A Review of Zeroaccess Peer-To-Peer Botnet Ms
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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. -
Biuletyn 2016 1.Pdf
szkolenia badania raport zgłoszenie DBI.pl CERT.pl inicjatywy domena .pl bezpieczeństwo honeypot seminarium biometria eksperci konferencje dyżurnet.pl digitalizacja nauka BIPSE SPIS treści KONFERENCJE 5 Razem tworzymy lepszy Internet 7 Globalne wyzwanie – bezpieczny Internet dla dzieci i młodzieży 8 SECURE 2015 – Cyberpolicjanci kontra cyberprzestępcy WYDARZENIA 10 Piknik Naukowy 10 Festiwal Nauki 10 CyberPol – szkolenia dla Policji 11 Seminarium eksperckie 11 Konferencja naukowa „Nastolatki wobec internetu” 11 Sukces polskiej biometrii RAPORTY 12 Roczny raport CERT Polska za 2014 rok 13 Raport Dyżurnet.pl 15 Rekordowy III kwartał w rejestrze domeny .pl BADANIA 17 Nastolatki wobec internetu PROJEKTY 21 Malware kontra lodówka 22 Bezpieczne uwierzytelnienie we współczesnym świecie 24 Digitalizacja, cyfryzacja czyli dostępność…. BEZPIECZEńStwO 28 Cyberprzestępcy podszywają się pod Pocztę Polską 29 Dorkbot już nam nie zagraża ROZMOWA Z … 30 Senior dla kultury NR 1/2016 Redakcja: Anna Maj, Monika Gajewska-Pol Projekt okładki, skład i przygotowanie do druku: Anna Nykiel Adres: ul. Wąwozowa 18, 02-796 Warszawa, Redakcja zastrzega sobie prawo do skrótu tel. (22) 38 08 200, e-mail: [email protected] i opracowania redakcyjnego otrzymanych tekstów. Biuletyn Szanowni Państwo, Mam przyjemność zaprosić Państwa do lektury najnow- celu ochronę przed zagrożeniami najmłodszych użyt- szego numeru „Biuletynu NASK”. Prezentujemy w nim kowników internetu. W ramach realizowanego przez nasze osiągnięcia, najważniejsze wydarzenia minione- NASK projektu Safer Internet funkcjonuje zespół go roku, opisujemy ciekawe i ważne projekty oraz naj- Dyżurnet.pl, przyjmujący zgłoszenia o niebezpiecz- nowsze opracowane przez nas rozwiązania naukowe. nych treściach internetowych, które zagrażają dzie- ciom i młodzieży korzystającym z sieci. W czasie swo- NASK jest instytutem badawczym, który realizuje jej dziesięcioletniej działalności zespół przeanalizował liczne projekty naukowe oraz komercyjne, szczególnie blisko 45 tysięcy zgłoszeń. -
Cyberaanval Op Nederland Citadel-Malwareonderzoek “Pobelka” Botnet
Cyberaanval op Nederland Citadel-malwareonderzoek “Pobelka” botnet Cyberaanval op Nederland | Citadel-malwareonderzoek “Pobelka” botnet Pagina 1 Inhoudsopgave Inleiding ....................................................................................................................................................................................................... 3 Telegraaf.nl ............................................................................................................................................................................................ 3 Pobelka ........................................................................................................................................................................................................ 4 Doelgericht ............................................................................................................................................................................................ 4 Nederland............................................................................................................................................................................................... 5 Java exploits .......................................................................................................................................................................................... 5 Cyberincidenten .................................................................................................................................................................................. -
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 -
Threat Landscape Report
QUARTERLY Threat Landscape Report Q3 2020 NUSPIRE.COM THIS REPORT IS SOURCED FROM 90 BILLION TRAFFIC LOGS INGESTED FROM NUSPIRE CLIENT SITES AND ASSOCIATED WITH THOUSANDS OF DEVICES AROUND THE GLOBE. Nuspire Threat Report | Q2Q3 | 2020 Contents Introduction 4 Summary of Findings 6 Methodology and Overview 7 Quarter in Review 8 Malware 9 Botnets 15 Exploits 20 The New Normal 28 Conclusion and Recommendations 31 About Nuspire 33 3 | Contents Nuspire Threat Report | Q3 | 2020 Introduction In Q2 2020, Nuspire observed the increasing lengths threat actors were going to in order to capitalize on the pandemic and resulting crisis. New attack vectors were created; including VPN usage, home network security issues, personal device usage for business purposes and auditability of network traffic. In Q3 2020, we’ve observed threat actors become even more ruthless. Shifting focus from home networks to overburdened public entities including the education sector and the Election Assistance Commission (EAC). Many school districts were forced into 100% virtual or hybrid learning models by the pandemic. Attackers have waged ransomware attacks at learning institutions who not only have the financial resources to pay ransoms but feel a sense of urgency to do so in order to avoid disruptions during the school year. Meanwhile, the U.S. Elections have provided lures for phishers to attack. Nuspire witnessed Q3 attempts to guide victims to fake voter registration pages to harvest information while spoofing the Election Assistance Commission (EAC). Like these examples, cybercriminals taking advantage of prominent media themes are expected. We anticipate our Q4 2020 Threat Report 4 | Introduction Nuspire Threat Report | Q3 | 2020 to find campaigns leveraging more of the United report each quarter is a great step to gain that States Presidential election as well. -
