Email in the Early 1980'S Spoofed Email the Received Header Spam
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Technical and Legal Approaches to Unsolicited Electronic Mail, 35 USFL Rev
UIC School of Law UIC Law Open Access Repository UIC Law Open Access Faculty Scholarship 1-1-2001 Technical and Legal Approaches to Unsolicited Electronic Mail, 35 U.S.F. L. Rev. 325 (2001) David E. Sorkin John Marshall Law School, [email protected] Follow this and additional works at: https://repository.law.uic.edu/facpubs Part of the Computer Law Commons, Internet Law Commons, Marketing Law Commons, and the Privacy Law Commons Recommended Citation David E. Sorkin, Technical and Legal Approaches to Unsolicited Electronic Mail, 35 U.S.F. L. Rev. 325 (2001). https://repository.law.uic.edu/facpubs/160 This Article is brought to you for free and open access by UIC Law Open Access Repository. It has been accepted for inclusion in UIC Law Open Access Faculty Scholarship by an authorized administrator of UIC Law Open Access Repository. For more information, please contact [email protected]. Technical and Legal Approaches to Unsolicited Electronic Mailt 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 "spain," 2 causes or contributes to a wide variety of problems for network administrators, t 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. -
Trendmicro™ Hosted Email Security
TrendMicro™ Hosted Email Security Best Practice Guide Trend Micro Incorporated reserves the right to make changes to this document and to the products described herein without notice. The names of companies, products, people, characters, and/or data mentioned herein are fictitious and are in no way intended to represent any real individual, company, product, or event, unless otherwise noted. Complying with all applicable copyright laws is the responsibility of the user. Copyright © 2016 Trend Micro Incorporated. All rights reserved. Trend Micro, the Trend Micro t-ball logo, and TrendLabs are trademarks or registered trademarks of Trend Micro, Incorporated. All other brand and product names may be trademarks or registered trademarks of their respective companies or organizations. No part of this publication may be reproduced, photocopied, stored in a retrieval system, or transmitted without the express prior written consent of Trend Micro Incorporated. Authors : Michael Mortiz, Jefferson Gonzaga Editorial : Jason Zhang Released : June 2016 Table of Contents 1 Best Practice Configurations ................................................................................................................................. 8 1.1 Activating a domain ....................................................................................................................................... 8 1.2 Adding Approved/Blocked Sender ................................................................................................................ 8 1.3 HES order -
In-Depth Evaluation of Redirect Tracking and Link Usage
Proceedings on Privacy Enhancing Technologies ; 2020 (4):394–413 Martin Koop*, Erik Tews, and Stefan Katzenbeisser In-Depth Evaluation of Redirect Tracking and Link Usage Abstract: In today’s web, information gathering on 1 Introduction users’ online behavior takes a major role. Advertisers use different tracking techniques that invade users’ privacy It is common practice to use different tracking tech- by collecting data on their browsing activities and inter- niques on websites. This covers the web advertisement ests. To preventing this threat, various privacy tools are infrastructure like banners, so-called web beacons1 or available that try to block third-party elements. How- social media buttons to gather data on the users’ on- ever, there exist various tracking techniques that are line behavior as well as privacy sensible information not covered by those tools, such as redirect link track- [52, 69, 73]. Among others, those include information on ing. Here, tracking is hidden in ordinary website links the user’s real name, address, gender, shopping-behavior pointing to further content. By clicking those links, or or location [4, 19]. Connecting this data with informa- by automatic URL redirects, the user is being redirected tion gathered from search queries, mobile devices [17] through a chain of potential tracking servers not visible or content published in online social networks [5, 79] al- to the user. In this scenario, the tracker collects valuable lows revealing further privacy sensitive information [62]. data about the content, topic, or user interests of the This includes personal interests, problems or desires of website. Additionally, the tracker sets not only third- users, political or religious views, as well as the finan- party but also first-party tracking cookies which are far cial status. -
