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Ivan Burke and Renier van Heerden According to (Google Gadgets API, 2009), Google’s makeRequest() function does not validate the existence of a page prior to sending the HTTP request to remote server. This would mean malicious coders can use Google Gadgets to probe websites for config, admin or script files stored in un-listable directories of web pages. This could also be used to create a large amount of traffic towards the web server by generating makeRequest() calls for none-existent pages on the server. This type of probing and traffic generation could also be created by pure JavaScript without the use of Google Gadget’s makeRequest() function, but the benefit of using Google Gadget API is that the remote server logs will only contain the IP address of Google Gadget application servers, as illustrated by Figure 4: Remote server log. Figure 4: Remote server log Google provides a cache features for all its gadgets to reduce server loads (Google Gadgets API, 2009). This cache server saves a copy of the remote content on a local server for faster retrieval. By default Google gadgets get cached for approximately one hour. Due to the requirement of some gadget developers to have shortened cache timing due to dynamic nature of their gadgets, Google provided developers with the capability to set the cache interval. According to Google Gadgets API (2009), it is possible to set the interval to zero seconds. Google Gadget API does not prevent developers from setting cache interval to zero but warns against setting cache interval to zero as it might overload remote server. Thus we have discovered two means of disrupting remote server. Either by generating near infinite fictitious web pages from a server, or by fetching the same page recursively and setting the refresh interval to zero seconds. 3.2 Retrieving user data Clients using the Cloud uses API calls to communicated and execute commands on the Cloud, through its Service-Orientated Architecture (SOA). In general, cloud computing units are heavily compartmentalized to insure no data can be leaked between clients. Unfortunately the components that makeup the Cloud infrastructure, such as CPU, Ram and GPU, where not specifically designed for isolation. (Hubbard et al., 2010) Techniques to exploit this weakness have been demonstrated by Joanna Rutkowska (Rutkowska, 2008) and Kostya Kortchinsky (Kortchinsky, 2009). In our specific case we do not target data on the Cloud specifically we merely use the Cloud as a channel to pass and receive message. Google gadget API is a collection of JavaScript libraries; as such they require JavaScript to be enabled to utilize its capability. JavaScript can be used to determine user browser history and browser information. Cabri (2007), created a simplistic JavaScript to determine if a page have been visited before. Figure 5: Sites visited script, contains the script he used. By using this script to look up banking sites or social media sites one can determine which banking and social media services the user have visited. By combining this script with Google gadget makeRequest(), one can determine if the user has auto login enabled for certain social media sites. For example: to test if the user has auto-logon enabled on Facebook one can request http://www.facebook.com/home.php. If the content is the home page it would mean the browser automatically logged the user in or the user has an active Facebook session. If the login page is returned it would mean the user’s session has expired or that auto-logon is disabled. Keep in mind that makeRequest() does not display the page, it merely returns its contents to the callback function specified by the makeRequest() call. This means that the user does not need to get any visual cues of gadget activity. The Botnet designer can choose whether to scrape the resulting homepage for more data or to crawl the social network site for more data or to just report the information back to Botherder for future use. 36
Ivan Burke and Renier van Heerden Figure 5: Sites visited script Hashemian (2005), created a PHP script that can be accessed via JavaScript to perform IP resolution and reverse DNS lookups for visitors to sites. This provides more info on the location and domain usage of gadget user. Google’s makeRequest() function is also capable of performing a POST request. By combining these JavaScript information gathering techniques and posting capability of Google’s makeRequest() one can report back gathered information to Botherder. This is just some of the data that can be gathered using JavaScript and by no means covers all the data that can be harvested by JavaScript but for the purposes of this Proof of Concept they are sufficient. 3.3 Adsense abuse Advertising companies offering website designers money for serving up adverts on their sites. By requesting pages using makeRequest() one can fool most Impression Based advertising models into counting the page fetch as an impression hence generating revenue for the website designer. Unique IP addresses have a higher weight on Advanced Impression Based advertising sites. Because Google Gadget Application servers make the request, only a select few IP addresses will in effect be displayed in advertising company logs. Hence, Adsense abuse is not really effective with Google Gadget API but it does guarantees a steady and constant number of visits to a site. 3.4 Obfuscating source of attack Thus far it has already been stated that if the Google Feedfetcher is used to fetch remote data only the Google Gadget Domain Server's IP will be logged in the remote servers access logs. This is already an attempt to obfuscate the source of the attack. Unfortunately for Google gadgets to work and to be published Google needs to be able to access the gadget source code. This means that anyone wishing to add the gadget would also be able to fetch the source code and could possibly deduce that it executes malicious commands. A simple way of overcoming this obstacle is obfuscate the source code. By encoding the JavaScript source code in base64. Wang, (2009) developed a web tool specifically designed to obfuscate JavaScript. Figure 6 illustrates the result of obfuscating the hasLinkBeenVisited() function. 37
