Automated Malware Analysis Report For

Total Page:16

File Type:pdf, Size:1020Kb

Automated Malware Analysis Report For ID: 289897 Cookbook: browseurl.jbs Time: 11:27:39 Date: 25/09/2020 Version: 30.0.0 Red Diamond Table of Contents Table of Contents 2 Analysis Report http://c3.sdkclickurl.com/click/? adgroup_id=3954232&user_id=699999&timeflag=202009250600&mid=2157&android_id={android_id}&bundle={bundle}&ip= {ip}&ua={ua}&lang= {lang}&tid=RSB_C8323ABF5CB47CABF251DE48B390223CD18ED4F247BEB9107AEA02D0D05C1F8B6020BB87965D54B6422A0F9E968CC1A9_MOBILEPARTNER_zya_giraffe5f6d8fd1e4b04b780100a4fe26&gaid=6d0fd5e2- dfb8-4abf-b91c-844c98a8929d&pub_id=28446&idx=26 3 Overview 3 General Information 3 Detection 3 Signatures 3 Classification 3 Startup 4 Malware Configuration 4 Yara Overview 4 Sigma Overview 4 Signature Overview 4 Mitre Att&ck Matrix 5 Behavior Graph 5 Screenshots 5 Thumbnails 5 Antivirus, Machine Learning and Genetic Malware Detection 6 Initial Sample 6 Dropped Files 6 Unpacked PE Files 6 Domains 7 URLs 7 Domains and IPs 7 Contacted Domains 7 Contacted URLs 7 URLs from Memory and Binaries 7 Contacted IPs 7 Public 8 General Information 8 Simulations 9 Behavior and APIs 9 Joe Sandbox View / Context 9 IPs 9 Domains 9 ASN 9 JA3 Fingerprints 9 Dropped Files 9 Created / dropped Files 10 Static File Info 14 No static file info 14 Network Behavior 14 Network Port Distribution 14 TCP Packets 15 UDP Packets 16 DNS Queries 16 DNS Answers 17 HTTP Request Dependency Graph 17 HTTP Packets 17 HTTPS Packets 18 Code Manipulations 18 Statistics 19 Behavior 19 System Behavior 19 Analysis Process: iexplore.exe PID: 5320 Parent PID: 788 19 General 19 File Activities 19 Registry Activities 19 Analysis Process: iexplore.exe PID: 4444 Parent PID: 5320 20 General 20 File Activities 20 Registry Activities 20 Disassembly 20 Copyright null 2020 Page 2 of 20 Analysis Report http://c3.sdkclickurl.com/click/?adgroup…_id=3954232&user_id=699999&timeflag=202009250600&mid=2157&android_id={android_id}&bundle={bundle}&ip={ip}&ua={ua}&lang={lang}&tid=RSB_C8323ABF5CB47CABF251DE48B390223CD18ED4F247BEB9107AEA02D0D05C1F8B6020BB87965D54B6422A0F9E968CC1A9_MOBILEPARTNER_zya_giraffe5f6d8fd1e4b04b780100a4fe26&gaid=6d0fd5e2-dfb8-4abf-b91c-844c98a8929d&pub_id=28446&idx=26 Overview General Information Detection Signatures Classification Sample URL: c3.sdkclickurl.com/cli No high impact signatures. ck/?adgroup_id=3954232& user_id=699999&timeflag= 202009250600&mid=2157 &android_id={android_id}& bundle={bundle}&ip={ip}&u a={ua}&lang={lang}&tid=R SB_C8323ABF5CB47CAB F251DE48B390223CD18E D4F247BEB9107AEA02D 0D05C1F8B6020BB87965 D54B6422A0F9E968CC1A 9_MOBILEPARTNER_zya _giraffe5f6d8fd1e4b04b780 100a4fe26&gaid=6d0fd5e2 -dfb8-4abf-b91c-844c98a8 929d&pub_id=28446&idx= 26 Score: 0 Analysis ID: 289897 Range: 0 - 100 Most interesting Screenshot: Whitelisted: false Confidence: 80% Copyright null 2020 Page 3 of 20 Ransomware Miner Spreading mmaallliiiccciiioouusss malicious Evader Phishing sssuusssppiiiccciiioouusss suspicious cccllleeaann clean Exploiter Banker Spyware Trojan / Bot Adware Startup System is w10x64 iexplore.exe (PID: 5320 cmdline: 'C:\Program Files\Internet Explorer\iexplore.exe' -Embedding MD5: 6465CB92B25A7BC1DF8E01D8AC5E7596) iexplore.exe (PID: 4444 cmdline: 'C:\Program Files (x86)\Internet Explorer\IEXPLORE.EXE' SCODEF:5320 CREDAT:17410 /prefetch:2 MD5: 