Citadel Trojan Malware Analysis Jason Milletary Dell Secureworks Counter Threat Unit™ Intelligence Services
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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. -
คู่มือ การป้องกันและกําจัด Spyware ด้วยโปรแกรม Superanti
คูมือ่ การป้องกนและกั าจัดํ Spyware ด้วยโปรแกรม SUPERAntiSpyware Free Edition โดย นายสุชล แกวประทุม้ นักเอกสารสนเทศ ระดับ งานระบบเครือขายคอมพิวเตอร์่ ฝ่ายเทคโนโลยีสารสนเทศห้องสมุด สํานักหอสมุดกลาง มหาวิทยาลัยรามคําแหง มีนาคม สารบัญ หน้า สปายแวร์ (Spyware) คืออะไร .......................................................................................................... 3 สปายแวร์ (Spyware) มาได้อยางไร่ ..................................................................................................... 3 อาการของเครืองคอมพิวเตอร์ทีติดสบายแวร์ (Spyware) ............................................................................ 4 วิธีการป้องกนสบายแวร์ั (Spyware) เบืองต้น ......................................................................................... 4 การป้องกนั และกาจัดสปายแวร์ํ (Spyware) ด้วยโปรแกรม SUPERAntiSpyware ....................................... 5 รู้จักกบโปรแกรมั SUPERAntiSpyware ........................................................................................ 5 คุณสมบัติและความสามารถของโปรแกรม SUPERAntiSpyware ........................................................ 5 ข้อจํากดของโปรแกรมั SUPERAntiSpywaer Free Editon ............................................................. 5 การติดตังโปรแกรมโปรแกรม SUPERAntiSpyware Free Editon ..................................................... 6 การใช้งานโปรแกรม SUPERAntiSpyware Free Editon .............................................................. 10 การปรับปรุง (update) ฐานข้อมูลของโปรแกรม SUPERAntiSpyware .............................................. 13 -
Automated Malware Analysis Report for SUPERANTISPYWARE
ID: 459764 Sample Name: SUPERANTISPYWARE.EXE Cookbook: default.jbs Time: 14:53:19 Date: 05/08/2021 Version: 33.0.0 White Diamond Table of Contents Table of Contents 2 Windows Analysis Report SUPERANTISPYWARE.EXE 4 Overview 4 General Information 4 Detection 4 Signatures 4 Classification 4 Process Tree 4 Malware Configuration 4 Yara Overview 4 Memory Dumps 4 Sigma Overview 5 Jbx Signature Overview 5 Malware Analysis System Evasion: 5 Lowering of HIPS / PFW / Operating System Security Settings: 5 Stealing of Sensitive Information: 5 Remote Access Functionality: 5 Mitre Att&ck Matrix 5 Behavior Graph 6 Screenshots 6 Thumbnails 6 Antivirus, Machine Learning and Genetic Malware Detection 7 Initial Sample 7 Dropped Files 7 Unpacked PE Files 7 Domains 8 URLs 8 Domains and IPs 8 Contacted Domains 8 URLs from Memory and Binaries 8 Contacted IPs 8 Public 8 Private 8 General Information 8 Simulations 9 Behavior and APIs 9 Joe Sandbox View / Context 9 IPs 9 Domains 10 ASN 10 JA3 Fingerprints 11 Dropped Files 11 Created / dropped Files 11 Static File Info 27 General 28 File Icon 28 Static PE Info 28 General 28 Authenticode Signature 28 Entrypoint Preview 29 Rich Headers 29 Data Directories 29 Sections 29 Resources 29 Imports 29 Version Infos 29 Possible Origin 29 Network Behavior 29 Code Manipulations 29 Statistics 29 Behavior 29 System Behavior 29 Analysis Process: SUPERANTISPYWARE.EXE PID: 5720 Parent PID: 5776 29 General 29 File Activities 30 File Created 30 File Deleted 30 File Written 30 File Read 30 Registry Activities 30 Key Created 30 Key Value -
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 -
The Customer As a Target Risks of Phishing and Trojans
The Customer as a Target Risks of Phishing and Trojans Gijs Hollestelle | Deloitte Netherlands January 31, 2012 © 2012 Deloitte Touche Tohmatsu History of Computer Crime (1/2) •1980‟s • First worm: Morris Worm • Phone Phreaking • BBS Hacking boards • Movie: Wargames • Computer hacking was primarily done by people in universities to find out how things worked •1990‟s: • Real start of computer crime, targeting financial institutions • Succesful hacks of various banks, phone companies, etc • Kevin Mitnick convicted • 2000‟s / Today • Early 2000‟s examples of „Hobby‟ projects, everyone can be a hacker. I love You/Kournikova Virus • Late 2000‟s Professionalization of computer crime • Internet banking and online shopping become popular, leading to increased incentive to use computer crime for financial gain • Avanced trojans • Shift of hacking companies to hacking consumers • Sophisticated trojans/virusses such as Zeus and Stuxnet 2 © 2012 Deloitte Touche Tohmatsu History of Computer Crime (2/2) 3 © 2012 Deloitte Touche Tohmatsu The Underground Economy (1/2) Some recent figures • Dutch Association of Banks (NVB) released information that in 2012 Internet banking fraud was 9.8 mln euro. • In first half of 2011 alone, this has increased to 11.2 mln euro. • In Germany Internet banking fraud is estimated at 17mln euro in 2012 • In the UK 60mln pounds in Internet Crime in 2009 4 © 2012 Deloitte Touche Tohmatsu The Underground Economy (2/2) Where are these identities sold? Source: krebsonsecurity.com 5 © 2012 Deloitte Touche Tohmatsu The Logic of the Cyber Criminal • Stricter regulations such as PCI have forced companies have forced companies to further increase their security measures. -