Page 1 and 2: The Proceedings of the 6th Internat
Page 3 and 4: Contents Paper Title Author(s) Page
Page 5 and 6: Preface These Proceedings are the w
Page 7 and 8: Biographies of contributing authors
Page 9 and 10: Department of Computer Science, IQR
Page 11 and 12: Using the Longest Common Substring
Page 13 and 14: Jaime Acosta Some techniques that u
Page 15 and 16: Jaime Acosta assigned by an anti-vi
Page 17 and 18: Jaime Acosta Cormen, T.H., Leiserso
Page 19 and 20: Hind Al Falasi and Liren Zhang tran
Page 21 and 22: Hind Al Falasi and Liren Zhang ther
Page 23 and 24: Hind Al Falasi and Liren Zhang the
Page 25 and 26: Edwin Leigh Armistead and Thomas Mu
Page 27 and 28: Deception Operations Security (OPS
Page 33 and 34: The Uses and Limits of Game Theory
Page 35 and 36: 3. Limits to using game theory 3.1
Page 37 and 38: Merritt Baer Effective cyberintrusi
Page 39 and 40: Merritt Baer 1.5), there seems to b
Page 41 and 42: Merritt Baer Report of the Defense
Page 43 and 44: Ivan Burke and Renier van Heerden F
Page 45: Ivan Burke and Renier van Heerden a
Page 53 and 54: Marco Carvalho et al. systems start
Page 55 and 56: Marco Carvalho et al. Benatallah, 2
Page 57 and 58: Marco Carvalho et al. management la
Page 59 and 60: Marco Carvalho et al. Figure 4: Sta
Page 61 and 62: Marco Carvalho et al. Sorrels, D.,
Page 63 and 64: Manoj Cherukuri and Srinivas Mukkam
Page 79 and 80: Mecealus Cronkrite et al. to see bo
Page 81 and 82: Mecealus Cronkrite et al. trivial.
Page 83 and 84: Mecealus Cronkrite et al. socially
Page 85 and 86: Mecealus Cronkrite et al. The views
Page 87 and 88: Vincent Garramone and Daniel Likari
Page 95 and 96: Stephen Groat et al. Sections 4 and
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Stephen Groat et al. probability fo
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Stephen Groat et al. host. In this
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Stephen Groat et al. changing addre
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Marthie Grobler et al. leadership,
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Marthie Grobler et al. apply to sta
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Marthie Grobler et al. 6. Working t
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Cyber Strategy and the Law of Armed
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Ulf Haeussler Alliance and Allies r
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Ulf Haeussler following the invocat
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Ulf Haeussler NCSA (2009) NCSA Supp
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Karim Hamza and Van Dalen of respon
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Karim Hamza and Van Dalen From a mi
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Karim Hamza and Van Dalen productiv
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Intelligence-Driven Computer Networ
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Eric Hutchins et al. of defensive a
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Eric Hutchins et al. Defenders can
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Eric Hutchins et al. Equally as imp
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Eric Hutchins et al. X-Mailer: Yaho
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Eric Hutchins et al. Received: (qma
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Eric Hutchins et al. U.S.-China Eco
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Saara Jantunen and Aki-Mauri Huhtin
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Brian Jewell and Justin Beaver In t
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Brian Jewell and Justin Beaver Figu
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4. Evaluation Brian Jewell and Just
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Brian Jewell and Justin Beaver othe
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Detection of YASS Using Calibration
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Kesav Kancherla and Srinivas Mukkam
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M M M Su−2 Sv ∑∑ u= 1 v= 1 h(
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5.2 ROC curves Kesav Kancherla and
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Developing a Knowledge System for I
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Louise Leenen et al. We distinction
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Louise Leenen et al. There is growi
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3.1 Needs analysis Louise Leenen et
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Louise Leenen et al. Kroenke, D.M.
