Understanding How Spammers Steal Your E-Mail Address: an Analysis of the First Six Months of Data from Project Honey Pot
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Prospects, Leads, and Subscribers
PAGE 2 YOU SHOULD READ THIS eBOOK IF: You are looking for ideas on finding leads. Spider Trainers can help You are looking for ideas on converting leads to Marketing automation has been shown to increase subscribers. qualified leads for businesses by as much as 451%. As You want to improve your deliverability. experts in drip and nurture marketing, Spider Trainers You want to better maintain your lists. is chosen by companies to amplify lead and demand generation while setting standards for design, You want to minimize your list attrition. development, and deployment. Our publications are designed to help you get started, and while we may be guilty of giving too much information, we know that the empowered and informed client is the successful client. We hope this white paper does that for you. We look forward to learning more about your needs. Please contact us at 651 702 3793 or [email protected] . ©2013 SPIDER TRAINERS PAGE 3 TAble Of cOnTenTS HOW TO cAPTure SubScriberS ...............................2 HOW TO uSe PAiD PrOGrAMS TO GAin Tipping point ..................................................................2 SubScriberS ...........................................................29 create e mail lists ...........................................................3 buy lists .........................................................................29 Pop-up forms .........................................................4 rent lists ........................................................................31 negative consent -
Address Munging: the Practice of Disguising, Or Munging, an E-Mail Address to Prevent It Being Automatically Collected and Used
Address Munging: the practice of disguising, or munging, an e-mail address to prevent it being automatically collected and used as a target for people and organizations that send unsolicited bulk e-mail address. Adware: or advertising-supported software is any software package which automatically plays, displays, or downloads advertising material to a computer after the software is installed on it or while the application is being used. Some types of adware are also spyware and can be classified as privacy-invasive software. Adware is software designed to force pre-chosen ads to display on your system. Some adware is designed to be malicious and will pop up ads with such speed and frequency that they seem to be taking over everything, slowing down your system and tying up all of your system resources. When adware is coupled with spyware, it can be a frustrating ride, to say the least. Backdoor: in a computer system (or cryptosystem or algorithm) is a method of bypassing normal authentication, securing remote access to a computer, obtaining access to plaintext, and so on, while attempting to remain undetected. The backdoor may take the form of an installed program (e.g., Back Orifice), or could be a modification to an existing program or hardware device. A back door is a point of entry that circumvents normal security and can be used by a cracker to access a network or computer system. Usually back doors are created by system developers as shortcuts to speed access through security during the development stage and then are overlooked and never properly removed during final implementation. -
Technical and Legal Approaches to Unsolicited Electronic Mail†
35 U.S.F. L. REV. 325 (2001) Technical and Legal Approaches to Unsolicited Electronic Mail† By DAVID E. SORKIN* “Spamming” is truly the scourge of the Information Age. This problem has become so widespread that it has begun to burden our information infrastructure. Entire new networks have had to be constructed to deal with it, when resources would be far better spent on educational or commercial needs. United States Senator Conrad Burns (R-MT)1 UNSOLICITED ELECTRONIC MAIL, also called “spam,”2 causes or contributes to a wide variety of problems for network administrators, † Copyright © 2000 David E. Sorkin. * Assistant Professor of Law, Center for Information Technology and Privacy Law, The John Marshall Law School; Visiting Scholar (1999–2000), Center for Education and Research in Information Assurance and Security (CERIAS), Purdue University. The author is grateful for research support furnished by The John Marshall Law School and by sponsors of the Center for Education and Research in Information Assurance and Security. Paul Hoffman, Director of the Internet Mail Consortium, provided helpful comments on technical matters based upon an early draft of this Article. Additional information related to the subject of this Article is available at the author’s web site Spam Laws, at http://www.spamlaws.com/. 1. Spamming: Hearing Before the Subcomm. on Communications of the Senate Comm. on Commerce, Sci. & Transp., 105th Cong. 2 (1998) (prepared statement of Sen. Burns), available at 1998 WL 12761267 [hereinafter 1998 Senate Hearing]. 2. The term “spam” reportedly came to be used in connection with online activities following a mid-1980s episode in which a participant in a MUSH created and used a macro that repeatedly typed the word “SPAM,” interfering with others’ ability to participate. -
