Threatsaurus the A-Z of Computer and Data Security Threats 2 the A-Z of Computer and Data Security Threats
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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, -
Xbt.Doc.248.2.Pdf
MAY 25, 2018 United States District Court Southern District of Florida Miami Division CASE NO. 1:17-CV-60426-UU ALEKSEJ GUBAREV, XBT HOLDING S.A., AND WEBZILLA, INC., PLAINTIFFS, VS BUZZFEED, INC. AND BEN SMITH, DEFENDANTS Expert report of Anthony J. Ferrante FTI Consulting, Inc. 4827-3935-4214v.1 0100812-000009 Table of Contents Table of Contents .............................................................................................................................................. 1 Qualifications ..................................................................................................................................................... 2 Scope of Assignment ......................................................................................................................................... 3 Glossary of Important Terms ............................................................................................................................. 4 Executive Summary ........................................................................................................................................... 7 Methodology ..................................................................................................................................................... 8 Technical Investigation ................................................................................................................................ 8 Investigative Findings ....................................................................................................................................... -
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 Honeypot for Arbitrary Malware on USB Storage Devices
A Honeypot for Arbitrary Malware on USB Storage Devices Sebastian Poeplau Jan Gassen University of Bonn Elmar Gerhards-Padilla Institute of Computer Science 4 Fraunhofer FKIE Friedrich-Ebert-Allee 144 Cyber Defense research group 53113 Bonn Friedrich-Ebert-Allee 144 53113 Bonn Abstract—Malware is a serious threat for modern information be infected usually by pretending to be vulnerable computers technology. It is therefore vital to be able to detect and analyze or services. Most commonly, honeypots are run on dedicated such malicious software in order to develop contermeasures. systems, i. e. machines that are maintained exclusively for the Honeypots are a tool supporting that task—they collect malware samples for analysis. Unfortunately, existing honeypots concen- purpose of capturing malware. Honeypots enable researchers trate on malware that spreads over networks, thus missing any and anti-virus companies to analyze new types of malware and malware that does not use a network for propagation. to develop countermeasures, and they are vital in generating A popular network-independent technique for malware to signatures of previously unknown malware. Even though there spread is copying itself to USB flash drives. In this article we are various different honeypot concepts, they all face one basic present Ghost, a new kind of honeypot for such USB malware. problem: How to trick malware into infecting a honeypot It detects malware by simulating a removable device in software, thereby tricking malware into copying itself to the virtual device. machine? We explain the concept in detail and evaluate it using samples Many of the employed concepts make use of the fact that of wide-spread malware. -
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 -
Adware-Searchsuite
McAfee Labs Threat Advisory Adware-SearchSuite June 22, 2018 McAfee Labs periodically publishes Threat Advisories to provide customers with a detailed analysis of prevalent malware. This Threat Advisory contains behavioral information, characteristics and symptoms that may be used to mitigate or discover this threat, and suggestions for mitigation in addition to the coverage provided by the DATs. To receive a notification when a Threat Advisory is published by McAfee Labs, select to receive “Malware and Threat Reports” at the following URL: https://www.mcafee.com/enterprise/en-us/sns/preferences/sns-form.html Summary Detailed information about the threat, its propagation, characteristics and mitigation are in the following sections: Infection and Propagation Vectors Mitigation Characteristics and Symptoms Restart Mechanism McAfee Foundstone Services The Threat Intelligence Library contains the date that the above signatures were most recently updated. Please review the above mentioned Threat Library for the most up to date coverage information. Infection and Propagation Vectors Adware-SearchSuite is a "potentially unwanted program" (PUP). PUPs are any piece of software that a reasonably security- or privacy-minded computer user may want to be informed of and, in some cases, remove. PUPs are often made by a legitimate corporate entity for some beneficial purpose, but they alter the security state of the computer on which they are installed, or the privacy posture of the user of the system, such that most users will want to be aware of them. Mitigation Mitigating the threat at multiple levels like file, registry and URL could be achieved at various layers of McAfee products. Browse the product guidelines available here (click Knowledge Center, and select Product Documentation from the Support Content list) to mitigate the threats based on the behavior described in the Characteristics and symptoms section. -
A Crawler-Based Study of Spyware on the Web
