The Trojan Wars: Building the Big Picture to Combat Efraud
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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. -
Miscellaneous: Malware Cont'd & Start on Bitcoin
Miscellaneous: Malware cont’d & start on Bitcoin CS 161: Computer Security Prof. Raluca Ada Popa April 19, 2018 Credit: some slides are adapted from previous offerings of this course Viruses vs. Worms VIRUS WORM Propagates By infecting Propagates automatically other programs By copying itself to target systems Usually inserted into A standalone program host code (not a standalone program) Another type of virus: Rootkits Rootkit is a ”stealthy” program designed to give access to a machine to an attacker while actively hiding its presence Q: How can it hide itself? n Create a hidden directory w /dev/.liB, /usr/src/.poop and similar w Often use invisiBle characters in directory name n Install hacked Binaries for system programs such as netstat, ps, ls, du, login Q: Why does it Become hard to detect attacker’s process? A: Can’t detect attacker’s processes, files or network connections By running standard UNIX commands! slide 3 Sony BMG copy protection rootkit scandal (2005) • Sony BMG puBlished CDs that apparently had copy protection (for DRM). • They essentially installed a rootkit which limited user’s access to the CD. • It hid processes that started with $sys$ so a user cannot disaBle them. A software engineer discovered the rootkit, it turned into a Big scandal Because it made computers more vulneraBle to malware Q: Why? A: Malware would choose names starting with $sys$ so it is hidden from antivirus programs Sony BMG pushed a patch … But that one introduced yet another vulneraBility So they recalled the CDs in the end Detecting Rootkit’s -
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 -
An Introduction to Malware
Downloaded from orbit.dtu.dk on: Sep 24, 2021 An Introduction to Malware Sharp, Robin Publication date: 2017 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Sharp, R. (2017). An Introduction to Malware. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. An Introduction to Malware Robin Sharp DTU Compute Spring 2017 Abstract These notes, written for use in DTU course 02233 on Network Security, give a short introduction to the topic of malware. The most important types of malware are described, together with their basic principles of operation and dissemination, and defenses against malware are discussed. Contents 1 Some Definitions............................2 2 Classification of Malware........................2 3 Vira..................................3 4 Worms................................ -
Symantec Intelligence Report: June 2011
Symantec Intelligence Symantec Intelligence Report: June 2011 Three-quarters of spam send from botnets in June, and three months on, Rustock botnet remains dormant as Cutwail becomes most active; Pharmaceutical spam in decline as new Wiki- pharmacy brand emerges Welcome to the June edition of the Symantec Intelligence report, which for the first time combines the best research and analysis from the Symantec.cloud MessageLabs Intelligence Report and the Symantec State of Spam & Phishing Report. The new integrated report, the Symantec Intelligence Report, provides the latest analysis of cyber security threats, trends and insights from the Symantec Intelligence team concerning malware, spam, and other potentially harmful business risks. The data used to compile the analysis for this combined report includes data from May and June 2011. Report highlights Spam – 72.9% in June (a decrease of 2.9 percentage points since May 2011): page 11 Phishing – One in 330.6 emails identified as phishing (a decrease of 0.05 percentage points since May 2011): page 14 Malware – One in 300.7 emails in June contained malware (a decrease of 0.12 percentage points since May 2011): page 15 Malicious Web sites – 5,415 Web sites blocked per day (an increase of 70.8% since May 2011): page 17 35.1% of all malicious domains blocked were new in June (a decrease of 1.7 percentage points since May 2011): page 17 20.3% of all Web-based malware blocked was new in June (a decrease of 4.3 percentage points since May 2011): page 17 Review of Spam-sending botnets in June 2011: page 3 Clicking to Watch Videos Leads to Pharmacy Spam: page 6 Wiki for Everything, Even for Spam: page 7 Phishers Return for Tax Returns: page 8 Fake Donations Continue to Haunt Japan: page 9 Spam Subject Line Analysis: page 12 Best Practices for Enterprises and Users: page 19 Introduction from the editor Since the shutdown of the Rustock botnet in March1, spam volumes have never quite recovered as the volume of spam in global circulation each day continues to fluctuate, as shown in figure 1, below. -
Downloading and Running
City Research Online City, University of London Institutional Repository Citation: Meng, X. (2018). An integrated networkbased mobile botnet detection system. (Unpublished Doctoral thesis, City, Universtiy of London) This is the accepted version of the paper. This version of the publication may differ from the final published version. Permanent repository link: https://openaccess.city.ac.uk/id/eprint/19840/ Link to published version: Copyright: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to. Reuse: Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. City Research Online: http://openaccess.city.ac.uk/ [email protected] AN INTEGRATED NETWORK- BASED MOBILE BOTNET DETECTION SYSTEM Xin Meng Department of Computer Science City, University of London This dissertation is submitted for the degree of Doctor of Philosophy City University London June 2017 Declaration I hereby declare that except where specific reference is made to the work of others, the contents of this dissertation are original and have not been submitted in whole or in part for consideration for any other degree or qualification in this, or any other University. This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration, except where specifically indicated in the text. -
