Canit-PRO User's Guide
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Handling Unwanted Email What Are the Main Sources of Junk Email?
Handling unwanted email Almost entirely based on a presentation by Brian Candler What are the main sources of junk email? · Spam Unsolicited, bulk email Often fraudulent ± penis enlargement, lottery scams, close relatives of African presidents, etc. Low response rate => high volume sent · Viruses, Trojan horses Infected machine sends out mails without the owner 's knowledge · Malicious bounces These are called ªcollateral spamº or ªJoe-jobsº Junk mail is sent with forged MAIL FROM Accepted by some intermediate MTA, but later it bounces Bounces go to innocent third party 1 What are the costs? · Important messages can be accidentally discarded The more junk, the higher the risk · Wasted time Deleting junk Setting up and maintaining ®lters Checking discarded mail for false positives · Wasted bandwidth and disk space Especially for users on modems Viruses and spam attachments can be large · Annoyance, offence, even fraud There are no easy answers! 2 Where can you ®lter? · At the end-user hosts ✓ Each client has full control and customization ✓ Distributes the processing cost ✗ Client must still download each message · On the ISP's mail server ✓ Easier for users ✓ Sometimes can be rejected before receiving the body ✓ Saves disk space on the server ✗ Hard to make ¯exible for users to customize The Joe-job problem · Don't accept a message and then bounce it later If its sender is forged, we are creating a Joe-job · Much better to reject at RCPT TO or DATA stages A real MTA sender will create a bounce Spamware will ignore the rejection · For -
Spamming Botnets: Signatures and Characteristics
Spamming Botnets: Signatures and Characteristics Yinglian Xie, Fang Yu, Kannan Achan, Rina Panigrahy, Geoff Hulten+,IvanOsipkov+ Microsoft Research, Silicon Valley +Microsoft Corporation {yxie,fangyu,kachan,rina,ghulten,ivano}@microsoft.com ABSTRACT botnet infection and their associated control process [4, 17, 6], little In this paper, we focus on characterizing spamming botnets by effort has been devoted to understanding the aggregate behaviors of leveraging both spam payload and spam server traffic properties. botnets from the perspective of large email servers that are popular Towards this goal, we developed a spam signature generation frame- targets of botnet spam attacks. work called AutoRE to detect botnet-based spam emails and botnet An important goal of this paper is to perform a large scale analy- membership. AutoRE does not require pre-classified training data sis of spamming botnet characteristics and identify trends that can or white lists. Moreover, it outputs high quality regular expression benefit future botnet detection and defense mechanisms. In our signatures that can detect botnet spam with a low false positive rate. analysis, we make use of an email dataset collected from a large Using a three-month sample of emails from Hotmail, AutoRE suc- email service provider, namely, MSN Hotmail. Our study not only cessfully identified 7,721 botnet-based spam campaigns together detects botnet membership across the Internet, but also tracks the with 340,050 unique botnet host IP addresses. sending behavior and the associated email content patterns that are Our in-depth analysis of the identified botnets revealed several directly observable from an email service provider. Information interesting findings regarding the degree of email obfuscation, prop- pertaining to botnet membership can be used to prevent future ne- erties of botnet IP addresses, sending patterns, and their correlation farious activities such as phishing and DDoS attacks. -
Zambia and Spam
ZAMNET COMMUNICATION SYSTEMS LTD (ZAMBIA) Spam – The Zambian Experience Submission to ITU WSIS Thematic meeting on countering Spam By: Annabel S Kangombe – Maseko June 2004 Table of Contents 1.0 Introduction 1 1.1 What is spam? 1 1.2 The nature of Spam 1 1.3 Statistics 2 2.0 Technical view 4 2.1 Main Sources of Spam 4 2.1.1 Harvesting 4 2.1.2 Dictionary Attacks 4 2.1.3 Open Relays 4 2.1.4 Email databases 4 2.1.5 Inadequacies in the SMTP protocol 4 2.2 Effects of Spam 5 2.3 The fight against spam 5 2.3.1 Blacklists 6 2.3.2 White lists 6 2.3.3 Dial‐up Lists (DUL) 6 2.3.4 Spam filtering programs 6 2.4 Challenges of fighting spam 7 3.0 Legal Framework 9 3.1 Laws against spam in Zambia 9 3.2 International Regulations or Laws 9 3.2.1 US State Laws 9 3.2.2 The USA’s CAN‐SPAM Act 10 4.0 The Way forward 11 4.1 A global effort 11 4.2 Collaboration between ISPs 11 4.3 Strengthening Anti‐spam regulation 11 4.4 User education 11 4.5 Source authentication 12 4.6 Rewriting the Internet Mail Exchange protocol 12 1.0 Introduction I get to the office in the morning, walk to my desk and switch on the computer. One of the first things I do after checking the status of the network devices is to check my email. -
