A Taxonomy of Javascript Redirection Spam
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Click Trajectories: End-To-End Analysis of the Spam Value Chain
Click Trajectories: End-to-End Analysis of the Spam Value Chain ∗ ∗ ∗ ∗ z y Kirill Levchenko Andreas Pitsillidis Neha Chachra Brandon Enright Mark´ Felegyh´ azi´ Chris Grier ∗ ∗ † ∗ ∗ Tristan Halvorson Chris Kanich Christian Kreibich He Liu Damon McCoy † † ∗ ∗ Nicholas Weaver Vern Paxson Geoffrey M. Voelker Stefan Savage ∗ y Department of Computer Science and Engineering Computer Science Division University of California, San Diego University of California, Berkeley z International Computer Science Institute Laboratory of Cryptography and System Security (CrySyS) Berkeley, CA Budapest University of Technology and Economics Abstract—Spam-based advertising is a business. While it it is these very relationships that capture the structural has engendered both widespread antipathy and a multi-billion dependencies—and hence the potential weaknesses—within dollar anti-spam industry, it continues to exist because it fuels a the spam ecosystem’s business processes. Indeed, each profitable enterprise. We lack, however, a solid understanding of this enterprise’s full structure, and thus most anti-spam distinct path through this chain—registrar, name server, interventions focus on only one facet of the overall spam value hosting, affiliate program, payment processing, fulfillment— chain (e.g., spam filtering, URL blacklisting, site takedown). directly reflects an “entrepreneurial activity” by which the In this paper we present a holistic analysis that quantifies perpetrators muster capital investments and business rela- the full set of resources employed to monetize spam email— tionships to create value. Today we lack insight into even including naming, hosting, payment and fulfillment—using extensive measurements of three months of diverse spam data, the most basic characteristics of this activity. How many broad crawling of naming and hosting infrastructures, and organizations are complicit in the spam ecosystem? Which over 100 purchases from spam-advertised sites. -
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. -
Elastic Load Balancing Application Load Balancers Elastic Load Balancing Application Load Balancers
Elastic Load Balancing Application Load Balancers Elastic Load Balancing Application Load Balancers Elastic Load Balancing: Application Load Balancers Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Elastic Load Balancing Application Load Balancers Table of Contents What is an Application Load Balancer? .................................................................................................. 1 Application Load Balancer components ......................................................................................... 1 Application Load Balancer overview ............................................................................................. 2 Benefits of migrating from a Classic Load Balancer ........................................................................ 2 Related services ......................................................................................................................... 3 Pricing ...................................................................................................................................... 3 Getting started ................................................................................................................................. -
Elastic Load Balancing Application Load Balancers Elastic Load Balancing Application Load Balancers
Elastic Load Balancing Application Load Balancers Elastic Load Balancing Application Load Balancers Elastic Load Balancing: Application Load Balancers Elastic Load Balancing Application Load Balancers Table of Contents What is an Application Load Balancer? .................................................................................................. 1 Application Load Balancer components ......................................................................................... 1 Application Load Balancer overview ............................................................................................. 2 Benefits of migrating from a Classic Load Balancer ........................................................................ 2 Related services ......................................................................................................................... 3 Pricing ...................................................................................................................................... 3 Getting started .................................................................................................................................. 4 Before you begin ....................................................................................................................... 4 Step 1: Configure your target group ............................................................................................. 4 Step 2: Choose a load balancer type ........................................................................................... -
IBM Cognos Analytics - Reporting Version 11.1
IBM Cognos Analytics - Reporting Version 11.1 User Guide IBM © Product Information This document applies to IBM Cognos Analytics version 11.1.0 and may also apply to subsequent releases. Copyright Licensed Materials - Property of IBM © Copyright IBM Corp. 2005, 2021. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. IBM, the IBM logo and ibm.com are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at " Copyright and trademark information " at www.ibm.com/legal/copytrade.shtml. The following terms are trademarks or registered trademarks of other companies: • Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries. • Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both. • Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. • Linux is a registered trademark of Linus Torvalds in the United States, other countries, or both. • UNIX is a registered trademark of The Open Group in the United States and other countries. • Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates. -
