Mcafee Threats Report: Second Quarter 2009 by Mcafee® Avert® Labs Report Mcafee Threats Report: Second Quarter 2009
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Botection: Bot Detection by Building Markov Chain Models of Bots Network Behavior Bushra A
BOTection: Bot Detection by Building Markov Chain Models of Bots Network Behavior Bushra A. Alahmadi Enrico Mariconti Riccardo Spolaor University of Oxford, UK University College London, UK University of Oxford, UK [email protected] [email protected] [email protected] Gianluca Stringhini Ivan Martinovic Boston University, USA University of Oxford, UK [email protected] [email protected] ABSTRACT through DDoS (e.g. DDoS on Estonia [22]), email spam (e.g. Geodo), Botnets continue to be a threat to organizations, thus various ma- ClickFraud (e.g. ClickBot), and spreading malware (e.g. Zeus). 10,263 chine learning-based botnet detectors have been proposed. How- malware botnet controllers (C&C) were blocked by Spamhaus Mal- ever, the capability of such systems in detecting new or unseen ware Labs in 2018 alone, an 8% increase from the number of botnet 1 botnets is crucial to ensure its robustness against the rapid evo- C&Cs seen in 2017. Cybercriminals are actively monetizing bot- lution of botnets. Moreover, it prolongs the effectiveness of the nets to launch attacks, which are evolving significantly and require system in detecting bots, avoiding frequent and time-consuming more effective detection mechanisms capable of detecting those classifier re-training. We present BOTection, a privacy-preserving which are new or unseen. bot detection system that models the bot network flow behavior Botnets rely heavily on network communications to infect new as a Markov Chain. The Markov Chains state transitions capture victims (propagation), to communicate with the C&C server, or the bots’ network behavior using high-level flow features as states, to perform their operational task (e.g. -
Fortinet's March Threatscape Report Shows Domination of Ransomware and Troublesome Zero-Day
Fortinet's March Threatscape Report Shows Domination of Ransomware and Troublesome Zero-Day Rise of Ransomware Is Primarily Driven by Bredolab and Pushdo Botnets SUNNYVALE, CA, Apr 01, 2010 (MARKETWIRE via COMTEX News Network) -- Fortinet(R) (NASDAQ: FTNT) -- a leading network security provider and worldwide leader of unified threat management (UTM) solutions -- today announced its March 2010 Threatscape report showed domination of ransomware threats with nine of the detections in the malware top ten list resulting in either scareware or ransomware infesting the victim's PC. Fortinet observed the primary drivers behind these threats to be two of the most notorious botnet "loaders" -- Bredolab and Pushdo. Another important finding is the aggressive entrance of a new zero-day threat in FortiGuard's top ten attack list, MS.IE.Userdata.Behavior.Code.Execution, which accounted for 25 percent of the detected activity last month. Key threat activities for the month of March include: -- SMS-based Ransomware High Activity: A new ransomware threat -- W32/DigiPog.EP -- appeared in Fortinet's top ten malware list. DigiPog is an SMS blocker using Russian language, locking out a system and aggressively killing off popular applications like Internet Explorer and Firefox until an appropriate code is entered into a field provided to the user. To obtain the code, a user must send an SMS message to the provided number, receiving a code in return. Upon execution, DigiPog registers the user's MAC address with its server. It is the first time that SMS-based ransomware enters Fortinet's top ten list, showing that the rise of ransomware is well on its way. -
Internet Security Threat Report Volume 24 | February 2019
ISTRInternet Security Threat Report Volume 24 | February 2019 THE DOCUMENT IS PROVIDED “AS IS” AND ALL EXPRESS OR IMPLIED CONDITIONS, REPRESENTATIONS AND WARRANTIES, INCLUDING ANY IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR NON-INFRINGEMENT, ARE DISCLAIMED, EXCEPT TO THE EXTENT THAT SUCH DISCLAIMERS ARE HELD TO BE LEGALLY INVALID. SYMANTEC CORPORATION SHALL NOT BE LIABLE FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES IN CONNECTION WITH THE FURNISHING, PERFORMANCE, OR USE OF THIS DOCUMENT. THE INFORMATION CONTAINED IN THIS DOCUMENT IS SUBJECT TO CHANGE WITHOUT NOTICE. INFORMATION OBTAINED FROM THIRD PARTY SOURCES IS BELIEVED TO BE RELIABLE, BUT IS IN NO WAY GUARANTEED. SECURITY PRODUCTS, TECHNICAL SERVICES, AND