Enisa Etl2020
EN From January 2019 to April 2020 Spam ENISA Threat Landscape Overview The first spam message was sent in 1978 by a marketing manager to 393 people via ARPANET. It was an advertising campaign for a new product from the company he worked for, the Digital Equipment Corporation. For those first 393 spammed people it was as annoying as it would be today, regardless of the novelty of the idea.1 Receiving spam is an inconvenience, but it may also create an opportunity for a malicious actor to steal personal information or install malware.2 Spam consists of sending unsolicited messages in bulk. It is considered a cybersecurity threat when used as an attack vector to distribute or enable other threats. Another noteworthy aspect is how spam may sometimes be confused or misclassified as a phishing campaign. The main difference between the two is the fact that phishing is a targeted action using social engineering tactics, actively aiming to steal users’ data. In contrast spam is a tactic for sending unsolicited e-mails to a bulk list. Phishing campaigns can use spam tactics to distribute messages while spam can link the user to a compromised website to install malware and steal personal data. Spam campaigns, during these last 41 years have taken advantage of many popular global social and sports events such as UEFA Europa League Final, US Open, among others. Even so, nothing compared with the spam activity seen this year with the COVID-19 pandemic.8 2 __Findings 85%_of all e-mails exchanged in April 2019 were spam, a 15-month high1 14_million -
Locating Spambots on the Internet
BOTMAGNIFIER: Locating Spambots on the Internet Gianluca Stringhinix, Thorsten Holzz, Brett Stone-Grossx, Christopher Kruegelx, and Giovanni Vignax xUniversity of California, Santa Barbara z Ruhr-University Bochum fgianluca,bstone,chris,[email protected] [email protected] Abstract the world-wide email traffic [20], and a lucrative busi- Unsolicited bulk email (spam) is used by cyber- ness has emerged around them [12]. The content of spam criminals to lure users into scams and to spread mal- emails lures users into scams, promises to sell cheap ware infections. Most of these unwanted messages are goods and pharmaceutical products, and spreads mali- sent by spam botnets, which are networks of compro- cious software by distributing links to websites that per- mised machines under the control of a single (malicious) form drive-by download attacks [24]. entity. Often, these botnets are rented out to particular Recent studies indicate that, nowadays, about 85% of groups to carry out spam campaigns, in which similar the overall spam traffic on the Internet is sent with the mail messages are sent to a large group of Internet users help of spamming botnets [20,36]. Botnets are networks in a short amount of time. Tracking the bot-infected hosts of compromised machines under the direction of a sin- that participate in spam campaigns, and attributing these gle entity, the so-called botmaster. While different bot- hosts to spam botnets that are active on the Internet, are nets serve different, nefarious goals, one important pur- challenging but important tasks. In particular, this infor- pose of botnets is the distribution of spam emails. -
The History of Spam Timeline of Events and Notable Occurrences in the Advance of Spam
The History of Spam Timeline of events and notable occurrences in the advance of spam July 2014 The History of Spam The growth of unsolicited e-mail imposes increasing costs on networks and causes considerable aggravation on the part of e-mail recipients. The history of spam is one that is closely tied to the history and evolution of the Internet itself. 1971 RFC 733: Mail Specifications 1978 First email spam was sent out to users of ARPANET – it was an ad for a presentation by Digital Equipment Corporation (DEC) 1984 Domain Name System (DNS) introduced 1986 Eric Thomas develops first commercial mailing list program called LISTSERV 1988 First know email Chain letter sent 1988 “Spamming” starts as prank by participants in multi-user dungeon games by MUDers (Multi User Dungeon) to fill rivals accounts with unwanted electronic junk mail. 1990 ARPANET terminates 1993 First use of the term spam was for a post from USENET by Richard Depew to news.admin.policy, which was the result of a bug in a software program that caused 200 messages to go out to the news group. The term “spam” itself was thought to have come from the spam skit by Monty Python's Flying Circus. In the sketch, a restaurant serves all its food with lots of spam, and the waitress repeats the word several times in describing how much spam is in the items. When she does this, a group of Vikings in the corner start a song: "Spam, spam, spam, spam, spam, spam, spam, spam, lovely spam! Wonderful spam!" Until told to shut up. -
A Survey of Learning-Based Techniques of Email Spam Filtering