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Jose Mas y Rubi et al. As we can se
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Figure 2: CALEA forensic model (Pel
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Jose Mas y Rubi et al. Table 2: Com
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Jose Mas y Rubi et al. Another pend
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Tree of Objectives Acknowledgements
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Secure Proactive Recovery - a Hardw
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Ruchika Mehresh et al. implementing
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Ruchika Mehresh et al. The coordina
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Ruchika Mehresh et al. multiplicati
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Ruchika Mehresh et al. Table 2: App
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2. Network infiltration detection D
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David Merritt and Barry Mullins on
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David Merritt and Barry Mullins Ess
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David Merritt and Barry Mullins Dev
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Muhammad Naveed Pakistan Computer E
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Muhammad Naveed response could also
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Muhammad Naveed Table 10: Aggressiv
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Muhammad Naveed 2006 Tcp Open Mysql
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Muhammad Naveed 8009 Tcp Open Ajp13
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Muhammad Naveed Austalian Taxation
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Alexandru Nitu world and bring it i
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Alexandru Nitu Article 51 restricts
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Alexandru Nitu As IW strategy and t
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Cyberwarfare and Anonymity Christop
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Christopher Perr attacks again help
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Christopher Perr about the current
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Catch me if you can: Cyber Anonymit
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David Rohret and Michael Kraft reve
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David Rohret and Michael Kraft sary
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Data (Evidence) Removal Shield Davi
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Neutrality in the Context of Cyberw
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Julie Ryan and Daniel Ryan 18th cen
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Julie Ryan and Daniel Ryan “Decla
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Julie Ryan and Daniel Ryan von Glah
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Harm Schotanus et al. In the remain
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Harm Schotanus et al. 2.3.1 Secure
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Harm Schotanus et al. In this setup
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Harm Schotanus et al. the label (by
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Harm Schotanus et al. these aspects
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Maria Semmelrock-Picej et al. they
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Maria Semmelrock-Picej et al. User
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Maria Semmelrock-Picej et al. SPIKE
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Maria Semmelrock-Picej et al. A cl
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Maria Semmelrock-Picej et al. in co
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Maria Semmelrock-Picej et al. In th
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Maria Semmelrock-Picej et al. Fuchs
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Madhu Shankarapani and Srinivas Muk
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Figure 1: UPX packed Trojan Figure
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Trojan.Zb ot- 1342.mal Trojan.Sp y.
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Madhu Shankarapani and Srinivas Muk
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Namosha Veerasamy and Marthie Grobl
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4. Conclusion Namosha Veerasamy and
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Tanya Zlateva et al. Computer Infor
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Tanya Zlateva et al. security and v
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Tanya Zlateva et al. court opinions
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Tanya Zlateva et al. 5. Pedagogy, e
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PhD Research Papers 277
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Shada Alsalamah et al. Level 3 all
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Shada Alsalamah et al. assure the a
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Shada Alsalamah et al. for Health I
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3. Hematology Laboratory System Who
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Shada Alsalamah et al. Pirnejad, H.
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Michael Bilzor a diverse base of U.
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Michael Bilzor In our current exper
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5. Execution monitor theory Michael
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Michael Bilzor design was run in si
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Michael Bilzor over testbench metho
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Evan Dembskey and Elmarie Biermann
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Theoretical Offensive Cyber Militia
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Rain Ottis Last, but not least, it
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Rain Ottis an infantry battalion, w
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Rain Ottis Ottis, R. (2008) “Anal
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Work in Progress Papers 315
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Large-Scale Analysis of Continuous
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References William Acosta Abadi, D.
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Natarajan Vijayarangan top box unit
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Natarajan Vijayarangan The proposed
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6th European Conference - Academic Conferences

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