ANY OTHER TECHNICAL DATA REFERENCED IN THIS DOCUMENT (“CONTROLLED ITEMS”) ARE SUBJECT TO U.S. EXPORT CONTROL AND SANCTIONS LAWS, REGULATIONS AND REQUIREMENTS, AND MAY BE SUBJECT TO EXPORT OR IMPORT REGULATIONS IN OTHER COUNTRIES. YOU AGREE TO COMPLY STRICTLY WITH THESE LAWS, REGULATIONS AND REQUIREMENTS, AND ACKNOWLEDGE THAT YOU HAVE THE RESPONSIBILITY TO OBTAIN ANY LICENSES, PERMITS OR OTHER APPROVALS THAT MAY BE REQUIRED IN ORDER FOR YOU TO EXPORT, RE-EXPORT, TRANSFER IN COUNTRY OR IMPORT SUCH CONTROLLED ITEMS. TABLE OF CONTENTS 1 2 3 BIG NUMBERS YEAR-IN-REVIEW FACTS AND FIGURES METHODOLOGY Formjacking Messaging Cryptojacking Malware Ransomware Mobile Living off the land Web attacks and supply chain attacks Targeted attacks Targeted attacks IoT Cloud Underground economy IoT Election interference MALICIOUS -
2015 Threat Report Provides a Comprehensive Overview of the Cyber Threat Landscape Facing Both Companies and Individuals
THREAT REPORT 2015 AT A GLANCE 2015 HIGHLIGHTS A few of the major events in 2015 concerning security issues. 08 07/15: Hacking Team 07/15: Bugs prompt 02/15: Europol joint breached, data Ford, Range Rover, 08/15: Google patches op takes down Ramnit released online Prius, Chrysler recalls Android Stagefright botnet flaw 09/15: XcodeGhost 07/15: Android 07/15: FBI Darkode tainted apps prompts Stagefright flaw 08/15: Amazon, ENFORCEMENT bazaar shutdown ATTACKS AppStore cleanup VULNERABILITY reported SECURITYPRODUCT Chrome drop Flash ads TOP MALWARE BREACHING THE MEET THE DUKES FAMILIES WALLED GARDEN The Dukes are a well- 12 18 resourced, highly 20 Njw0rm was the most In late 2015, the Apple App prominent new malware family in 2015. Store saw a string of incidents where dedicated and organized developers had used compromised tools cyberespionage group believed to be to unwittingly create apps with malicious working for the Russian Federation since behavior. The apps were able to bypass at least 2008 to collect intelligence in Njw0rm Apple’s review procedures to gain entry support of foreign and security policy decision-making. Angler into the store, and from there into an ordinary user’s iOS device. Gamarue THE CHAIN OF THE CHAIN OF Dorkbot COMPROMISE COMPROMISE: 23 The Stages 28 The Chain of Compromise Nuclear is a user-centric model that illustrates Kilim how cyber attacks combine different Ippedo techniques and resources to compromise Dridex devices and networks. It is defined by 4 main phases: Inception, Intrusion, WormLink Infection, and Invasion. INCEPTION Redirectors wreak havoc on US, Europe (p.28) INTRUSION AnglerEK dominates Flash (p.29) INFECTION The rise of rypto-ransomware (p.31) THREATS BY REGION Europe was particularly affected by the Angler exploit kit. -
Power-Law Properties in Indonesia Internet Traffic. Why Do We Care About It
by Bisyron Wahyudi Muhammad Salahuddien Amount of malicious traffic circulating on the Internet is increasing significantly. Increasing complexity and rapid change in hosts and networks technology suggests that there will be new vulnerabilities. Attackers have interest in identifying networks and hosts to expose vulnerabilities : . Network scans . Worms . Trojans . Botnet Complicated methods of attacks make difficult to identify the real attacks : It is not simple as filtering out the traffic from some sources Security is implemented like an “add on” module for the Internet. Understanding nature behavior of malicious sources and targeted ports is important to minimize the damage by build strong specific security rules and counter measures Help the cyber security policy-making process, and to raise public awareness Questions : . Do malicious sources generate the attacks uniformly ? . Is there any pattern specific i.e. recurrence event ? . Is there any correlation between the number of some attacks over specific time ? Many systems and phenomena (events) are distributed according to a “power law” When one quantity (say y) depends on another (say x) raised to some power, we say that y is described by a power law A power law applies to a system when: . large is rare and . small is common Collection of System logs from Networked Intrusion Detection System (IDS) The NIDS contains 11 sensors installed in different core networks in Indonesian ISP (NAP) Period : January, 2012 - September, 2012 . Available fields : ▪ Event Message, Timestamp, Dest. IP, Source IP, Attacks Classification, Priority, Protocol, Dest. Port/ICMP code, Source Port/ICMP type, Sensors ID Two quantities x and y are related by a power law if y is proportional to x(-c) for a constant c y = .x(-c) If x and y are related by a power law, then the graph of log(y) versus log(x) is a straight line log(y) = -c.log(x) + log() The slope of the log-log plot is the power exponent c Destination Port Distribution . -