Requests Documentation Release 2.26.0
Requests Documentation Release 2.26.0 Kenneth Reitz Sep 21, 2021 Contents 1 Beloved Features 3 2 The User Guide 5 2.1 Installation of Requests.........................................5 2.2 Quickstart................................................6 2.3 Advanced Usage............................................. 15 2.4 Authentication.............................................. 30 3 The Community Guide 33 3.1 Recommended Packages and Extensions................................ 33 3.2 Frequently Asked Questions....................................... 34 3.3 Integrations................................................ 35 3.4 Articles & Talks............................................. 35 3.5 Support.................................................. 36 3.6 Vulnerability Disclosure......................................... 36 3.7 Release Process and Rules........................................ 38 3.8 Community Updates........................................... 38 3.9 Release History.............................................. 39 4 The API Documentation / Guide 71 4.1 Developer Interface........................................... 71 5 The Contributor Guide 93 5.1 Contributor’s Guide........................................... 93 5.2 Authors.................................................. 96 Python Module Index 103 Index 105 i ii Requests Documentation, Release 2.26.0 Release v2.26.0. (Installation) Requests is an elegant and simple HTTP library for Python, built for human beings. Behold, the power of Requests: >>>r= requests.get ('https://api.github.com/user', -
Pulse Secure Virtual Traffic Manager: Trafficscript Guide, V19.3
Pulse Secure Virtual Traffic Manager: TrafficScript Guide Supporting Pulse Secure Virtual Traffic Manager 19.3 Product Release 19.3 Published 15 October, 2019 Document Version 1.0 Pulse Secure Virtual Traffic Manager: TrafficScript Guide Pulse Secure, LLC 2700 Zanker Road, Suite 200 San Jose CA 95134 www.pulsesecure.net © 2019 by Pulse Secure, LLC. All rights reserved. Pulse Secure and the Pulse Secure logo are trademarks of Pulse Secure, LLC in the United States. All other trademarks, service marks, registered trademarks, or registered service marks are the property of their respective owners. Pulse Secure, LLC assumes no responsibility for any inaccuracies in this document. Pulse Secure, LLC reserves the right to change, modify, transfer, or otherwise revise this publication without notice. Pulse Secure Virtual Traffic Manager: TrafficScript Guide The information in this document is current as of the date on the title page. END USER LICENSE AGREEMENT The Pulse Secure product that is the subject of this technical documentation consists of (or is intended for use with) Pulse Secure software. Use of such software is subject to the terms and conditions of the End User License Agreement (“EULA”) posted at http://www.pulsesecure.net/support/eula/. By downloading, installing or using such software, you agree to the terms and conditions of that EULA. © 2019 Pulse Secure, LLC. Pulse Secure Virtual Traffic Manager: TrafficScript Guide Contents PREFACE . 1 DOCUMENT CONVENTIONS . 1 TEXT FORMATTING CONVENTIONS . 1 COMMAND SYNTAX CONVENTIONS . 1 NOTES AND WARNINGS. 2 REQUESTING TECHNICAL SUPPORT . 2 SELF-HELP ONLINE TOOLS AND RESOURCES. 2 OPENING A CASE WITH PSGSC . 3 INTRODUCTION. -
Download Forecheck Guide
Forecheck Content 1 Welcome & Introduction 5 2 Overview: What Forecheck Can Do 6 3 First Steps 7 4 Projects and Analyses 9 5 Scheduler and Queue 12 6 Important Details 13 6.1 La..n..g..u..a..g..e..s.,. .C...h..a..r.a..c..t.e..r. .S..e..t.s.. .a..n..d.. .U..n..i.c..o..d..e....................................................................... 13 6.2 Ch..o..o..s..i.n..g.. .t.h..e.. .c.o..r..r.e..c..t. .F..o..n..t............................................................................................. 14 6.3 St.o..r.a..g..e.. .L..o..c..a..t.i.o..n.. .o..f. .D..a..t.a................................................................................................ 15 6.4 Fo..r.e..c..h..e..c..k. .U...s.e..r.-.A...g..e..n..t. .a..n..d.. .W...e..b.. .A..n..a..l.y..s.i.s.. .T..o..o..l.s............................................................. 15 6.5 Er.r.o..r.. .H..a..n..d..l.i.n..g................................................................................................................ 17 6.6 Ro..b..o..t.s...t.x..t.,. .n..o..i.n..d..e..x..,. .n..o..f.o..l.l.o..w......................................................................................... 18 6.7 Co..m...p..l.e..t.e.. .A..n..a..l.y..s..i.s. .o..f. .l.a..r.g..e.. .W....e..b..s.i.t.e..s............................................................................. 20 6.8 Fi.n..d..i.n..g.. .a..l.l. .p..a..g..e..s. .o..f. .a.. .W....e..b..s.i.t.e....................................................................................... 21 6.9 Go..o..g..l.e.. .A...n..a..l.y.t.i.c..s. -
Web Tracking: Mechanisms, Implications, and Defenses Tomasz Bujlow, Member, IEEE, Valentín Carela-Español, Josep Solé-Pareta, and Pere Barlet-Ros