Presentations Made by Senders
SES ���� ��� � �� � � � � � � � ������������� DomainKeys ��������� SPF ��������������������� ���������� ����������������� ������������������������������������������������ Contents Introduction 3 Deployment: For Email Receivers 6 Audience 3 Two Sides of the Coin 6 How to Read this White Paper 3 Recording Trusted Senders Who Passed Authentication 6 A Vision for Spam-Free Email 4 Whitelisting Incoming Forwarders 6 The Problem of Abuse 4 What To Do About Forgeries 6 The Underlying Concept 4 Deployment: For ISPs and Enterprises 7 Drivers; or, Who’s Buying It 4 Complementary considerations for ISPs 7 Vision Walkthrough 5 Deployment: For MTA vendors 8 About Sender Authentication 8 Which specification? 8 An Example 8 Conformance testing 8 History 8 Perform SRS and prepend headers when forwarding 8 How IP-based Authentication Works 9 Add ESMTP support for Submitter 8 The SPF record 9 Record authentication and policy results in the headers 8 How SPF Classic Works 9 Join the developers mailing list 8 How Sender ID works 9 Deployment: For MUA vendors 9 How Cryptographic Techniques Work 0 Displaying Authentication-Results 9 Using Multiple Approaches Automatic switching to port 587 9 Reputation Systems Deployment: For ESPs 20 Deployment: For Email Senders 2 Don’t look like a phisher! 20 First, prepare. 2 Delegation 20 Audit Your Outbound Mailstreams 2 Publish Appropriately 20 Construct the record 2 Deployment: For Spammers 2 Think briefly about PRA and Mail-From contexts. 3 Two Types of Spammers 2 Test the record, part 3 Publish SPF and sign with DomainKeys. 2 Put the record in DNS 3 Stop forging random domains. 2 Test the record, part 2 4 Buy your own domains. 2 Keep Track of Violations 4 Reuse an expired domain. -
Asian Anti-Spam Guide 1
Asian Anti-Spam Guide 1 © MediaBUZZ Pte Ltd January 2009 Asian Anti-SpamHighlights Guide 2 • Combating the latest inbound threat: Spam and dark traffic, Pg. 13 • Secure Email Policy Best Practices, Pg. 17 • The Continuous Hurdle of Spam, Pg. 29 • Asian Anti Spam Acts, Pg. 42 Contents: • Email Spam: A Rising Tide 4 • What everyone should know about spam and privacy 7 • Scary Email Issues of 2008 12 • Combating the latest inbound threat: Spam and dark 13 • Proofpoint survey viewed spam as an increasing threat 16 • Secure Email Policy Best Practices 17 • Filtering Out Spam and Scams 24 • The Resurgence of Spam 26 • 2008 Q1 Security Threat landscape 27 • The Continuous Hurdle of Spam 29 • Spam Filters are Adaptive 30 • Liberating the inbox: How to make email safe and pro- 31 ductive again • Guarantee a clear opportunity to opt out 33 • The Great Balancing Act: Juggling Collaboration and 34 Authentication in Government IT Networks • The Not So Secret Cost of Spam 35 • How to Avoid Spam 36 • How to ensure your e-mails are not classified as spam 37 • Blue Coat’s Top Security Trends for 2008 38 • The Underground Economy 40 • Losing Email is No Longer Inevitable 42 • Localized malware gains ground 44 • Cyber-crime shows no signs of abating 45 MEDIABUZZ PTE LTD • Asian Anti-Spam Acts 47 ASIAN ANTI-SPAM GUIDE © MediaBUZZ Pte Ltd January 2009 Asian Anti-SpamHighlights Guide 3 • Frost & Sullivan: Do not underestimate spam, Pg. 65 • Unifying email security is key, Pg. 71 • The many threats of network security, Pg. 76 • The UTM story, Pg. -
Taxonomy of Email Reputation Systems (Invited Paper)
Taxonomy of Email Reputation Systems (Invited Paper) Dmitri Alperovitch, Paul Judge, and Sven Krasser Secure Computing Corporation 4800 North Point Pkwy Suite 400 Alpharetta, GA 30022 678-969-9399 {dalperovitch, pjudge, skrasser}@securecomputing.com Abstract strong incentive for people to act maliciously without paying reputational consequences [1]. While this Today a common goal in the area of email security problem can be solved by disallowing anonymity on is to provide protection from a wide variety of threats the Internet, email reputation systems are able to by being more predictive instead of reactive and to address this problem in a much more practical fashion. identify legitimate messages in addition to illegitimate By assigning a reputation to every email entity, messages. There has been previous work in the area of reputation systems can influence agents to operate email reputation systems that can accomplish these responsibly for fear of getting a bad reputation and broader goals by collecting, analyzing, and being unable to correspond with others [2]. distributing email entities' past behavior The goal of an email reputation system is to monitor characteristics. In this paper, we provide taxonomy activity and assign a reputation to an entity based on its that examines the required properties of email past behavior. The reputation value should be able to reputation systems, identifies the range of approaches, denote different levels of trustworthiness on the and surveys previous work. spectrum from good to bad. In 2000, Resnick et al. described Internet reputation system as having three 1. Introduction required properties [3]: • Entities are long lived, As spam volumes have continued to increase with • feedback about current interactions is high rates, comprising 90% of all email by the end of captured and distributed, and 2006 as determined by Secure Computing Research, • past feedback guides buyer decisions. -