Dgarchive a Deep Dive Into Domain Generating Malware
DGArchive A deep dive into domain generating malware Daniel Plohmann [email protected] 2015-12-03 | Botconf, Paris © 2015 Fraunhofer FKIE 1 About me Daniel Plohmann PhD candidate at University of Bonn, Germany Security Researcher at Fraunhofer FKIE Focus: Reverse Engineering / Malware Analysis / Automation Projects ENISA Botnet Study 2011 [1] Analysis Tools PyBox, IDAscope, DGArchive, … Botnet Analysis Gameover Zeus / P2P protocols [2] DGA-based Malware [1] http://www.enisa.europa.eu/act/res/botnets/botnets-measurement-detection-disinfection-and-defence [2] http://christian-rossow.de/publications/p2pwned-ieee2013.pdf © 2015 Fraunhofer FKIE 2 Agenda Intro: Domain Generation Algorithms / DGArchive Comparison of DGA Features Registration Status of DGA Domain Space Case Studies © 2015 Fraunhofer FKIE 3 Intro Domain Generation Algorithms © 2015 Fraunhofer FKIE 4 Domain Generation Algorithms Definitions Concept first described ~2008: Domain Flux Domain Generation Algorithm (DGA) An algorithm producing Command & Control rendezvous points dynamically Shared secret between malware running on compromised host and botmaster Seeds Collection of parameters influencing the output of the algorithm Algorithmically-Generated Domain (AGD) Domains resulting from a DGA © 2015 Fraunhofer FKIE 5 Domain Generation Algorithms Origin & History Feb 2006 Sality: dynamically generates 3rd-level domain part July 2007 Torpig: Report by Verisign includes DGA-like domains July 2007 Kraken: VirusTotal upload of binary using DDNS -
Banking Trojans: from Stone Age to Space Era
Europol Public Information Europol Public Information Banking Trojans: From Stone Age to Space Era A Joint Report by Check Point and Europol The Hague, 21/03/2017 Europol Public Information 1 / 16 Europol Public Information Contents 1 Introduction .............................................................................................................. 3 2 The Founding Fathers ................................................................................................ 3 3 The Current Top Tier ................................................................................................. 5 4 The Latest .................................................................................................................. 9 5 Mobile Threat .......................................................................................................... 10 6 Evolutionary Timeline ............................................................................................. 11 7 Impressions/Current Trends ................................................................................... 11 8 Banking Trojans: The Law Enforcement View ......................................................... 12 9 How are Banking Trojans used by Criminals? ......................................................... 13 10 How are the Criminals Structured? ......................................................................... 14 11 Building on Public-Private-Partnerships - The Law Enforcement Response ........... 15 12 How to Protect Yourself ......................................................................................... -
FORECAST – Skimming Off the Malware Cream
FORECAST – Skimming off the Malware Cream Matthias Neugschwandtner1, Paolo Milani Comparetti1, Gregoire Jacob2, and Christopher Kruegel2 1Vienna University of Technology, {mneug,pmilani}@seclab.tuwien.ac.at 2University of California, Santa Barbara, {gregoire,chris}@cs.ucsb.edu ABSTRACT Malware commonly employs various forms of packing and ob- To handle the large number of malware samples appearing in the fuscation to resist static analysis. Therefore, the most widespread wild each day, security analysts and vendors employ automated approach to the analysis of malware samples is currently based on tools to detect, classify and analyze malicious code. Because mal- executing the malicious code in a controlled environment to ob- ware is typically resistant to static analysis, automated dynamic serve its behavior. Dynamic analysis tools such as CWSandbox [3], analysis is widely used for this purpose. Executing malicious soft- Norman Sandbox and Anubis [13, 2] execute a malware sample in ware in a controlled environment while observing its behavior can an instrumented sandbox and record its interactions with system provide rich information on a malware’s capabilities. However, and network resources. This information can be distilled into a running each malware sample even for a few minutes is expensive. human-readable report that provides an analyst with a high level For this reason, malware analysis efforts need to select a subset of view of a sample’s behavior, but it can also be fed as input to fur- samples for analysis. To date, this selection has been performed ei- ther automatic analysis tasks. Execution logs and network traces ther randomly or using techniques focused on avoiding re-analysis provided by dynamic analysis have been used to classify malware of polymorphic malware variants [41, 23]. -