A Crawler-based Study of Spyware on the Web Alexander Moshchuk, Tanya Bragin, Steven D. Gribble, and Henry M. Levy Department of Computer Science & Engineering University of Washington {anm, tbragin, gribble, levy}@cs.washington.edu Abstract servers [16]. The AOL scan mentioned above has provided simple summary statistics by directly examining desktop in- Malicious spyware poses a significant threat to desktop fections [2], while a recent set of papers have considered security and integrity. This paper examines that threat from user knowledge of spyware and its behavior [6, 29]. an Internet perspective. Using a crawler, we performed a In this paper we change perspective, examining the na- large-scale, longitudinal study of the Web, sampling both ture of the spyware threat not on the desktop but from an executables and conventional Web pages for malicious ob- Internet point of view. To do this, we conduct a large-scale jects. Our results show the extent of spyware content. For outward-looking study by crawling the Web, downloading example, in a May 2005 crawl of 18 million URLs, we found content from a large number of sites, and then analyzing it spyware in 13.4% of the 21,200 executables we identified. to determine whether it is malicious. In this way, we can At the same time, we found scripted “drive-by download” answer several important questions. For example: attacks in 5.9% of the Web pages we processed. Our analy- sis quantifies the density of spyware, the types of of threats, • How much spyware is on the Internet? and the most dangerous Web zones in which spyware is • Where is that spyware located (e.g., game sites, chil- likely to be encountered. -
PARK JIN HYOK, Also Known As ("Aka") "Jin Hyok Park," Aka "Pak Jin Hek," Case Fl·J 18 - 1 4 79
AO 91 (Rev. 11/11) Criminal Complaint UNITED STATES DISTRICT COURT for the RLED Central District of California CLERK U.S. DIS RICT United States ofAmerica JUN - 8 ?018 [ --- .. ~- ·~".... ~-~,..,. v. CENT\:y'\ l i\:,: ffl1G1 OF__ CAUFORN! BY .·-. ....-~- - ____D=E--..... PARK JIN HYOK, also known as ("aka") "Jin Hyok Park," aka "Pak Jin Hek," Case fl·J 18 - 1 4 79 Defendant. CRIMINAL COMPLAINT I, the complainant in this case, state that the following is true to the best ofmy knowledge and belief. Beginning no later than September 2, 2014 and continuing through at least August 3, 2017, in the county ofLos Angeles in the Central District of California, the defendant violated: Code Section Offense Description 18 U.S.C. § 371 Conspiracy 18 u.s.c. § 1349 Conspiracy to Commit Wire Fraud This criminal complaint is based on these facts: Please see attached affidavit. IBJ Continued on the attached sheet. Isl Complainant's signature Nathan P. Shields, Special Agent, FBI Printed name and title Sworn to before ~e and signed in my presence. Date: ROZELLA A OLIVER Judge's signature City and state: Los Angeles, California Hon. Rozella A. Oliver, U.S. Magistrate Judge Printed name and title -:"'~~ ,4G'L--- A-SA AUSAs: Stephanie S. Christensen, x3756; Anthony J. Lewis, x1786; & Anil J. Antony, x6579 REC: Detention Contents I. INTRODUCTION .....................................................................................1 II. PURPOSE OF AFFIDAVIT ......................................................................1 III. SUMMARY................................................................................................3 -
An API Honeypot for Ddos and XSS Analysis
An API Honeypot for DDoS and XSS Analysis G Leaden, Marcus Zimmermann, Casimer DeCusatis, Fellow, IEEE, and Alan G. Labouseur Marist College School of Computer Science and Mathematics Poughkeepsie, NY 12601 fG.Leaden1, Marcus.Zimmermann1, Casimer.DeCusatis, [email protected] Abstract—Honeypots are servers or systems built to mimic II. BACKGROUND critical parts of a network, distracting attackers while logging their information to develop attack profiles. This paper discusses Not long after making G-Star Studio available online, we the design and implementation of a honeypot disguised as a REp- observed a number of unauthorized connection attempts to resentational State Transfer (REST) Application Programming its Application Programming Interface (API). These attacks Interface (API). We discuss the motivation for this work, design specifically targeted G-star Studio’s REpresentational State features of the honeypot, and experimental performance results Transfer (REST) API. under various traffic conditions. We also present analyses of both a distributed denial of service (DDoS) attack and a cross-site A REST API is among the most commonly used API scripting (XSS) malware insertion attempt against this honeypot. architectures today [6]. There are many examples of recent attacks against REST APIs, including well-publicized attacks on the Nissan Leaf smart car [7] and the U.S. Internal Revenue Service database. Existing APIs do not always follow security I. INTRODUCTION best practices, and developers might be lulled into a false sense of security by believing that their API will not be an attack The number and severity of cyber attacks has grown signif- target. In an effort to improve the security of our SecureCloud icantly in recent years [1], [2]. -
Backdoors in Software: a Cycle of Fear and Uncertainty
BACKDOORS IN SOFTWARE: A CYCLE OF FEAR AND UNCERTAINTY Leah Holden, Tufts University, Medford, MA Abstract: With the advent of cryptography and an increasingly online world, an antagonist to the security provided by encryption has emerged: backdoors. Backdoors are slated as insidious but often they aren’t intended to be. Backdoors can just be abused maintenance accounts, exploited vulnerabilities, or created by another agent via infecting host servers with malware. We cannot ignore that they may also be intentionally programmed into the source code of an application. Like with the cyber attrition problem, it may be difficult to determine the root cause of a backdoor and challenging to prove its very existence. These characteristics of backdoors ultimately lead to a state of being that I liken to a cycle of fear where governments or companies throw accusations around, the public roasts the accused, and other companies live in fear of being next. Notably missing from this cycle are any concrete solutions for preventing backdoors. A pervasive problem underlies this cycle: backdoors could be mitigated if software developers and their managers fully embraced the concept that no one should ever be able to bypass authentication. From the Clipper chip to the FBI and Apple’s standoff, we will examine requested, suspected, and proven backdoors up through the end of 2017. We will also look at the aftermath of these incidents and their effect on the relationship between software and government. Introduction: A backdoor has been defined as both “an undocumented portal that allows an administrator to enter the system to troubleshoot or do upkeep” and “ a secret portal that hackers and intelligence agencies used to gain illicit access” (Zetter).