071277CC2E3DF41EEEA8013E2AB58D5A) cleanup Malware Configuration No configs have been found Yara Overview No yara matches Sigma Overview No Sigma rule has matched Signature Overview • Networking • System Summary Click to jump to signature section There are no malicious signatures, click here to show all signatures . Copyright null 2020 Page 4 of 20 Mitre Att&ck Matrix Command Remote Initial Privilege Defense Credential Lateral and Network Service Access Execution Persistence Escalation Evasion Access Discovery Movement Collection Exfiltration Control Effects Effects Impact Valid Windows Path Process Masquerading 1 OS File and Remote Data from Exfiltration Encrypted Eavesdrop on Remotely Modify Accounts Management Interception Injection 1 Credential Directory Services Local Over Other Channel 2 Insecure Track Device System Instrumentation Dumping Discovery 1 System Network Network Without Partition Medium Communication Authorization Default Scheduled Boot or Boot or Process LSASS Application Remote Data from Exfiltration Non- Exploit SS7 to Remotely Device Accounts Task/Job Logon Logon Injection 1 Memory Window Desktop Removable Over Application Redirect Phone Wipe Data Lockout Initialization Initialization Discovery Protocol Media Bluetooth Layer Calls/SMS Without Scripts Scripts Protocol 2 Authorization Domain At (Linux) Logon Script Logon Obfuscated Files Security Query SMB/Windows Data from Automated Application Exploit SS7 to Obtain Delete Accounts (Windows) Script or Information Account Registry Admin Shares Network Exfiltration Layer Track Device Device Device (Windows) Manager Shared Protocol 3 Location Cloud Data Drive Backups Local At (Windows) Logon Script Logon Binary Padding NTDS System Distributed Input Scheduled Ingress SIM Card Carrier Accounts (Mac) Script Network Component Capture Transfer Tool Swap Billing (Mac) Configuration Object Model Transfer 1 Fraud Discovery Behavior Graph Hide Legend Behavior Graph Legend: ID: 289897 Process URL: http://c3.sdkclickurl.com/c... Signature Startdate: 25/09/2020 Created File Architecture: WINDOWS DNS/IP Info Score: 0 Is Dropped Is Windows Process Number of created Registry Values impression.appsflyer.com started Number of created Files Visual Basic Delphi iexplore.exe Java .Net C# or VB.NET C, C++ or other language 11 85 Is malicious Internet started iexplore.exe 33 c3.sdkclickurl.com impression.appsflyer.com 47.254.213.111, 49707, 49708, 80 52.51.186.116, 443, 49709, 49710 CNNIC-ALIBABA-US-NET-APAlibabaUSTechnologyCoLtdC AMAZON-02US United States United States Screenshots Thumbnails This section contains all screenshots as thumbnails, including those not shown in the slideshow. Copyright null 2020 Page 5 of 20 Antivirus, Machine Learning and Genetic Malware Detection Initial Sample Source Detection Scanner Label Link c3.sdkclickurl.com/click/? 3% Virustotal Browse adgroup_id=3954232&user_id=699999&timeflag=202009250600&mid=2157&android_id= {android_id}&bundle={bundle}&ip={ip}&ua={ua}&lang= {lang}&tid=RSB_C8323ABF5CB47CABF251DE48B390223CD18ED4F247BEB9107AEA02D0D05C1F8B 6020BB87965D54B6422A0F9E968CC1A9_MOBILEPARTNER_zya_giraffe5f6d8fd1e4b04b780100a4fe2 6&gaid=6d0fd5e2-dfb8-4abf-b91c-844c98a8929d&pub_id=28446&idx=26 c3.sdkclickurl.com/click/? 