Diapositiva 1
Feliciano Intini Responsabile dei programmi di Sicurezza e Privacy di Microsoft Italia • NonSoloSecurity Blog: http://blogs.technet.com/feliciano_intini • Twitter: http://twitter.com/felicianointini 1. Introduction - Microsoft Security Intelligence Report (SIR) 2. Today‘s Threats - SIR v.8 New Findings – Italy view 3. Advancements in Software Protection and Development 4. What the Users and Industry Can Do The 8th volume of the Security Intelligence Report contains data and intelligence from the past several years, but focuses on the second half of 2009 (2H09) Full document covers Malicious Software & Potentially Unwanted Software Email, Spam & Phishing Threats Focus sections on: Malware and signed code Threat combinations Malicious Web sites Software Vulnerability Exploits Browser-based exploits Office document exploits Drive-by download attacks Security and privacy breaches Software Vulnerability Disclosures Microsoft Security Bulletins Exploitability Index Usage trends for Windows Update and Microsoft Update Microsoft Malware Protection Center (MMPC) Microsoft Security Response Center (MSRC) Microsoft Security Engineering Center (MSEC) Guidance, advice and strategies Detailed strategies, mitigations and countermeasures Fully revised and updated Guidance on protecting networks, systems and people Microsoft IT ‗real world‘ experience How Microsoft IT secures Microsoft Malware patterns around the world with deep-dive content on 26 countries and regions Data sources Malicious Software and Potentially Unwanted Software MSRT has a user base -
A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics
UNIVERSIDAD POLITECNICA´ DE MADRID ESCUELA TECNICA´ SUPERIOR DE INGENIEROS INFORMATICOS´ A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics PH.D THESIS Platon Pantelis Kotzias Copyright c 2019 by Platon Pantelis Kotzias iv DEPARTAMENTAMENTO DE LENGUAJES Y SISTEMAS INFORMATICOS´ E INGENIERIA DE SOFTWARE ESCUELA TECNICA´ SUPERIOR DE INGENIEROS INFORMATICOS´ A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF: Doctor of Philosophy in Software, Systems and Computing Author: Platon Pantelis Kotzias Advisor: Dr. Juan Caballero April 2019 Chair/Presidente: Marc Dasier, Professor and Department Head, EURECOM, France Secretary/Secretario: Dario Fiore, Assistant Research Professor, IMDEA Software Institute, Spain Member/Vocal: Narseo Vallina-Rodriguez, Assistant Research Professor, IMDEA Networks Institute, Spain Member/Vocal: Juan Tapiador, Associate Professor, Universidad Carlos III, Spain Member/Vocal: Igor Santos, Associate Research Professor, Universidad de Deusto, Spain Abstract of the Dissertation Potentially unwanted programs (PUP) are a category of undesirable software that, while not outright malicious, can pose significant risks to users’ security and privacy. There exist indications that PUP prominence has quickly increased over the last years, but the prevalence of PUP on both consumer and enterprise hosts remains unknown. Moreover, many important aspects of PUP such as distribution vectors, code signing abuse, and economics also remain unknown. In this thesis, we empirically and sys- tematically analyze in both breadth and depth PUP abuse, prevalence, distribution, and economics. We make the following four contributions. First, we perform a systematic study on the abuse of Windows Authenticode code signing by PUP and malware. -
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................................ -
Proposal of N-Gram Based Algorithm for Malware Classification
SECURWARE 2011 : The Fifth International Conference on Emerging Security Information, Systems and Technologies Proposal of n-gram Based Algorithm for Malware Classification Abdurrahman Pektaş Mehmet Eriş Tankut Acarman The Scientific and Technological The Scientific and Technological Computer Engineering Dept. Research Council of Turkey Research Council of Turkey Galatasaray University National Research Institute of National Research Institute of Istanbul, Turkey Electronics and Cryptology Electronics and Cryptology e-mail:[email protected] Gebze, Turkey Gebze, Turkey e-mail:[email protected] e-mail:[email protected] Abstract— Obfuscation techniques degrade the n-gram malware used by the previous work. Similar methodologies features of binary form of the malware. In this study, have been used in source authorship, information retrieval methodology to classify malware instances by using n-gram and natural language processing [5], [6]. features of its disassembled code is presented. The presented The first known use of machine learning in malware statistical method uses the n-gram features of the malware to detection is presented by the work of Tesauro et al. in [7]. classify its instance with respect to their families. n-gram is a fixed size sliding window of byte array, where n is the size of This detection algorithm was successfully implemented in the window. The contribution of the presented method is IBM’s antivirus scanner. They used 3-grams as a feature set capability of using only one vector to represent malware and neural networks as a classification model. When the 3- subfamily which is called subfamily centroid. Using only one grams parameter is selected, the number of all n-gram vector for classification simply reduces the dimension of the n- features becomes 2563, which leads to some spacing gram space. -