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. -
Redirect URL
July 2012 Redirect URL User Guide Welcome to AT&T Website Solutions SM We are focused on providing you the very best web hosting service including all the tools necessary to establish and maintain a successful website. This document contains information that will help you to redirect pages from your site to other locations. You can use it to create a new Domain Redirection as well. © 2012 AT&T Intellectual Property. All rights reserved. AT&T products and services are provided or offered by subsidiaries and affiliates of AT&T Inc. under the AT&T brand and not by AT&T Inc. AT&T, AT&T logo and all other AT&T marks contained herein are trademarks of AT&T Intellectual Property and/or AT&T affiliated companies. All other trademarks are the property of their owners. This document is not an offer, commitment, representation or warranty by AT&T and is subject to change. Your Web Hosting service is subject to the Terms and Conditions (T&Cs), which may be found at http://webhosting.att.com/Terms-Conditions.aspx . Service terms and Fees are subject to change without notice. Please read the T&Cs for additional information. © 2010 AT&T Intellectual Property. All rights re served. AT&T and the AT&T logo are trademarks of AT&T Intellectual Property. Table of ContenContentstststs Introduction ........................................................................................................................................................ 3 Create a New Redirect ................................................................................................................................... -
Successful Non-Governmental Threat Attribution
Successful Non-Governmental! Threat Attribution, Containment! and Deterrence: A Case Study! Joe St Sauver, Ph.D. ! [email protected] or [email protected]! Internet2 Nationwide Security Programs Manager! November 2nd, 2010, 1:15-2:30 PM, Chancellor I! http://pages.uoregon.edu/joe/attribute-contain-deter/! Disclaimer: The opinions expressed are those of the author and ! do not necessarily represent the opinion of any other party.! I. Introduction! 2! Cyberspace: Anonymous and Undeterred?! • General Keith Alexander, Director of the National Security Agency (DIRNSA), recently commented [1] that in cyberspace:! "" "“It is difficult to deliver an effective response if the ! " "attacker's identity isn't known,” and ! " "“It is unclear if the government's response to cyber ! " "threats and attacks have deterred criminals, ! " "terrorists, or nations.” ! • That's a provocatively framed (if equivocal) assessment, and one worthy of careful consideration given its source. ! 3! Is The Concept of Deterrence Even Relevant to ! Attacks on Private Critical Cyber Infrastructure?! • In pondering that quote, I also note the National Research Council's (NRC's) “Cyber Deterrence Research and Scholarship” question number 39, [2] which asked: ! "" "How and to what extent, if at all, is deterrence applicable! " "to cyber attacks on private companies (especially those that! " "manage U.S. critical infrastructure)? ! • Since the Office of the Director of National Intelligence (ODNI) requested the NRC's inquiry into cyber deterrence, and since General Alexander is now leading the new United States Cyber Command as well as the National Security Agency, it is appropriate to consider these two questions jointly. ! 4! Can We Identify An Example of Successful Attribution and Cyber Deterrence?! • If we are to prove that cyber deterrence is both relevant and possible, and that the difficulties associated with attribution can be overcome, we must be able to point to at least one example of successful attribution and cyber deterrence. -
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. -