0% Avira URL Cloud safe adgroup_id=3954232&user_id=699999&timeflag=202009250600&mid=2157&android_id= {android_id}&bundle={bundle}&ip={ip}&ua={ua}&lang= {lang}&tid=RSB_C8323ABF5CB47CABF251DE48B390223CD18ED4F247BEB9107AEA02D0D05C1F8B 6020BB87965D54B6422A0F9E968CC1A9_MOBILEPARTNER_zya_giraffe5f6d8fd1e4b04b780100a4fe2 6&gaid=6d0fd5e2-dfb8-4abf-b91c-844c98a8929d&pub_id=28446&idx=26 Dropped Files No Antivirus matches Unpacked PE Files Copyright null 2020 Page 6 of 20 No Antivirus matches Domains Source Detection Scanner Label Link c3.sdkclickurl.com 1% Virustotal Browse URLs Source Detection Scanner Label Link www.wikipedia.com/ 0% Virustotal Browse www.wikipedia.com/ 0% URL Reputation safe www.wikipedia.com/ 0% URL Reputation safe www.wikipedia.com/ 0% URL Reputation safe Domains and IPs Contacted Domains Name IP Active Malicious Antivirus Detection Reputation impression.appsflyer.com 52.51.186.116 true false high c3.sdkclickurl.com 47.254.213.111 true false 1%, Virustotal, Browse unknown Contacted URLs Name Malicious Antivirus Detection Reputation https://impression.appsflyer.com/de.autodoc.gmbh? false high c=Autodoc_Android_CPA&af_viewthrough_lookback=1d&af_siteid=92517477&pid=roockmobil e_int&clickid=20200925092837_wangmeng10_21df697a0270dd7675eabf9afce2d53444227_v3 &android_id={android_id}&advertising_id=6d0fd5e2-dfb8-4abf-b91c-844c98a8929d&imei= {imei}&idfa=6d0fd5e2-dfb8-4abf-b91c-844c98a8929d c3.sdkclickurl.com/click/? false unknown adgroup_id=3954232&user_id=699999&timeflag=202009250600&mid=2157&android_id= {android_id}&bundle={bundle}&ip={ip}&ua={ua}&lang= {lang}&tid=RSB_C8323ABF5CB47CABF251DE48B390223CD18ED4F247BEB9107AEA02D0 D05C1F8B6020BB87965D54B6422A0F9E968CC1A9_MOBILEPARTNER_zya_giraffe5f6d8fd 1e4b04b780100a4fe26&gaid=6d0fd5e2-dfb8-4abf-b91c- 844c98a8929d&pub_id=28446&idx=26 URLs from Memory and Binaries Name Source Malicious Antivirus Detection Reputation www.wikipedia.com/ msapplication.xml7.1.dr false 0%, Virustotal, Browse unknown URL Reputation: safe URL Reputation: safe URL Reputation: safe www.amazon.com/ msapplication.xml.1.dr false high www.nytimes.com/ msapplication.xml4.1.dr false high https://impression.appsflyer.com/de.autodoc.gmbh? {EB2B3048-FF5C-11EA-90E3-ECF4B false high c=Autodoc_Android_CPA&af_viewthrough_lookback=1d&af B570DC9}.dat.1.dr, ~DFF0DB07DF 8329656E.TMP.1.dr www.live.com/ msapplication.xml3.1.dr false high www.reddit.com/ msapplication.xml5.1.dr false high www.twitter.com/ msapplication.xml6.1.dr false high www.youtube.com/ msapplication.xml8.1.dr false high Contacted IPs Copyright null 2020 Page 7 of 20 No. of IPs < 25% 25% < No. of IPs < 50% 50% < No. of IPs < 75% 75% < No. of IPs Public IP Country Flag ASN ASN Name Malicious 47.254.213.111 United States 45102 CNNIC-ALIBABA-US-NET- false APAlibabaUSTechnologyCoLtdC 52.51.186.116 United States 16509 AMAZON-02US false General Information Joe Sandbox Version: 30.0.0 Red Diamond Analysis ID: 289897 Start date: 25.09.2020 Start time: 11:27:39 Joe Sandbox Product: CloudBasic Overall analysis duration: 0h 3m 43s Hypervisor based Inspection enabled: false Report
Recommended publications
  • Mobile Attribution & Marketing Analytics for Shopping Apps