Factors Involved in Estimating Cost of Email Spam
Factors involved in estimating cost of Email spam Farida Ridzuan, Vidyasagar Potdar, Alex Talevski Anti Spam Research Lab, Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology. [email protected], {v.potdar, a.talevski}@curtin.edu.au Abstract. This paper analyses existing research work to identify all possible factors involved in estimating cost of spam. Main motivation of this paper is to provide unbiased spam costs estimation. For that, we first study the email spam lifecycle and identify all possible stakeholders. We then categorise cost and study the impact on each stakeholder. This initial study will form the backbone of the real time spam cost calculating engine that we are developing for Australia. Keywords: spam cost, email spam, spam lifecycle 1 Introduction Spamming in email refers to sending unwanted, irrelevant, inappropriate and unsolicited email messages to a large number of recipients. Sending email is fast, convenient and cheap; making it as an important means of communication in business and personal. This is supported by the report from Radicati Group saying that there is a growth of email users from time to time [1]. Dependencies on email usage throughout the whole world provide a huge opportunity to the spammers for spamming. Spamming activities starts from spammers (who create and send spam), but its impacts goes far beyond them, involving Internet Service Provider (ISP), company, and users (spam email recipients) since they represent the key stakeholders. It is undeniable that each stakeholders involved in this activity has to bear some costs associated with spam. Throughout our study, there are a few papers discussing on the costs of email spam, but most of them focuses only on one stakeholder, which is the user. -
NIST SP 800-44 Version 2
Special Publication 800-44 Version 2 Guidelines on Securing Public Web Servers Recommendations of the National Institute of Standards and Technology Miles Tracy Wayne Jansen Karen Scarfone Theodore Winograd NIST Special Publication 800-44 Guidelines on Securing Public Web Version 2 Servers Recommendations of the National Institute of Standards and Technology Miles Tracy, Wayne Jansen, Karen Scarfone, and Theodore Winograd C O M P U T E R S E C U R I T Y Computer Security Division Information Technology Laboratory National Institute of Standards and Technology Gaithersburg, MD 20899-8930 September 2007 U.S. Department of Commerce Carlos M. Gutierrez, Secretary National Institute of Standards and Technology James Turner, Acting Director GUIDELINES ON SECURING PUBLIC WEB SERVERS Reports on Computer Systems Technology The Information Technology Laboratory (ITL) at the National Institute of Standards and Technology (NIST) promotes the U.S. economy and public welfare by providing technical leadership for the Nation’s measurement and standards infrastructure. ITL develops tests, test methods, reference data, proof of concept implementations, and technical analysis to advance the development and productive use of information technology. ITL’s responsibilities include the development of technical, physical, administrative, and management standards and guidelines for the cost-effective security and privacy of sensitive unclassified information in Federal computer systems. This Special Publication 800-series reports on ITL’s research, guidance, and outreach efforts in computer security, and its collaborative activities with industry, government, and academic organizations. National Institute of Standards and Technology Special Publication 800-44 Version 2 Natl. Inst. Stand. Technol. Spec. Publ. 800-44 Ver. -
WHITE PAPER Email Deliverability Review
WHITE PAPER Email DELIVeraBility REView dmawe are the White Paper Email Deliverability Review Published by Deliverability Hub of the Email Marketing Council Sponsored by 1 COPYRIGHT: THE DIRECT MARKETING ASSOCIATION (UK) LTD 2012 WHITE PAPER Email DELIVeraBility REView Contents About this document ...............................................................................................................................3 About the authors ...................................................................................................................................4 Sponsor’s perspective .............................................................................................................................5 Executive summary .................................................................................................................................6 1. Major factors that impact on deliverability ..............................................................................................7 1.1 Sender reputation .............................................................................................................................7 1.2 Spam filtering ...................................................................................................................................7 1.3 Blacklist operators ............................................................................................................................8 1.4 Smart Inboxes ..................................................................................................................................9 -
How Do Spammers Harvest Email Addresses ?