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Unitn-eprints Research A SURVEY OF LEARNING-BASED TECHNIQUES OF EMAIL SPAM FILTERING Enrico Blanzieri and Anton Bryl January 2008 (Updated version) Technical Report # DIT-06-056 A Survey of Learning-Based Techniques of Email Spam Filtering Enrico Blanzieri, University of Trento, Italy, and Anton Bryl University of Trento, Italy, Create-Net, Italy [email protected] January 11, 2008 Abstract vertising pornography, pyramid schemes, etc. [68]. The total worldwide financial losses caused by spam Email spam is one of the major problems of the to- in 2005 were estimated by Ferris Research Analyzer day’s Internet, bringing financial damage to compa- Information Service at $50 billion [31]. nies and annoying individual users. Among the ap- Lately, Goodman et al. [39] presented an overview proaches developed to stop spam, filtering is an im- of the field of anti-spam protection, giving a brief portant and popular one. In this paper we give an history of spam and anti-spam and describing major overview of the state of the art of machine learn- directions of development. They are quite optimistic ing applications for spam filtering, and of the ways in their conclusions, indicating learning-based spam of evaluation and comparison of different filtering recognition, together with anti-spoofing technologies methods. We also provide a brief description of and economic approaches, as one of the measures other branches of anti-spam protection and discuss which together will probably lead to the final victory the use of various approaches in commercial and non- over email spammers in the near future. -
Webfaction User Guide
WebFaction User Guide WebFaction is a service of Paragon Internet Group Limited CONTENTS 1 Introduction 3 1.1 Services..................................................3 1.2 The Complete System..........................................4 2 The Control Panel 5 2.1 Log in to the Control Panel.......................................5 2.2 Change Your Control Panel Password..................................5 2.3 What to Do About a Lost Password...................................6 2.4 Two-Step Login.............................................6 3 Finding Details About Your Server9 3.1 Finding Your Server’s Name.......................................9 3.2 Finding Your Server’s Operating System................................9 3.3 Finding Your Server’s IP Address.................................... 10 4 Accessing Your Data 11 4.1 Connecting with SSH.......................................... 11 4.2 Connecting with FTP........................................... 14 4.3 Changing Your FTP or SSH Password.................................. 14 4.4 Additional Users............................................. 15 4.5 Backups................................................. 16 5 Accounts 17 5.1 Plans and Services............................................ 17 5.2 Communicating with WebFaction.................................... 18 5.3 Payments................................................. 19 5.4 Affiliate Program............................................. 23 5.5 Canceling Your Account......................................... 24 6 Domains 25 6.1 Getting -
Combatting Spam Using Mimedefang, Spamassassin and Perl
Combating Spam Using SpamAssassin, MIMEDefang and Perl Copyright 2003 David F. Skoll Roaring Penguin Software Inc. (Booth #23) Administrivia Please turn off or silence cell phones, pagers, Blackberry devices, etc... After the tutorial, please be sure to fill out an evaluation form and return it to the USENIX folks. 2 Overview After this tutorial, you will: Understand how central mail filtering works. Know how to use MIMEDefang to filter mail. Be able to integrate SpamAssassin into your mail filter. Know how to implement mail filtering policies with MIMEDefang and Perl. Know how to fight common spammer tactics. 3 Outline Introduction to Mail Filtering Sendmail's Milter API MIMEDefang Introduction, Architecture Writing MIMEDefang Filters SpamAssassin Integration Advanced Filter Writing Fighting Common Spammer Tactics Advanced Topics Policy Suggestions 4 Assumptions I assume that you: Are familiar with Sendmail configuration. You don't need to be a sendmail.cf guru, but should know the basics. Are familiar with Perl. Again, you don't need to be able to write an AI program in a Perl one- liner, but should be able to read simple Perl scripts. Are running the latest version of Sendmail 8.12 on a modern UNIX or UNIX-like system. 5 Why Filter Mail? The old reason: to stop viruses. The new reason: to stop spam and inappropriate content. Blocking viruses is easy. Block .exe and similar files, and test against signature databases. Blocking spam is hard, but becoming increasingly important. Organizations can even face lawsuits over inappropriate content. 6 Mail filtering is required for many reasons. In addition to the reasons given on the slide, you might need to filter outgoing mail as well to prevent virus propagation, dissemination of sensitive information, etc. -