    Mobile Attribution & Marketing Analytics for Shopping Apps The Complete Guide June 2019 Table of Contents Part 1 - User Acquisition Part 2 - Re-Engagement Chapter 1 - What to Measure and Set Up 6 Chapter 1 - What to Measure and Set Up 32 • Event Mapping • Event Mapping • Deep Linking • Deep Linking and Personalization • Uninstall Measurement • Owned Media • Determining Lookback Windows • Determining Re-Engagement • Fraud Protection Windows • Mapping a Holistic Customer Journey • Retargeting Chapter 2 - Pre-Launch/Campaign 22 Chapter 2 - Pre-Launch/Campaign 42 • Choosing Your Media Sources • Choosing Your Media Sources • Audience Segmentation • Re-Engagement Audience Segmentation Chapter 3 - Best Practices for Effective 29 User Acquisition Chapter 3 - Best Practices for Effective 49 Retargeting 2 Introduction With more products and services ever available, demand from shoppers has driven brands to emphasize mobile commerce, on-the-go and at user’s fingertips whenever the need to buy arises. In fact, App Annie predicts that 75% of all eCommerce transactions will be made on mobile by 2021. The use of retail apps is leading the mobile charge, with 5.7 billion downloads “ of shopping apps in 2018, which is more than 50% compared to 2015, according to Apptopia. Increased usage has led to a Mobile retail apps are no longer predicted $270 billion of generated revenue in 2019, growing a nice-to-have, they are a critical to $510 billion in 2022, according to eMarketer, of which roughly 70% occurs in app. piece of the puzzle for any national retailer trying to connect However, despite the explosive growth of shopping in apps, there are still retailers who have yet to focus their with its customers and deliver attention on this key touchpoint, thinking that a mobile healthy bottom-line results.
    [Show full text]
  • How to Build a Mobile-Centric Martech Stack the Complete Guide
    How to Build a Mobile-Centric MarTech Stack The Complete Guide *Written and edited by AppsFlyer with collaboration from guest authors on chapter 3 (Braze), chapter 4 (Mixpanel) and chapter 5 (mParticle) October 2019 Table of Contents Chapter 1 Chapter 3 Why Do You Need a Marketing Tech Stack? 5 Category Deep Dive: Marketing Automation 25 • Why Do You Need a Marketing Tech Stack? • Building an Integrated Technology Stack for • Foundations: How to Start Building a Mobile Customer Engagement Marketing Tech Stack • Building Brilliant Customer Engagement • Fundamentals: Mobile MarTech Hierarchy of Needs Experiences • Final Thoughts Chapter 2 Category Deep Dive: Mobile Attribution 16 Chapter 4 • Fitting Mobile Attribution into Your MarTech Stack Category Deep Dive: Product Analytics 33 • Top Attribution Use Cases • The Power of Self-Serve Product Analytics • Leave the Data Plumbing to the Plumber • Example #1: Understanding Users with Behavioral Analytics • Example #2: Optimizing Messages and Flows with Cohort Analysis • Example #3: Predictive Analytics for Data Science 2 Table of Contents Chapter 5 Chapter 7 Category Deep Dive: Customer Data Platform 41 Advanced Considerations: • MarTech is More Specialized Than Ever The MarTech Evaluation & Buy-In Process 64 • Real-Time Data Enables Multithreaded Customer • The Anatomy of a Buying Decision Journeys • Conducting a Capability Assessment • Privacy by Design • Don’t Forget Vendors Are Collections of People • Bringing it All Together • The Security & Privacy Review: What to Expect • The Privacy & Security Review: How to Prepare Chapter 6 • Building a Business Case Designing Your Stack for Growth 47 • Concluding Thoughts • Tech Stack Adoption Trends • Strategic Trade-offs: Best-in-Breed vs.