Detection of Malicious Urls by Correlating the Chains of Redirection in an Online Social Network (Twitter)
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) Volume 1, Issue 3, July 2014, PP 33-38 ISSN 2349-4840 (Print) & ISSN 2349-4859 (Online) www.arcjournals.org Detection of Malicious URLs by Correlating the Chains of Redirection in an Online Social Network (Twitter) 1MD.Sabeeha, SK.Karimullah, 2P.Babu 1PG Schalor,CSE, Quba college of engineering and technology 2, Associate professor, QCET, NELLORE ABSTRACT: Twitter is prone to malicious tweets containing URLs for spam, phishing, and malware distribution. Conventional Twitter spam detection schemes utilize account features such as the ratio of tweets containing URLs and the account creation date, or relation features in the Twitter graph. These detection schemes are ineffective against feature fabrications or consume much time and resources. Conventional suspicious URL detection schemes utilize several features including lexical features of URLs, URL redirection, HTML content, and dynamic behavior. However, evading techniques such as time-based evasion and crawler evasion exist. In this paper, we propose WARNINGBIRD, a suspicious URL detection system for Twitter. Our system investigates correlations of URL redirect chains extracted from several tweets. Because attackers have limited resources and usually reuse them, their URL redirect chains frequently share the same URLs. We develop methods to discover correlated URL redirect chains using the frequently shared URLs and to determine their suspiciousness. We collect numerous tweets from the Twitter public timeline and build a statistical classifier using them. Evaluation results show that our classifier accurately and efficiently detects suspicious URLs. We also present WARNINGBIRD as a near real-time system for classifying suspicious URLs in the Twitter stream. -
OWASP Asia 2008 Rsnake.Pdf
1 Robert Hansen - CEO SecTheory LLC Bespoke Boutique Internet Security Web Application/Browser Security Network/OS Security http://www.sectheory.com/ Advisory capacity to VCs/start-ups Founded the web application security lab http://ha.ckers.org/ - the lab http://sla.ckers.org/ - the forum 2 iHumble I want to explain the history… Only a few know the whole story. Sit back and relax, it’s story time. 3 We’ve all heard these sentiments: “If you find a vulnerability, we ask that you share it with us. If you share it with us, we will respond to you with a time we will fix that hole.” Scott Petry – Director @ Google (We’ll be coming back to this!) 4 It all started four years ago… We found that redirection vulnerabilities were being used by phishers in a number of sites, Visa, Doubleclick, eBay and of course, Google to confuse consumers. Timeframes for fixes: Visa closed their hole down within hours Double Click within days (partially) eBay within weeks Google still hasn’t closed them (~4 years later) Every company agrees it’s a hole. Everyone 5 Word gets out – fast! http://blogs.geekdojo.net/brian/archive/2004/10/14/googlephishing.aspx http://lists.virus.org/dshield-0602/msg00156.html http://blog.eweek.com/blogs/larry_seltzer/archive/2006/03/05/8240.aspx http://thespamdiaries.blogspot.com/2006/03/google-used-as-url-cloaking-device- in.html http://www.docuverse.com/blog/donpark/EntryViewPage.aspx?guid=e08af74b- 8b86-418c-94e0-7d29a7cb91e2 http://email.about.com/od/outlooktips/qt/et043005.htm http://listserv.educause.edu/cgi- bin/wa.exe?A2=ind0511&L=security&T=0&F=&S=&P=15599 http://www.zataz.com/news/13296/google-corrige-une-faille.html http://google.blognewschannel.com/archives/2007/02/22/google-changes-redirects- adds-nofollow-to-blogger/ http://googlesystem.blogspot.com/2007/02/google-redirect-notice.html And others… 6 Everyone has vulns. -
Real-Time Detection System for Suspicious Urls Krishna Prasad Chouty Governors State University