CS 3700 Networks and Distributed Systems
CS 3700 Networks and Distributed Systems Lecture 20: Malware/Botnets Slides stolen from Vern Paxson (ICSI) and Stefan Savage (UCSD) Motivation 2 Internet currently used for important services ! Financial transactions, medical records Increasingly used for critical services ! 911, surgical operations, water/electrical system control, remote controlled drones, etc. Networks more open than ever before ! Global, ubiquitous Internet, wireless Malicious Users 3 Miscreants, e.g. LulzSec ! In it for thrills, street cred, or just to learn ! Defacing web pages, spreading viruses, etc. Hacktivists, e.g. Anonymous ! Online political protests ! Stealing and revealing classified information Organized Crime ! Profit driven, online criminals ! Well organized, divisions of labor, highly motivated Network Security Problems 4 Host Compromise ! Attacker gains control of a host ! Can then be used to try and compromise others Denial-of-Service ! Attacker prevents legitimate users from gaining service Attack can be both ! E.g., host compromise that provides resources for denial-of- service Definitions 5 Virus ! Program that attaches itself to another program Worm ! Replicates itself over the network ! Usually relies on remote exploit (e.g. buffer overflow) Rootkit ! Program that infects the operating system (or even lower) ! Used for privilege elevation, and to hide files/processes Trojan horse ! Program that opens “back doors” on an infected host ! Gives the attacker remote access to machines Botnet ! A large group of Trojaned machines, controlled -
[Recognising Botnets in Organisations] Barry Weymes Number
[Recognising Botnets in Organisations] Barry Weymes Number: 662 A thesis submitted to the faculty of Computer Science, Radboud University in partial fulfillment of the requirements for the degree of Master of Science Eric Verheul, Chair Erik Poll Sander Peters (Fox-IT) Department of Computer Science Radboud University August 2012 Copyright © 2012 Barry Weymes Number: 662 All Rights Reserved ABSTRACT [Recognising Botnets in Organisations] Barry WeymesNumber: 662 Department of Computer Science Master of Science Dealing with the raise in botnets is fast becoming one of the major problems in IT. Their adaptable and dangerous nature makes detecting them difficult, if not impossible. In this thesis, we present how botnets function, how they are utilised and most importantly, how to limit their impact. DNS Dynamic Reputations Systems, among others, are an innovative new way to deal with this threat. By indexing individual DNS requests and responses together we can provide a fuller picture of what computer systems on a network are doing and can easily provide information about botnets within the organisation. The expertise and knowledge presented here comes from the IT security firm Fox-IT in Delft, the Netherlands. The author works full time as a security analyst there, and this rich environment of information in the field of IT security provides a deep insight into the current botnet environment. Keywords: [Botnets, Organisations, DNS, Honeypot, IDS] ACKNOWLEDGMENTS • I would like to thank my parents, whom made my time in the Netherlands possible. They paid my tuition, and giving me the privilege to follow my ambition of getting a Masters degree. • My dear friend Dave, always gets a mention in my thesis for asking the questions other dont ask. -
YOUR BABY MONITOR IS ATTACKING the GOVERNMENT a Perspective on Security Risks Today and a Look Towards the Future
YOUR BABY MONITOR IS ATTACKING THE GOVERNMENT A perspective on security risks today and a look towards the future Nick McKerrall | Threat Prevention Team ©2016 Check Point Software Technologies Ltd. 1 2016 Statistics 5.5 million “things” are getting connected 75% of the to the internet every organizations we day perform security checkups on have machines infected Every 32 minutes – Sensitive with bots data is sent outside the org Every 5 seconds – a host Every 4 minutes - a high accesses a malicious risk application is used website ©2016 Check Point Software Technologies Ltd. September 2016 World Cyber Threat Map Green – Low Risk Beige – Medium Pink – Higher Red – Highest White – Insufficient Data RED: Bolivia, Angola, Zambia, Botswana, Uganda, Mongolia, Sri Lanka, Vietnam ©2016 Check Point Software Technologies Ltd. 3 September 2016 ‘Most Wanted’ Malware 1. Conficker Worm – Botnet 2. Sality – Remote Access and Control 3. Locky – Ransomware (via mostly email) 4. Cutwail – Botnet (Spam/DDoS) 5. Zeus – Banking Trojan 6. Chanitor – Downloader 7. Tinba – Banking Trojan 8. Cryptowall – Ransomware (via exploit kits and phishing) 9. Blackhole – Exploit kit 10. Nivdort (Bayrob) – Multipurpose bot September 2016 ‘Mobile Most Wanted’ Malware 1. HummingBad – Android Rootkit 2. Triada – Android Backdoor 3. Ztorg - Application Dropper ©2016 Check Point Software Technologies Ltd. 4 The threat landscape is changing You need to dynamically adjust to new threat sources Attacks change geography all the time Malware is changing constantly Both in signature/variant and purpose We are seeing new levels of sophistication Malware is becoming big business Our approach to protecting networks needs to change ©2016 Check Point Software Technologies Ltd.