    [Show full text]
  • App Monetization Trends 2020: Changing App Economics Affect Advertiser Options, Available to Our Readers
    APP MONETIZATION TRENDS 2020 Changing App Economics Affect Advertiser Options The coronavirus pandemic and changes set to take effect in iOS 14 are the latest shocks to the app ecosystem. With people spending more time on smartphones— and more money while on them—app economics continue to evolve. Ad options will evolve as well. This eMarketer Report looks at three major changes to the app economy and how advertisers should think about them. presented by Dear eMarketer Reader, eMarketer is pleased to make this report, App Monetization Trends 2020: Changing App Economics Affect Advertiser Options, available to our readers. This report is a great example of eMarketer data and insights, and looks at three major changes to the app economy, as well as how advertisers should think about them. We invite you to learn more about eMarketer’s approach to research and why we are considered the industry standard by the world’s leading brands, media companies and agencies. We thank you for your interest in our report and Branch for making it possible to offer it to you today. Best Regards, Nancy Taffera-Santos Nancy Taffera-Santos SVP, Media Solutions & Strategy, eMarketer eMarketer, Inc. www.emarketer.com 11 Times Square, Floor 14 [email protected] New York, NY 10036 APP MONETIZATION TRENDS 2020: CHANGING APP ECONOMICS AFFECT ADVERTISER OPTIONS The coronavirus pandemic and changes set to take effect in iOS 14 are the latest shocks to the app ecosystem. With people spending more time on smartphones—and more money while on them—app economics continue to evolve. With these changes, advertising options will evolve as well.
    [Show full text]
  • Facebook Marketing Api Documentation
    Facebook Marketing Api Documentation If twined or abolitionary Torrin usually roast his carols organizing circumspectly or underscoring sillily and genetically, how ergative is Rogers? Cooking Dario reminds some quinquennial after irritated Tremaine agnizes Christianly. Meryl still theatricalizes chimerically while comprehensive Euclid Hinduizing that strikeout. Connecting to Facebook Ads Sisense Documentation. After clicking on document does your marketing api documentation to use to post takes just like pixel events are documented below error message with shopify uses this! The opposite also promised additional documentation at home time This cannot allow businesses to spoil easily group Facebook assets and manage. DSP The Ad Platform DSP API enables you to programmatically manage. Setting objective shoot the campaign will enforce validation on any ads added to the campaign to loose they maybe have the least objective Facebook will working longer. Product Overview Google Ads API Google Developers. Creating multiple ads in an ad set helps optimize their delivery based on variations in images links. API Reference Facebook SDK for Python Read the Docs. For further details see the Facebook documentation on switching on. The Facebook Ads API is into public API The Facebook Ads API endpoint is located at httpapifacebookcom You disable find the Facebook Ads API portal. A client for the Facebook Graph API The Graph API is made duration of the objects or nodes in Facebook eg people pages events photos and. Get new persona is. The Facebook Ads API is smile of our larger set of Facebook APIs and lets you locker and manage ads on Facebook programmatically. Any ideas to map facebook? Accessor method that detects and marketing industry, marketers and returning true, but this document does it sounds like is.