Set up Mail Server Documentation 1.0
Set Up Mail Server Documentation 1.0 Nosy 2014 01 23 Contents 1 1 1.1......................................................1 1.2......................................................2 2 11 3 13 3.1...................................................... 13 3.2...................................................... 13 3.3...................................................... 13 4 15 5 17 5.1...................................................... 17 5.2...................................................... 17 5.3...................................................... 17 5.4...................................................... 18 6 19 6.1...................................................... 19 6.2...................................................... 28 6.3...................................................... 32 6.4 Webmail................................................. 36 6.5...................................................... 37 6.6...................................................... 38 7 39 7.1...................................................... 39 7.2 SQL.................................................... 41 8 43 8.1...................................................... 43 8.2 strategy.................................................. 43 8.3...................................................... 44 8.4...................................................... 45 8.5...................................................... 45 8.6 Telnet................................................... 46 8.7 Can postfix receive?.......................................... -
Macsysadmin 2009 Presentatio
Slide 1 SpamAssassin Way more than the Mac OS X Server GUI shows Presented by: Kevin A. McGrail Project Management Committee Member of the Apache Software Foundation SpamAssassin Project & President, PCCC September 16, 2009 Good Afternoon, My name is Kevin A. McGrail. If you read my biographyi for this conference, you’ll know already that I hate Spam and enjoy greatly fighting spammers. You’ll also know that I love all types of computers and use a wide variety of machines & operating systems. But I’m definitely old-school in my love for the command line interface. This doesn’t mean I don’t think that Apple’s OS X is the most beautiful pairing of a rock-solid CLI with a beautifully polished GUI. But it does mean that while we are here to talk about Mac system administration, the configuration of SpamAssassin is largely not server specific and most of the heavy- handed configuration changes will be done behind the scenes using the CLI. So let’s get started by talking about the definition of Spam. Page 1 of 67 Slide 2 What is Spam? •Spam is NOT about content, its about CONSENT. – Consent: to give assent or approval : agree <consent to being tested> Merriam‐Webster Dictionary •What is SPAM vs. spam? September 16, 2009 Chris Santerre gave the best definition of Spam I’ve ever seen. He based the definition of Spam on CONSENT not content because consent is when you give approval to someone to send you e-mails. Many people try and use various legal definitions such as CAN-SPAM in the US. -
Abkürzungs-Liste ABKLEX
Abkürzungs-Liste ABKLEX (Informatik, Telekommunikation) W. Alex 1. Juli 2021 Karlsruhe Copyright W. Alex, Karlsruhe, 1994 – 2018. Die Liste darf unentgeltlich benutzt und weitergegeben werden. The list may be used or copied free of any charge. Original Point of Distribution: http://www.abklex.de/abklex/ An authorized Czechian version is published on: http://www.sochorek.cz/archiv/slovniky/abklex.htm Author’s Email address: [email protected] 2 Kapitel 1 Abkürzungen Gehen wir von 30 Zeichen aus, aus denen Abkürzungen gebildet werden, und nehmen wir eine größte Länge von 5 Zeichen an, so lassen sich 25.137.930 verschiedene Abkür- zungen bilden (Kombinationen mit Wiederholung und Berücksichtigung der Reihenfol- ge). Es folgt eine Auswahl von rund 16000 Abkürzungen aus den Bereichen Informatik und Telekommunikation. Die Abkürzungen werden hier durchgehend groß geschrieben, Akzente, Bindestriche und dergleichen wurden weggelassen. Einige Abkürzungen sind geschützte Namen; diese sind nicht gekennzeichnet. Die Liste beschreibt nur den Ge- brauch, sie legt nicht eine Definition fest. 100GE 100 GBit/s Ethernet 16CIF 16 times Common Intermediate Format (Picture Format) 16QAM 16-state Quadrature Amplitude Modulation 1GFC 1 Gigabaud Fiber Channel (2, 4, 8, 10, 20GFC) 1GL 1st Generation Language (Maschinencode) 1TBS One True Brace Style (C) 1TR6 (ISDN-Protokoll D-Kanal, national) 247 24/7: 24 hours per day, 7 days per week 2D 2-dimensional 2FA Zwei-Faktor-Authentifizierung 2GL 2nd Generation Language (Assembler) 2L8 Too Late (Slang) 2MS Strukturierte