, both W32/Mydoom and W32/Netsky showed a decreasing trend. When we looked into the cases reported for W32/Netsky, we found that in most of those cases, the virus code had been corrupted, for which the virus was unable to carry out its infection activity. So, it is unlikely that the number of cases involving this virus will increase significantly in the future As for W32/IRCbot, it has greatly decreased from the level of the fourth quarter of 2012. W32/IRCbot carries out infection activities by exploiting vulnerabilities within Windows or programs, and is often used as a foothold for carrying out "Targeted Attack". It is likely that that there has been a shift to attacks not using this virus. XM/Mailcab is a mass-mailing type virus that exploits mailer's address book and distributes copies of itself. By carelessly opening this type of email attachment, the user's computer is infected and if the number of such users increases, so will the number of the cases reported. As for the number of the malicious programs detected in the first quarter of 2013, Bancos, which steals IDs/Passwords for Internet banking, Backdoor, which sets up a back door on the target PC, and Webkit, which guides Internet users to a maliciously-crafted Website to infect with another virus, were detected in large numbers. -
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. -
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. -
Hacking the Industrial Network
Hacking the industrial network A White Paper presented by: Phoenix Contact P.O. Box 4100 Harrisburg, PA 17111-0100 Phone: 717-944-1300 Fax: 717-944-1625 Website: www.phoenixcontact.com © PHOENIX CONTACT 1 Hacking the Industrial Network Is Your Production Line or Process Management System at Risk? The Problem Malicious code, a Trojan program deliberately inserted into SCADA system software, manipulated valve positions and compressor outputs to cause a massive natural gas explosion along the Trans-Siberian pipeline, according to 2005 testimony before a U.S. House of Representatives subcommittee by a Director from Sandia National Laboratories.1 According to the Washington Post, the resulting fireball yielded “the most monumental non-nuclear explosion and fire ever seen from space.”2 The explosion was subsequently estimated at the equivalent of 3 kilotons.3 (In comparison, the 9/11 explosions at the World Trade Center were roughly 0.1 kiloton.) According to Internet blogs and reports, hackers have begun to discover that SCADA (Supervisory Control and Data Acquisition) and DCS (Distributed Control Systems) are “cool” to hack.4 The interest of hackers has increased since reports of successful attacks began to emerge after 2001. A security consultant interviewed by the in-depth news program, PBS Frontline, told them “Penetrating a SCADA system that is running a Microsoft operating system takes less than two minutes.”5 DCS, SCADA, PLCs (Programmable Logic Controllers) and other legacy control systems have been used for decades in power plants and grids, oil and gas refineries, air traffic and railroad management, pipeline pumping stations, pharmaceutical plants, chemical plants, automated food and beverage lines, industrial processes, automotive assembly lines, and water treatment plants. -
Detecting Botnets Using File System Indicators
Detecting botnets using file system indicators Master's thesis University of Twente Author: Committee members: Peter Wagenaar Prof. Dr. Pieter H. Hartel Dr. Damiano Bolzoni Frank Bernaards LLM (NHTCU) December 12, 2012 Abstract Botnets, large groups of networked zombie computers under centralised control, are recognised as one of the major threats on the internet. There is a lot of research towards ways of detecting botnets, in particular towards detecting Command and Control servers. Most of the research is focused on trying to detect the commands that these servers send to the bots over the network. For this research, we have looked at botnets from a botmaster's perspective. First, we characterise several botnet enhancing techniques using three aspects: resilience, stealth and churn. We see that these enhancements are usually employed in the network communications between the C&C and the bots. This leads us to our second contribution: we propose a new botnet detection method based on the way C&C's are present on the file system. We define a set of file system based indicators and use them to search for C&C's in images of hard disks. We investigate how the aspects resilience, stealth and churn apply to each of the indicators and discuss countermeasures botmasters could take to evade detection. We validate our method by applying it to a test dataset of 94 disk images, 16 of which contain C&C installations, and show that low false positive and false negative ratio's can be achieved. Approaching the botnet detection problem from this angle is novel, which provides a basis for further research. -
System Center Endpoint Protection for Mac
System Center Endpoint Protection for Mac Installation Manual and User Guide Contents Context menu 19 System Center Endpoint Protection 3 System requirements 3 Advanced user 20 Import and export settings 20 Installation 4 Import settings 20 Typical installation 4 Export settings 20 Proxy server setup 20 Custom installation 4 Removable media blocking 20 Uninstallation 5 21 Beginners guide 6 Glossary Types of infiltrations 21 User interface 6 Viruses 21 Checking operation of the system 6 Worms 21 What to do if the program does not work properly 7 Trojan horses 21 Work with System Center Endpoint Adware 22 Spyware 22 Protection 8 Potentially unsafe applications 22 Antivirus and antispyware protection 8 Potentially unwanted applications 22 Real-time file system protection 8 Real-time Protection setup 8 Scan on (Event triggered scanning) 8 Advanced scan options 8 Exclusions from scanning 8 When to modify Real-time protection configuration 9 Checking Real-time protection 9 What to do if Real-time protection does not work 9 On-demand computer scan 10 Type of scan 10 Smart scan 10 Custom scan 11 Scan targets 11 Scan profiles 11 Engine parameters setup 12 Objects 12 Options 12 Cleaning 13 Extensions 13 Limits 13 Others 13 An infiltration is detected 14 Updating the program 14 Update setup 15 How to create update tasks 15 Upgrading to a new build 15 Scheduler 16 Purpose of scheduling tasks 16 Creating new tasks 16 Creating user-defined task 17 Quarantine 17 Quarantining files 17 Restoring from Quarantine 17 Log files 18 Log maintenance 18 Log filtering 18 User interface 18 Alerts and notifications 19 Alerts and notifications advanced setup 19 Privileges 19 System Center Endpoint Protection As the popularity of Unix-based operating systems increases, malware authors are developing more threats to target Mac users. -
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 -
Combating Spyware in the Enterprise.Pdf
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Symantec Internet Security Threat Report
Symantec Internet EXECUTIVE SUMMARY Symantec Internet Security Threat Report September 2003 EXECUTIVE EDITOR Executive Summary Linda McCarthy Symantec Office of the CTO The Symantec Internet Security Threat Report provides a six-month update about Internet threat MANAGER, DEVELOPMENT activity1. It includes analysis of network-based attacks, a review of known vulnerabilities, and David Ahmad Symantec Security Response highlights of malicious code. This summary of that report can alert executives to impending threats and current trends. SENIOR THREAT ANALYST Cori Lynn Arnold Symantec Managed Security With over 20,000 sensors monitoring network activity in over 180 countries, Symantec has Services established one of the most comprehensive sources of Internet threat data in the world, giving SENIOR MANAGER, ANALYSIS Symantec's analysts a superior source of attack data from which to spot important trends. OPERATIONS These trends educate executives about potential threats and exposures, and using the data Brian Dunphy Symantec Managed Security can help them identify weaknesses in their own security architecture or policies. Services In August 2003, the Win32.Blaster blended threat rapidly spread worldwide, and several other SENIOR MANAGER, DEVELOPMENT Oliver Friedrichs highly severe worms followed. In only eight days the pace and frequency of these threats created Symantec Security Response havoc for systems administrators as well as for PC home users, with an estimated cost of damages 2 RESEARCH FELLOW running up to $2 billion . This report