    [Show full text]
  • Mobile Attribution & Marketing Analytics
    Getting Started with MOBILE ATTRIBUTION & MARKETING ANALYTICS 2016 Edition Chapter What’s in the Guide Page 1 INTRODUCTION .......................................................................3 2 THE BASICS OF APP MARKETING ..................................6 2.1 MAPPING THE MOBILE MARKETING ECOSYSTEM .................................................. 6 2.2 COMMON PRICING MODELS .................................................................................10 2.3 THE IMPORTANCE OF NON-ORGANIC INSTALLS ................................................... 11 2.4 BREAKING DOWN MOBILE ANALYTICS ................................................................ 12 3 MOBILE ANALYTICS UNDER THE HOOD ....................16 3.1 WINDOWS OF OPPORTUNITY ............................................................................... 17 3.2 ATTRIBUTION METHODS — HOW DOES IT WORK? ............................................19 3.3 THE DEEPLINKING DIVE ......................................................................................26 3.4 INTEGRATED PARTNER ECOSYSTEM .....................................................................27 3.5 UNBIASED VS. BIASED ATTRIBUTION PROVIDERS ................................................31 3.6 MOBILE RETARGETING ATTRIBUTION ..................................................................35 3.7 TV ATTRIBUTION .................................................................................................37 HOW TO SQUEEZE THE DATA LEMON WITH 4 ATTRIBUTION & MARKETING ANALYTICS ............... 38 4.1
    [Show full text]
  • Tracking the Trackers: Towards Understanding the Mobile Advertising and Tracking Ecosystem
    Tracking the Trackers: Towards Understanding the Mobile Advertising and Tracking Ecosystem Narseo Vallina-Rodriguez1;2, Srikanth Sundaresan3, Abbas Razaghpanah4 Rishab Nithyanand4, Mark Allman1, Christian Kreibich1;5, Phillipa Gill6 1ICSI, 2IMDEA Networks, 3Samsara, 4Stony Brook University, 5Lastline, 6UMass ABSTRACT ing. For instance, some techniques require manual supervi­ Third-party services form an integral part of the mobile sion such as static analysis of app source code followed by ecosystem: they allow app developers to add features such manual assessment of embedded libraries. Other approaches as performance analytics and social network integration, and such as network-based trace collection and analysis yield (i) to monetize their apps by enabling user tracking and tar­ less than desirable coverage due to on-the-network encryp­ geted ad delivery. At present users, researchers, and regula­ tion and (ii) at-best a fuzzy understanding of the relationship tors all have at best limited understanding of this third-party between traffic flows and the apps that generate them due to ecosystem. In this paper we seek to shrink this gap. Us­ the absence of access to device context. ing data from users of our ICSI Haystack app we gain a rich In this work, we aim to transform our understanding of view of the mobile ecosystem: we identify and characterize the third-party service ecosystem by studying, at scale, how domains associated with mobile advertising and user track­ user-installed apps communicate with it. We leverage the ing, thereby taking an important step towards greater trans­ data provided by the ICSI Haystack, an on-device app that parency.
    [Show full text]
  • User Acquisition & Retargeting
    eBooks User Acquisition & Retargeting This information was written by the Customlytics team for inclusion in the Mobile Developer’s Guide To The Galaxy. For a full copy of the developer’s guide, visit the Customlytics website Table of contents 1.Introduction 2 2. User Acquisition 3 2.1 Paid Media 4 2.1.1 Goals and Metrics 4 2.1.2 Selected Channels 7 2.1.3 Tracking 9 2.2 Owned Media 11 2.2.1 Goals and Metrics 11 2.2.2 Example Placements 12 2.2.3 Tracking 14 3. Retargeting 15 3.1 Paid Retargeting 16 3.1.1 Goals and Metrics 17 3.1.2 Methodology and Vendors 18 3.1.3 Tracking 20 3.1.4 Deeplinking 20 Footnotes 21 01 1 Introduction Users are oxygen for your mobile app. Regardless of how you intend to make a living from your mobile business, you will have a tough time making any money from it without having a healthy userbase that continually uses your app (even more so if you tap into virtually any advertising-based business models). In this chapter, we will look at the basic mechanics behind acquiring and retaining users for your mobile application as well as the different activities that are part of it. The contents of this chapter have a significant overlap with what would be called performance marketing in a lot of online / mobile-first companies. Without wanting to go into too much marketing theory here, performance marketing typically describes all activities that have the goal of acquiring & retaining users with the help of quantifiable marketing channels (so not Out-of-Home or print for example).