ARXIV.ORG DIGITAL LIBRARY 1 Web Tracking: Mechanisms, Implications, and Defenses Tomasz Bujlow, Member, IEEE, Valentín Carela-Español, Josep Solé-Pareta, and Pere Barlet-Ros Abstract—This articles surveys the existing literature on the of ads [1], [2], price discrimination [3], [4], assessing our methods currently used by web services to track the user online as health and mental condition [5], [6], or assessing financial well as their purposes, implications, and possible user’s defenses. credibility [7]–[9]. Apart from that, the data can be accessed A significant majority of reviewed articles and web resources are from years 2012 – 2014. Privacy seems to be the Achilles’ by government agencies and identity thieves. Some affiliate heel of today’s web. Web services make continuous efforts to programs (e.g., pay-per-sale [10]) require tracking to follow obtain as much information as they can about the things we the user from the website where the advertisement is placed search, the sites we visit, the people with who we contact, to the website where the actual purchase is made [11]. and the products we buy. Tracking is usually performed for Personal information in the web can be voluntarily given commercial purposes. We present 5 main groups of methods used for user tracking, which are based on sessions, client by the user (e.g., by filling web forms) or it can be collected storage, client cache, fingerprinting, or yet other approaches. indirectly without their knowledge through the analysis of the A special focus is placed on mechanisms that use web caches, IP headers, HTTP requests, queries in search engines, or even operational caches, and fingerprinting, as they are usually very by using JavaScript and Flash programs embedded in web rich in terms of using various creative methodologies. -
A Study on Topologically Dedicated Hosts on Malicious Web Infrastructures
Finding the Linchpins of the Dark Web: a Study on Topologically Dedicated Hosts on Malicious Web Infrastructures Zhou Li, Sumayah Alrwais Yinglian Xie, Fang Yu XiaoFeng Wang Indiana University at Bloomington MSR Silicon Valley Indiana University at Bloomington {lizho, salrwais}@indiana.edu {yxie, fangyu}@microsoft.com [email protected] Abstract—Malicious Web activities continue to be a major misdeeds. Indeed, such infrastructures become the backbone threat to the safety of online Web users. Despite the plethora of the crimes in today’s cyberspace, delivering malicious forms of attacks and the diversity of their delivery channels, web content world wide and causing hundreds of millions in the back end, they are all orchestrated through malicious Web infrastructures, which enable miscreants to do business in damage every year. with each other and utilize others’ resources. Identifying the Malicious Web infrastructures. Given the central role linchpins of the dark infrastructures and distinguishing those those infrastructures play, an in-depth understanding of their valuable to the adversaries from those disposable are critical for gaining an upper hand in the battle against them. structures and the ways they work becomes critical for coun- In this paper, using nearly 4 million malicious URL paths teracting cybercrimes. To this end, prior research investi- crawled from different attack channels, we perform a large- gated the infrastructures associated with some types of chan- scale study on the topological relations among hosts in the nels (e.g., Spam [2], black-hat Search-Engine Optimization malicious Web infrastructure. Our study reveals the existence (SEO) [11]) and exploits (e.g., drive-by downloads [23]). -
Lxmldoc-4.5.0.Pdf
lxml 2020-01-29 Contents Contents 2 I lxml 14 1 lxml 15 Introduction................................................. 15 Documentation............................................... 15 Download.................................................. 16 Mailing list................................................. 17 Bug tracker................................................. 17 License................................................... 17 Old Versions................................................. 17 2 Why lxml? 18 Motto.................................................... 18 Aims..................................................... 18 3 Installing lxml 20 Where to get it................................................ 20 Requirements................................................ 20 Installation................................................. 21 MS Windows............................................. 21 Linux................................................. 21 MacOS-X............................................... 21 Building lxml from dev sources....................................... 22 Using lxml with python-libxml2...................................... 22 Source builds on MS Windows....................................... 22 Source builds on MacOS-X......................................... 22 4 Benchmarks and Speed 23 General notes................................................ 23 How to read the timings........................................... 24 Parsing and Serialising........................................... 24 The ElementTree -
The Abcs—Web Lingo and Definitions
THE ABCS—WEB LINGO AND DEFINITIONS THE A's ABOVE THE FOLD the page section visible without scrolling down—the exact size depends on screen settings; this is premium ad-rate space but may be worth it. AD EXTENSIONS added information in a text ad such as location, phone number, and links. AD NETWORKING multiple websites with a single advertiser controlling all or a portion of the sites' ad space, such as Google Search Network, which includes AOL, Amazon, Ask.com (formerly Ask Jeeves), and thousands of other sites. AD WORDS is Google’s paid search marketing program (introduced in 2001), the world's largest and available in only a handful of countries that run their own similar programs such as Russia (Yandex) and China (Baidu). AdWords uses a Quality Score determined by search relevancy (via click- through rate) and bid to determine an ad's positioning. AFFILIATE MARKETING involves internet marketing with other partner websites, individuals, or companies to drive site traffic, typically with fees based on a Cost per Acquisition (CPA) or Cost per Click (CPC) basis. AGGREGATE DATA details how a group of consumers interacts with your marketing or websites and what they do after interacting, offering a comprehensive view of your target market as a whole, as opposed to the behavior of individuals. ALGORITHM is a trade-secret formula (or formulas) used by search engines to determine search rankings in natural or organic search. Search engines periodically crawl sites (using “Spiders”) to analyze site content and value-rank your site for searches. ALT TAGS are embedded HTML tags used to make website graphics viewable by search engines, which are otherwise generally unable to view graphics or see text they might contain.