PC Anti-Virus Protection 2011
PC Anti-Virus Protection 2011 12 POPULAR ANTI-VIRUS PROGRAMS COMPARED FOR EFFECTIVENESS Dennis Technology Labs, 03/08/2010 www.DennisTechnologyLabs.com This test aims to compare the effectiveness of the most recent releases of popular anti-virus software1. The products include those from Kaspersky, McAfee, Microsoft, Norton (Symantec) and Trend Micro, as well as free versions from Avast, AVG and Avira. Other products include those from BitDefender, ESET, G-Data and K7. The tests were conducted between 07/07/2010 and 22/07/2010 using the most up to date versions of the software available. A total of 12 products were exposed to genuine internet threats that real customers could have encountered during the test period. Crucially, this exposure was carried out in a realistic way, reflecting a customer’s experience as closely as possible. For example, each test system visited real, infected websites that significant numbers of internet users were encountering at the time of the test. These results reflect what would have happened if those users were using one of the seven products tested. EXECUTIVE SUMMARY Q Products that block attacks early tended to protect the system more fully The nature of web-based attacks means that the longer malware has access to a system, the more chances it has of downloading and installing further threats. Products that blocked the malicious and infected websites from the start reduced the risk of compromise by secondary and further downloads. Q 100 per cent protection is rare This test recorded an average protection rate of 87.5 per cent. New threats appear online frequently and it is inevitable that there will be times when specific security products are unable to protect from some of these threats. -
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. -
Iptrust Botnet / Malware Dictionary This List Shows the Most Common Botnet and Malware Variants Tracked by Iptrust
ipTrust Botnet / Malware Dictionary This list shows the most common botnet and malware variants tracked by ipTrust. This is not intended to be an exhaustive list, since new threat intelligence is always being added into our global Reputation Engine. NAME DESCRIPTION Conficker A/B Conficker A/B is a downloader worm that is used to propagate additional malware. The original malware it was after was rogue AV - but the army's current focus is undefined. At this point it has no other purpose but to spread. Propagation methods include a Microsoft server service vulnerability (MS08-067) - weakly protected network shares - and removable devices like USB keys. Once on a machine, it will attach itself to current processes such as explorer.exe and search for other vulnerable machines across the network. Using a list of passwords and actively searching for legitimate usernames - the ... Mariposa Mariposa was first observed in May 2009 as an emerging botnet. Since then it has infected an ever- growing number of systems; currently, in the millions. Mariposa works by installing itself in a hidden location on the compromised system and injecting code into the critical process ͞ĞdžƉůŽƌĞƌ͘ĞdžĞ͘͟/ƚŝƐknown to affect all modern Windows versions, editing the registry to allow it to automatically start upon login. Additionally, there is a guard that prevents deletion while running, and it automatically restarts upon crash/restart of explorer.exe. In essence, Mariposa opens a backdoor on the compromised computer, which grants full shell access to ... Unknown A botnet is designated 'unknown' when it is first being tracked, or before it is given a publicly- known common name. -
Transition Analysis of Cyber Attacks Based on Long-Term Observation—