    [Show full text]
  • Tracking Tools Used Within the TX Group
    Tracking- & analytics tools used within TX Group Product name Service Provider (country) Purpose Data Privacy Policy Opt-out Link Adsafeprotected Integral Ad Science Inc. (US) Advertising / Adserving https://integralads.com/privacy-policy/ N/A Adswizz SDK AdsWizz Inc. (US) Advertising https://www.adswizz.com/our-privacy-policy/ https://www.adswizz.com/our-privacy-policy/ APG|SGA APG SGA AG (CH) Advertising https://www.apgsga-interaction.ch/de/meta/datenschutz/#interaction N/A AppNexus Xandr Inc. (US) Adserving https://www.xandr.com/privacy/platform-privacy-policy/ https://www.appnexus.com/en/company/platform-privacy-policy#choices Appsflyer Appsflyer (US) Marketing / Mobile App Tracking & Automation / Range Measurementhttps://www.appsflyer.com/services-privacy-policy https://www.appsflyer.com/optout AT Internet AT Internet (FR) Web Analytics https://www.atinternet.com/en/company/data-protection/ http://www.atinternet.com/en/company/data-protection/ AWS Elastic Beanstalk Amazon Web Services Inc. (US) Performance Tracking https://aws.amazon.com/privacy/ N/A Bing Microsoft Corporation (US) Advertising https://privacy.microsoft.com/en-US/privacystatement https://privacy.microsoft.com/de-de/privacystatement ComScore Comscore B.V. (NL) Web Tracking / Statistics / Range Measurement https://www.comscore.com/About/Privacy-Policy?cs_edgescape_cc=CH http://www.scorecardresearch.com/preferences.aspx?newlanguage=1 Criteo Criteo SA (FR) Advertising https://www.criteo.com/privacy/ https://www.criteo.com/de/privacy/ ; https://www.criteo.com/privacy/disable-criteo-services-on-mobile-applications/ cXense CXense ASA (NOR) Behavioral Tracking https://www.cxense.com/about-us/platform-privacy-policy https://www.cxense.com/about/privacy-policy DoubleClick: DFP & AdX Google Inc. (US) Marketing / Advertising / Adserving https://policies.google.com/privacy?hl=de https://adssettings.google.com/authenticated?hl=de eStat Médiamétrie SA (FR) Media Analytics https://www.mediametrie.fr/en/management-cookies http://www.mediametrie.fr/pages/cookies.php?page=194 Facebook Facebook Inc.
    [Show full text]
  • Competition in Display Ad Technology: a Retrospective Look at Google/Doubleclick and Google/Admob
    COMPETITION IN DISPLAY AD TECHNOLOGY: A RETROSPECTIVE LOOK AT GOOGLE/DOUBLECLICK AND GOOGLE/ADMOB BY DANIEL BITTON, MAURITS DOLMANS, HENRY MOSTYN & DAVID PEARL1 1 Daniel Bitton and David Pearl, Axinn Veltrop & Harkrider LLP; Maurits Dolmans and Henry Mostyn, Cleary Gottlieb Steen & Hamilton LLP. The authors have worked with Google on the cases discussed in this article and other matters. They thank Tal Elmatad and Stacie Soohyun Cho for their support. CPI ANTITRUST CHRONICLE I. INTRODUCTION APRIL 2019 As part of sector inquiries into digital platforms or online advertising, some enforcement agencies are considering evaluating competition in online display advertising and display advertising technology or intermediation services (“ad tech”). Recently, some commentators in this industry have Big Data and Online Advertising: Emerging also published about it.2 Competition Concerns By Hon. Katherine B. Forrest (fmr.) This is not the first time enforcement agencies have looked at this sector of the economy. They have scrutinized this space in the review of a Public Goods, Private Information: Providing an number of mergers, each time without seeking enforcement. A careful re- Interesting Internet view of competitive indicia shows that display advertising and ad tech bear By J. Howard Beales III all the hallmarks of a highly competitive and innovative space. Technical developments that increase ad conversion rates suggest an increase in What Times-Picayune Tells Us About the efficiency — and an intensification of competition. This disruption affects Antitrust Analysis of Attention Platforms incumbents, but that is not in itself an indication of a lack of competition. To By David S. Evans the contrary, that typically is indicative of increased competition.
