16,010 research outputs found
The zombies strike back: Towards client-side beef detection
A web browser is an application that comes bundled with every consumer operating system, including both desktop and mobile platforms. A modern web browser is complex software that has access to system-level features, includes various plugins and requires the availability of an Internet connection. Like any multifaceted software products, web browsers are prone to numerous vulnerabilities. Exploitation of these vulnerabilities can result in destructive consequences ranging from identity theft to network infrastructure damage. BeEF, the Browser Exploitation Framework, allows taking advantage of these vulnerabilities to launch a diverse range of readily available attacks from within the browser context. Existing defensive approaches aimed at hardening network perimeters and detecting common threats based on traffic analysis have not been found successful in the context of BeEF detection. This paper presents a proof-of-concept approach to BeEF detection in its own operating environment β the web browser β based on global context monitoring, abstract syntax tree fingerprinting and real-time network traffic analysis
Traffic measurement and analysis
Measurement and analysis of real traffic is important to gain knowledge
about the characteristics of the traffic. Without measurement, it is
impossible to build realistic traffic models. It is recent that data
traffic was found to have self-similar properties. In this thesis work
traffic captured on the network at SICS and on the Supernet, is shown to
have this fractal-like behaviour. The traffic is also examined with
respect to which protocols and packet sizes are present and in what
proportions. In the SICS trace most packets are small, TCP is shown to be
the predominant transport protocol and NNTP the most common application.
In contrast to this, large UDP packets sent between not well-known ports
dominates the Supernet traffic. Finally, characteristics of the client
side of the WWW traffic are examined more closely. In order to extract
useful information from the packet trace, web browsers use of TCP and HTTP
is investigated including new features in HTTP/1.1 such as persistent
connections and pipelining. Empirical probability distributions are
derived describing session lengths, time between user clicks and the
amount of data transferred due to a single user click. These probability
distributions make up a simple model of WWW-sessions
The zombies strike back: Towards client-side BeEFdetection
A web browser is an application that comes bundled with every consumer operating system, including both desktop and mobile platforms. A modern web browser is complex software that has access to system-level features, includes various plugins and requires the availability of an Internet connection. Like any multifaceted software products, web browsers are prone to numerous vulnerabilities. Exploitation of these vulnerabilities can result in destructive consequences ranging from identity theft to network infrastructure damage. BeEF, the Browser Exploitation Framework, allows taking advantage of these vulnerabilities to launch a diverse range of readily available attacks from within the browser context. Existing defensive approaches aimed at hardening network perimeters and detecting common threats based on traffic analysis have not been found successful in the context of BeEF detection. This paper presents a proof-of-concept approach to BeEF detection in its own operating environment β the web browser β based on global context monitoring, abstract syntax tree fingerprinting and real-time network traffic analysis
Tracking Users across the Web via TLS Session Resumption
User tracking on the Internet can come in various forms, e.g., via cookies or
by fingerprinting web browsers. A technique that got less attention so far is
user tracking based on TLS and specifically based on the TLS session resumption
mechanism. To the best of our knowledge, we are the first that investigate the
applicability of TLS session resumption for user tracking. For that, we
evaluated the configuration of 48 popular browsers and one million of the most
popular websites. Moreover, we present a so-called prolongation attack, which
allows extending the tracking period beyond the lifetime of the session
resumption mechanism. To show that under the observed browser configurations
tracking via TLS session resumptions is feasible, we also looked into DNS data
to understand the longest consecutive tracking period for a user by a
particular website. Our results indicate that with the standard setting of the
session resumption lifetime in many current browsers, the average user can be
tracked for up to eight days. With a session resumption lifetime of seven days,
as recommended upper limit in the draft for TLS version 1.3, 65% of all users
in our dataset can be tracked permanently.Comment: 11 page
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