2-3 nicterReport —TransitionAnalysisofCyberAttacksBasedon Long-termObservation— NAKAZATO Junji and OHTAKA Kazuhiro In this report, we provide a statistical data concerning cyber attacks and malwares based on a long-term network monitoring on the nicter. Especially, we show a continuous observation report of Conficker, which is a pandemic malware since November 2008. In addition, we report a transition analysis of the scale of botnet activities. Keywords Incident analysis, Darknet, Network monitoring, Malware analysis 1 Introduction leverages the traffic as detected by the four black hole sensors placed on different network We have been monitoring the IP address environments as shown by Fig. 1. space that is reachable and unused on the ● Sensor I : Structure where live nets and Internet (i.e. darknets) on a large-scale to darknets coexist in a class B understand the overall impact inflicted by network infectious activities including malware. This ● Sensor II : Structure where only darknets report analyzes the darknet traffic that has exist in a class B network been monitored and accumulated over six ● Sensor III : Structure where a /24 subnet years by an incident analysis center named in a class B network is a dark- *1 the nicter[1][2] to provide changing trends of net cyber attacks and fluctuation of attacker host ● Sensor IV : Structure where live nets and activities as obtained by long-term monitor- darknets coexist in a class B ing. In particular, we focus on Conficker, a network worm that has triggered large-scale infections The traffic obtained by these four sensors since November 2008, and report its impact on is analyzed by different analysis engines[3][4] the Internet and its current activities. -
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. -
Contents in This Issue
FEBRUARY 2014 Covering the global threat landscape CONTENTS IN THIS ISSUE 2 COMMENT A LIFE OF GRIME It is time for defenders to go on the offence Cross-platform execution is one of the promises of Java – but cross-platform infection is probably 3 NEWS not what the designers had in mind. Nevertheless, that was clearly in the mind of the author of Law minister is former spammer W32/Java.Grimy, a virus for the Windows platform, Cash for hacks which infects Java class fi les. Peter Ferrie has the details. MALWARE ANALYSES page 4 4 Getting one’s hands dirty LAME DUCK 6 Salted algorithm – part 2 Sometimes what looks like a genuine MP3 encoder 11 Inside W32.Xpaj.B’s infection – part 2 library, and even works as a functional encoder, actually hides malicious code deep amongst a 19 FEATURE pile of clean code. Gabor Szappanos reveals the Needle in a haystack lengths to which one piece of malware goes to hide its tracks. page 19 27 BOOK REVIEW Don’t forget to write READING CORNER Industry veteran, prolifi c writer and educator David 30 SPOTLIGHT Harley reviews two recently published eBooks that aim to provide security guidance for consumers: Greetz from academe: Full frontal ‘Improve Your Security’ by Sorin Mustaca, and ‘One Parent to Another’ by Tony Anscombe. 31 END NOTES & NEWS page 27 ISSN 1749-7027 COMMENT ‘Challenge for example, an IPS or anti-virus product will still do some level of good if you do no more than install it on [defenders] to your network and make sure it gets updated occasionally, take a penetration a SIEM will not do anything except generate a (huge) bill. -
Autocoding Methods for Networked Embedded Systems
University of Warwick institutional repository: http://go.warwick.ac.uk/wrap A Thesis Submitted for the Degree of PhD at the University of Warwick http://go.warwick.ac.uk/wrap/36892 This thesis is made available online and is protected by original copyright. Please scroll down to view the document itself. Please refer to the repository record for this item for information to help you to cite it. Our policy information is available from the repository home page. Innovation Report AUTOCODING METHODS FOR NETWORKED EMBEDDED SYSTEMS Submitted in partial fulfilment of the Engineering Doctorate By James Finney, 0117868 November 2009 Academic Supervisors: Dr. Peter Jones, Ross McMurran Industrial Supervisor: Dr. Paul Faithfull Declaration I have read and understood the rules on cheating, plagiarism and appropriate referencing as outlined in my handbook and I declare that the work contained in this submission is my own, unless otherwise acknowledged. Signed: …………………………………………………………………….James Finney ii Acknowledgements I would like to thank Rapicore Ltd and the EPSRC for funding this project. I would also like to offer special thanks to my supervisors: Dr. R.P. Jones, Dr. P. Faithfull, and R. McMurran, for their time, support, and guidance throughout this project. iii Table of Contents Declaration ....................................................................................................................... ii Acknowledgements ......................................................................................................... iii Figures