Governors State University OPUS Open Portal to University Scholarship All Capstone Projects Student Capstone Projects Fall 2015 Real-Time Detection System for Suspicious URLs Krishna Prasad Chouty Governors State University Anup Chandra Thogiti Governors State University Kranthi Sudha Vudatha Governors State University Follow this and additional works at: http://opus.govst.edu/capstones Part of the Digital Communications and Networking Commons, and the Information Security Commons Recommended Citation Chouty, Krishna Prasad; Thogiti, Anup Chandra; and Vudatha, Kranthi Sudha, "Real-Time Detection System for Suspicious URLs" (2015). All Capstone Projects. 164. http://opus.govst.edu/capstones/164 For more information about the academic degree, extended learning, and certificate programs of Governors State University, go to http://www.govst.edu/Academics/Degree_Programs_and_Certifications/ Visit the Governors State Computer Science Department This Project Summary is brought to you for free and open access by the Student Capstone Projects at OPUS Open Portal to University Scholarship. It has been accepted for inclusion in All Capstone Projects by an authorized administrator of OPUS Open Portal to University Scholarship. For more information, please contact [email protected]. REAL-TIMEDETECTION SYSTEM FOR SUSPICIOUS URL’S By Krishna Prasad, Chouty B.Tech, JAWAHARLAL NEHURU TECHNOLOGICAL UNIVERSITY, 2012 AnupChandra, Thogiti B.Tech, JAWAHARLAL NEHURU TECHNOLOGICAL UNIVERSITY, 2011 Kranthi Sudha, Vudatha B.Tech, JAWAHARLAL NEHURU TECHNOLOGICAL UNIVERSITY, -
A Proposed Technique for Tracing Origin of Spam on the Usenet
A proposed technique for tracing origin of spam on the Usenet by Dirk Bertels, BComp A dissertation submitted to the School of Computing in partial fulfillment of the requirements for the degree of Bachelor of Computing with Honours University of Tasmania June 2006 This thesis contains no material which has been accepted for the award of any other degree or diploma in any tertiary institution. To the candidate’s knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made in the text of the thesis. Signed Dirk Bertels Hobart, June 2006 Abstract The Usenet, a worldwide distributed decentralized conferencing system, is widely targeted by spammers who use a variety of techniques in order to obscure their identity. One of these techniques is called path preload, in which the path header is spoofed by means of attaching a false section at the beginning of this path. The process of detecting and confirming path preload is laborious and requires a thorough understanding of the Usenet. A technique which downloads a particular article from several servers, and compares their path headers is explored as to its usefulness regarding path preload detection. This document begins with a general background on the Usenet, highlighting those aspects that are relevant to the research, especially the topics of Usenet headers and spam. This leads to a description of the proposed technique and the development of a tool capable of implementing this technique. The tool essentially downloads a spam article from different servers, and analyses their headers. -
Glossary of Spam Terms
white paper Glossary of Spam terms The jargon of The spam indusTry table of Contents A Acceptable Use Policy (AUP) . 5 Alias . 5 Autoresponder . 5 B Ban on Spam . 5 Bayesian Filtering . 5 C CAN-SPAM . 5 Catch Rate . 5 CAUSe . 5 Challenge Response Authentication . 6 Checksum Database . 6 Click-through . 6 Content Filtering . 6 Crawler . 6 D Denial of Service (DoS) . 6 Dictionary Attack . 6 DNSBL . 6 e eC Directive . 7 e-mail Bomb . 7 exploits Block List (XBL) (from Spamhaus org). 7 F False Negative . 7 False Positive . 7 Filter Scripting . 7 Fingerprinting . 7 Flood . 7 h hacker . 8 header . 8 heuristic Filtering . 8 honeypot . 8 horizontal Spam . 8 i internet Death Penalty . 8 internet Service Provider (iSP) . 8 J Joe Job . 8 K Keyword Filtering . 9 Landing Page . 9 LDAP . 9 Listwashing . 9 M Machine-learning . 9 Mailing List . 9 Mainsleaze . 9 Malware . 9 Mung . 9 N Nigerian 419 Scam . 10 Nuke . 10 O Open Proxy . 10 Open Relay . 10 Opt-in . 10 Opt-out . 10 P Pagejacking . 10 Phishing . 10 POP3 . 11 Pump and Dump . 11 Q Quarantine . 11 R RBLs . 11 Reverse DNS . 11 ROKSO . 11 S SBL . 11 Scam . 11 Segmentation . 11 SMtP . 12 Spam . 12 Spambot . 12 Spamhaus . 12 Spamming . 12 Spamware . 12 SPewS . 12 Spider . 12 Spim . 12 Spoof . 12 Spyware . 12 t training Set . 13 trojan horse . 13 trusted Senders List . 13 U UCe . 13 w whack-A-Mole . 13 worm . 13 V Vertical Spam . 13 Z Zombie . 13 Glossary of Spam terms A acceptable use policy (AUP) A policy statement, made by an iSP, whereby the company outlines its rules and guidelines for use of the account .