Understanding and Analyzing Malicious Domain Take-Downs
Cracking the Wall of Confinement: Understanding and Analyzing Malicious Domain Take-downs Eihal Alowaisheq1,2, Peng Wang1, Sumayah Alrwais2, Xiaojing Liao1, XiaoFeng Wang1, Tasneem Alowaisheq1,2, Xianghang Mi1, Siyuan Tang1, and Baojun Liu3 1Indiana University, Bloomington. fealowais, pw7, xliao, xw7, talowais, xm, [email protected] 2King Saud University, Riyadh, Saudi Arabia. [email protected] 3Tsinghua University, [email protected] Abstract—Take-down operations aim to disrupt cybercrime “clean”, i.e., no longer involved in any malicious activities. involving malicious domains. In the past decade, many successful Challenges in understanding domain take-downs. Although take-down operations have been reported, including those against the Conficker worm, and most recently, against VPNFilter. domain seizures are addressed in ICANN guidelines [55] Although it plays an important role in fighting cybercrime, the and in other public articles [14, 31, 38], there is a lack of domain take-down procedure is still surprisingly opaque. There prominent and comprehensive understanding of the process. seems to be no in-depth understanding about how the take-down In-depth exploration is of critical importance for combating operation works and whether there is due diligence to ensure its cybercrime but is by no means trivial. The domain take-down security and reliability. process is rather opaque and quite complicated. In particular, In this paper, we report the first systematic study on domain it involves several steps (complaint submission, take-down takedown. Our study was made possible via a large collection execution, and release, see SectionII). It also involves multiple of data, including various sinkhole feeds and blacklists, passive parties (authorities, registries, and registrars), and multiple DNS data spanning six years, and historical WHOIS informa- domain management elements (DNS, WHOIS, and registry tion. -
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. -
An Adaptive Multi-Layer Botnet Detection Technique Using Machine Learning Classifiers
applied sciences Article An Adaptive Multi-Layer Botnet Detection Technique Using Machine Learning Classifiers Riaz Ullah Khan 1,* , Xiaosong Zhang 1, Rajesh Kumar 1 , Abubakar Sharif 1, Noorbakhsh Amiri Golilarz 1 and Mamoun Alazab 2 1 Center of Cyber Security, School of Computer Science & Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; [email protected] (X.Z.); [email protected] (R.K.); [email protected] (A.S.); [email protected] (N.A.G.) 2 College of Engineering, IT and Environment, Charles Darwin University, Casuarina 0810, Australia; [email protected] * Correspondence: [email protected]; Tel.: +86-155-2076-3595 Received: 19 March 2019; Accepted: 24 April 2019; Published: 11 June 2019 Abstract: In recent years, the botnets have been the most common threats to network security since it exploits multiple malicious codes like a worm, Trojans, Rootkit, etc. The botnets have been used to carry phishing links, to perform attacks and provide malicious services on the internet. It is challenging to identify Peer-to-peer (P2P) botnets as compared to Internet Relay Chat (IRC), Hypertext Transfer Protocol (HTTP) and other types of botnets because P2P traffic has typical features of the centralization and distribution. To resolve the issues of P2P botnet identification, we propose an effective multi-layer traffic classification method by applying machine learning classifiers on features of network traffic. Our work presents a framework based on decision trees which effectively detects P2P botnets. A decision tree algorithm is applied for feature selection to extract the most relevant features and ignore the irrelevant features. -
Monthly Report on Online Threats in The
MONTHLY REPORT ON ONLINE THREATS REPORTING PERIOD: IN THE BANKING SECTOR 19.04–19.05.2014 One of the main events during the reporting period was the leakage of payment credentials belonging to eBay users. Details of the incident and other detected threats can be found in the section ‘Key events in the online banking sphere’ below. Overall statistics During the reporting period, Kaspersky Lab solutions blocked 341,216 attempts on user computers to launch malware capable of stealing money from online banking accounts. This figure represents a 36.6% increase compared to the previous reporting period (249,812). This increase in banking malware activity is most likely related to the onset of the vacation season, when customers actively use their payment data to make all types of purchases online. 24 001 - 78 000 16 001 - 24 000 7101 - 16 000 2101 - 7100 1 - 2100 Number of users targeted by banking malware The number of users attacked using these types of programs during the reporting period is shown in the diagram below (Top 10 rating based on the number of users attacked, in descending order): 77,412 27,071 21,801 22,115 13,876 15,651 17,333 5417 6883 7347 France Vietnam Austria India Germany United USA Russian Italy Brazil Kingdom Federation © 1997-2014 Kaspersky Lab ZAO. All Rights Reserved. The table below shows the programs most commonly used to attack online banking users, based on the number of infection attempts: Total notifications of Verdict* Number of users Number of notifications attempted infections by Trojan-Spy.Win32.Zbot 198 -