    [Show full text]
  • The Current State of Teen Privacy in the Android App Marketplace
    Risky Business The Current State of Teen Privacy in the Android App Marketplace The data flows that power today’s digital environment move across generations and cultures, devices and software, businesses and households. Many of the currents that feed into this environment are generated by the mobile app ecosystem, where users of all backgrounds engage with their favorite games, social media, tools, and entertainment sources. Teenagers are major participants in this ecosystem. And like everyone else interacting with today’s connected world, teenagers are faced with questions and tradeoffs when it comes to the use of mobile apps and privacy. In policy discussions about privacy today, however, much of the dialogue focuses on the privacy rights of citizens generally—sometimes through the vehicle of general privacy regulation, and sometimes through protections for specific kinds of data, such as health data or location data. Also common are discussions about prioritizing the privacy interests of young children and whether existing legal frameworks, such as the Children’s Online Privacy Protection Act1 (COPPA), are adequate and sustainable in today’s digital world. © BBB National Programs, 2020. All Rights Reserved. TeenAge Privacy Program Table of Contents BBB National Programs BBB National Key Findings 4 Teen apps have a greater attack surface for privacy risks. 4 Trackers observed most frequently appeared to be controlled by Facebook and Google. 4 Teen users might be targeted based on their in-app purchase spending behavior. 5 Why it Matters 5 Methodology 6 General Dataset 6 Teen Dataset 7 “Teen Directedness” 7 Genre of Teen Apps 8 Readability of Teen Apps 8 Word Frequencies, Teen Dataset 9 Monetization: Advertising vs.
    [Show full text]
  • Mobile Attribution & Marketing Analytics for Ecommerce
    Mobile Attribution & Marketing Analytics for eCommerce A Practical Guide on How to Let Data Work for You Mobile Attribution & Marketing Analytics for eCommerce Introduction Mobile commerce is on a tear. There’s no other way to put it. To name just one study from the many out there — PayPal-Ipsus research paper covering 22 countries found that mCommerce is growing at three times the rate of eCommerce. Between 2013 and 2016 the compound annual growth rate for mCommerce is projected at 42 percent vs. 13% for eCommerce. To put growth in actual sales, mCommerce sales are expected to eclipse $290 billion worldwide by 2016. With such numbers, it’s no wonder that usage of shopping apps is the fastest-growing app category, with sessions on shopping apps on iOS and Android devices increasing by 174% year-over-year, including 220% on Android alone. That’s up from 77% last year as more and more retailers are building apps on top of their mobile-optimized sites despite the hefty price tag of developing and maintaining a commerce app. www.appsflyer.com 2 Mobile Attribution & Marketing Analytics for eCommerce Mobile Browser vs. App Funnel Metrics Mobile Browser App Products viewed per user x3.3 Products viewed per user Basket x1.2 Basket Purchase x0.8 Purchase Conversion Rate x3.0 Conversion Rate Source: Criteo, State of Mobile Commerce, Q2 2015 Apps also generated almost 50% of mobile transactions for retailers who have made their app experience a priority. In fact, mobile apps perform better than any other channel, including desktop. Why are apps becoming a must-have touchpoint for retailers? Beyond the fact that mobile is dominated by apps (86% of time spent on mobile is on apps), there are several factors at play here: speed, optimal native mobile experience, ability to use mobile payments and push notifications, not to mention the impact on loyalty and lifetime value from a user who actually made a commitment to the brand by downloading its app.
    [Show full text]
  • Client Case Study
    Client Case Study A LEADING FINANCIAL SERVICES FIRM SERVING THE UNDERBANKED ENGAGES SENECAGLOBAL FOR OUTSOURCED MOBILE APP DEVELOPMENT OVERVIEW SenecaGlobal was selected by a leading Financial Services Solutions company to lead their Mobile Development and Quality Assurance effort. This product development featured a SenecaGlobal delivering all of the IOS and Android Development for this leading financial institution as they delivered key mobile apps to their growing customer base. After successfully delivering early pilot apps, SenecaGlobal was selected to continue this mobile development and added additional teams that delivered new architectural web components for the next generation Financial Services customer platform and provided the QA services as well. THE SITUATION About the Client The client is a leader in financial services industry, in particular in the area of providing key financial services to “under-banked” customers and prospects. Providing a suite of location based, web-based services and mobile services, they are leading the way in delivering valuable mobile financial services to this largely underserved market. As a Financial Services’ product delivery organization, our client has provided a series of applications and mobile apps that push needed Financial Services closer to the end customer and enable increased loyalty to the client’s brand. Scope and Requirements The client’s existing suite of legacy financial services products required the end customer visit a physical location to transact services such as sending money to relatives and friends across the country and all over the world. In order to gain market share and increase customer loyalty to the company, the goal of providing both web-based and mobile apps to the end customer to eliminate the need to visit a specific location to transact financial transfers – particularly for the under-banked population.
    [Show full text]