Modeling and Evaluating the Resilience of Peer-To-Peer Botnets
P2PWNED: Modeling and Evaluating the Resilience of Peer-to-Peer Botnets Christian Rossow∗‡, Dennis Andriesse‡, Tillmann Werner¶, Brett Stone-Gross†, Daniel Plohmann§, Christian J. Dietrich∗, Herbert Bos‡ ∗ Institute for Internet Security, Gelsenkirchen, Germany {rossow,dietrich}@internet-sicherheit.de ‡ VU University Amsterdam, The Netherlands {d.a.andriesse,h.j.bos}@vu.nl § Fraunhofer FKIE, Bonn, Germany, [email protected] † Dell SecureWorks, [email protected] ¶ CrowdStrike, Inc. Abstract—Centralized botnets are easy targets for takedown disrupted using the traditional approach of attacking critical efforts by computer security researchers and law enforcement. centralized infrastructure. Thus, botnet controllers have sought new ways to harden the Even though active P2P botnets such as the Zeus P2P infrastructures of their botnets. In order to meet this objective, some botnet operators have (re)designed their botnets to use variant, Sality, ZeroAccess and Kelihos have survived in the Peer-to-Peer (P2P) infrastructures. Many P2P botnets are far wild for as long as five years, relatively little is known about more resilient to takedown attempts than centralized botnets, the sizes of these botnets. It is difficult to estimate a P2P because they have no single points of failure. However, P2P botnets are subject to unique classes of attacks, such as node botnet’s size, for a number of reasons. P2P botnets often enumeration and poisoning. In this paper, we introduce a use custom protocols, so that researchers must first reverse formal graph model to capture the intrinsic properties and engineer the protocol and encryption before they can track fundamental vulnerabilities of P2P botnets. We apply our the botnet’s population. -
The Trojan Wars: Building the Big Picture to Combat Efraud
THE TROJAN WARS: BUILDING THE BIG PICTURE TO COMBAT EFRAUD MNEMONIC THREAT INTELLIGENCE UNIT White Paper TABLE OF CONTENTS INTRODUCTION ................................................................................3 THE INITIAL TORPIG CAMPAIGN ......................................................4 • Infection Cycles ..........................................................................................5 • Ice IX – Downloading Torpig and Pushdo ...................................................6 • Torpig Campaign C&C infrastructure ..........................................................9 • Ice IX Takedown Avoidance Technique .......................................................10 THE FOLLOW-ON P2P ZEUS CAMPAIGN ..........................................11 • Infection Cycles ...........................................................................................12 • Neurevt – Downloading P2P Zeus ..............................................................13 THE WAY FORWARD: CONCLUSIONS AND RECOMMENDATIONS ....14 ABOUT MNEMONIC ..........................................................................15 REFERENCES ...................................................................................16 THE TROJAN WARS - BUILDING THE BIG PICTURE TO COMBAT EFRAUD MNEMONIC AS INTRODUCTION Trojans are a very sophisticated type of malware and their use by cybercriminals to perform widespread eFraud is now well established. They are rarely operated in a standalone mode and the infrastructure used to spread and maintain Trojans is -
Download Slides
Scott Wu Point in time cleaning vs. RTP MSRT vs. Microsoft Security Essentials Threat events & impacts More on MSRT / Security Essentials MSRT Microsoft Windows Malicious Software Removal Tool Deployed to Windows Update, etc. monthly since 2005 On-demand scan on prevalent malware Microsoft Security Essentials Full AV RTP Inception in Oct 2009 RTP is the solution One-off cleaner has its role Quiikck response Workaround Baseline ecosystem cleaning Industrypy response & collaboration Threat Events Worms (some are bots) have longer lifespans Rogues move on quicker MarMar 2010 2010 Apr Apr 2010 2010 May May 2010 2010 Jun Jun 2010 2010 Jul Jul 2010 2010 Aug Aug 2010 2010 1,237,15 FrethogFrethog 979,427 979,427 Frethog Frethog 880,246880,246 Frethog Frethog465,351 TaterfTaterf 5 1,237,155Taterf Taterf 797,935797,935 TaterfTaterf 451,561451,561 TaterfTaterf 497,582 497,582 Taterf Taterf 393,729393,729 Taterf Taterf447,849 FrethogFrethog 535,627535,627 AlureonAlureon 493,150 493,150 AlureonAlureon 436,566 436,566 RimecudRimecud 371,646 371,646 Alureon Alureon 308,673308,673 Alureon Alureon 441,722 RimecudRimecud 341,778341,778 FrethogFrethog 473,996473,996 BubnixBubnix 348,120 348,120 HamweqHamweq 289,603 289,603 Rimecud Rimecud289,629 289,629 Rimecud Rimecud318,041 AlureonAlureon 292,810 292,810 BubnixBubnix 471,243 471,243 RimecudRimecud 287,942287,942 ConfickerConficker 286,091286, 091 Hamwe Hamweqq 250,286250, 286 Conficker Conficker220,475220, 475 ConfickerConficker 237237,348, 348 RimecudRimecud 280280,440, 440 VobfusVobfus 251251,335, 335