Financial Malware Analysis-Secrets of Zeus
IJSART - volume 1 Issue 2–FEBRUARY 2015 ISSN [ONLINE]: 2395-1052 Financial Malware Analysis- Secrets of ZeuS 1 2 Rushita Dave ,Anisetti Anjaneyulu 1 Forensics Analyst eSF Labs Ltd. Abstract- Malware becomes one of the internet’s major security DumpIt threats these days. Malware is the most widespread threat towards Virtual Machine Files (vmem): IT now. Because of the huge quantity of new malware samples, researchers rely on dynamic malware analysis. Malware analysis Virtual machines provide a useful environment for dynamic is an important part of understanding the objectives of the analysis of malware. Acquire RAM from guest machines by just malware and how to defend against this threat. To be able to defend against the threat imposed by malware we need to suspending or pausing the VM, and guest’s RAM will be written understand both how and why the malware exists. to a file on the host’s disk. Then grab the ".vmem" file for analysis. The default location of the vmem file for VMware is I. INTRODUCTION %My Documents%\My Virtual Machines\<VM Name>\*.vmem Malware is a general term for a piece of software inserted into B. Tool to analyze the memory an information system to cause harm to the system. Malware can gain remote access to system, record and send data to a third party Volatility without the user's permission or knowledge. Malware are The Volatility Framework is an open collection of tools for the commonly described as viruses, worms, trojan horses, backdoors, extraction of digital artifacts from volatile memory samples. keystroke loggers, rootkits or spyware. -
Zeus Spyeye Banking Trojan Analysis
SOFTWARE ASSURANCE Technical White Paper Reversal and Analysis of Zeus and SpyEye Banking Trojans IOActive, Inc. 701 5th Avenue, Suite 6850 Seattle, WA 98104 Toll free: (866) 760-0222 Office: (206) 784-4313 Fax: (206) 784-4367 Copyright ©2012 by IOActive, Incorporated All Rights Reserved. Contents Introduction ................................................................................................................................................... 1 SpyEye Malware Analysis ............................................................................................................................. 1 Initialization ............................................................................................................................................ 1 API Calls ................................................................................................................................................ 4 API Hooking ........................................................................................................................................... 4 Process Injection .................................................................................................................................... 5 Keystroke Logging ................................................................................................................................. 6 Form Grabbing ....................................................................................................................................... 6 Credentials Theft ................................................................................................................................... -
Cisco Identity Services Engine Release 1.2 Supported Windows
Cisco Identity Services Engine Supported Windows AV/AS Products Compliance Module Version 3.5.6317.2 This document provides Windows 8/7/Vista/XP AV/AS support information on the Cisco NAC Agent version 4.9.0.x and later. For other support information and complete release updates, refer to the Release Notes for Cisco Identity Services Engine corresponding to your Cisco Identity Services Engine release version. Supported Windows AV/AS Product Summary Added New AV Definition Support: COMODO Antivirus 5.x COMODO Internet Security 3.5.x COMODO Internet Security 3.x COMODO Internet Security 4.x Kingsoft Internet Security 2013.x Added New AV Products Support: V3 Click 1.x avast! Internet Security 8.x avast! Premier 8.x avast! Pro Antivirus 8.x Gen-X Total Security 1.x K7UltimateSecurity 13.x Kaspersky Endpoint Security 10.x Kaspersky PURE 13.x Norman Security Suite 10.x Supported Windows AntiVirus Products Product Name Product Version Installation Virus Definition Live Update 360Safe.com 360 Antivirus 1.x 4.9.0.28 / 3.4.21.1 4.9.0.28 / 3.4.21.1 yes 360 Antivirus 3.x 4.9.0.29 / 3.5.5767.2 4.9.0.29 / 3.5.5767.2 - 360杀毒 1.x 4.9.0.28 / 3.4.21.1 4.9.0.28 / 3.4.21.1 - 360杀毒 2.x 4.9.0.29 / 3.4.25.1 4.9.0.29 / 3.4.25.1 - 360杀毒 3.x 4.9.0.29 / 3.5.2101.2 - Other 360Safe.com Antivirus x 4.9.0.29 / 3.5.2101.2 - AEC, spol.