11/26/12 How do spammers harv est email addresses ? How do spammers harvest email addresses ? By Uri Raz There are many ways in which spammers can get your email address. The ones I know of are : 1. From posts to UseNet with your email address. Spammers regularily scan UseNet for email address, using ready made programs designed to do so. Some programs just look at articles headers which contain email address (From:, Reply-To:, etc), while other programs check the articles' bodies, starting with programs that look at signatures, through programs that take everything that contain a '@' character and attempt to demunge munged email addresses. There have been reports of spammers demunging email addresses on occasions, ranging from demunging a single address for purposes of revenge spamming to automatic methods that try to unmunge email addresses that were munged in some common ways, e.g. remove such strings as 'nospam' from email addresses. As people who where spammed frequently report that spam frequency to their mailbox dropped sharply after a period in which they did not post to UseNet, as well as evidence to spammers' chase after 'fresh' and 'live' addresses, this technique seems to be the primary source of email addresses for spammers. 2. From mailing lists. Spammers regularily attempt to get the lists of subscribers to mailing lists [some mail servers will give those upon request],knowing that the email addresses are unmunged and that only a few of the addresses are invalid. When mail servers are configured to refuse such requests, another trick might be used - spammers might send an email to the mailing list with the headers Return- Receipt-To: <email address> or X-Confirm-Reading-To: <email address>. -
Spam and Spam Prevention
SPAM AND SPAM PREVENTION 1 WHAT IS SPAM? • Classic definition: • Any kind of unsolicited bulk messages, unwanted by the receiver • Cambridge dictionary: • Email that is sent to a lot of people, esp. email that is not wanted • To send someone an advertisement that they do not want by email 2 WHAT IS SPAM? • According to Finn Brunton: “Spamming the project of leveraging information technology to exploit existing gatherings of attention” • Other definitions: • Breakfast meat sold in tin cans • Abbreviation for Special Processed American Meat 3 MEANINGS OF SPAM • Is spam a noun, adjective or a verb? • It refers to exploitation, malfeasance, and bad behavior. • Spam terminology has branched out into specific subdomains like: “Phishing spam”, “419 spam”, splogs, linkfarms, floodbots, content farms. 4 HISTORY OF SPAM • The three epochs of spam: 1. The first from 1970s – 1995 • During this time spam in this context was loud annoying messages 2. The second phase from 1995 – 2003 • Privatization of network • Passage of CAN-SPAM Act in the United States 3. The most recent phase from 2003 – present day • Algorithms and human attention • Adoption of powerful spam filters 5 SPAM STATISTICS • Out of the emails that people receive daily, about 85% are spam That is about 122.3 billion email spam messages • The most common source: • 10.85% come from IPs based in the United States • 23.52% originated from Russia (largest source of spam unsolicited emails sent) 6 SPAM STATISTICS 2019 VS 2020 2019: 2020: • 50,37% of emails were spam (6,14 • Most common spam: Nigerian Prince spam decrease) • Americans faced a fatality of $703,000 to this • Most originated from Russia (21,27%) type of fraud. -
84. Blog Spam Detection Using Intelligent Bayesian Approach
International Journal of Engineering Research and General Science Volume 2, Issue 5, August-September, 2014 ISSN 2091-2730 Blog-Spam Detection Using intelligent Bayesian Approach - Krushna Pandit, Savyasaachi Pandit Assistant Professor, GCET, VVNagar, E-mail- [email protected] , M - 9426759947 Abstract Blog-spam is one of the major problems of the Internet nowadays. Since the history of the internet the spam are considered a huge threat to the security and reliability of web content. The spam is the unsolicited messages sent for the fulfillment of the sender’s purpose and to harm the privacy of user, site owner and/or to steal available resource over the internet (may be or may not be allocated to).For dealing with spam there are so many methodologies available. Nowadays the blog spamming is a rising threat to safety, reliability, & purity of the published internet content. Since the search engines are using certain specific algorithms for creating the searching page-index/rank for the websites (i.e. google-analytics), it has attracted so many attention to spam the SMS(Social Media Sites) for gaining rank in order to increase the company’s popularity. The available solutions to malicious content detection are quite a more to be used very frequently in order to fulfill the requirement of analyzing all the web content in certain time with least possible ―false positives‖. For this purpose a site level algorithm is needed so that it can be easy, cheap & understandable (for site modifiers) to filter and monitor the content being published. Now for that we use a ―Bayes Theorem‖ of the ―Statistical approach‖.