))
Ben Feinstein & Daniel Peck: CaffeineMonkey: Automated Collection, Detection and Analysis of Malicious JavaScript
Manage episode 152211987 series 1053194
Contenu fourni par Black Hat Briefings, USA 2007 [Video] Presentations from the security conference.. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Black Hat Briefings, USA 2007 [Video] Presentations from the security conference. ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
The web browser is ever increasing in its importance to many organizations. Far from its origin as an application for fetching and rendering HTML, today?s web browser offers an expansive attack surface to exploit. All the major browsers now include full-featured runtime engines for a variety of interpreted scripting languages, including the popular JavaScript. The web experience now depends more than ever on the ability of the browser to dynamically interpret JavaScript on the client.
The authors present a software framework for the automated collection of JavaScript from the wild, the subsequent identification of malicious code, and characteristic analysis of malicious code once identified. Building on the work of several existing client honeypot implementations, our goal is to largely automate the painstaking work of malicious software collection. Our focus is on attacks using JavaScript for obfuscation or exploitation.
The authors will present findings based on the deployment of a distributed network of CaffeineMonkeys. The analysis and conclusions will focus on identifying new in-the-wild obfuscation / evasion techniques and JavaScript browser exploits, quantifying the prevalence and distribution of well-known and newly discovered obfuscation and evasion techniques, as well as quantifying the prevalence and distribution of known and newly discovered JavaScript browser exploits.
The authors will release a previously unpublished JavaScript evasion technique and demonstrate its use in evading a variety of present-day defensive technologies. Where present-day defenses have been demonstrated to be insufficient, the authors will present new ideas for ways mitigate the new threats.
…
continue reading
The authors present a software framework for the automated collection of JavaScript from the wild, the subsequent identification of malicious code, and characteristic analysis of malicious code once identified. Building on the work of several existing client honeypot implementations, our goal is to largely automate the painstaking work of malicious software collection. Our focus is on attacks using JavaScript for obfuscation or exploitation.
The authors will present findings based on the deployment of a distributed network of CaffeineMonkeys. The analysis and conclusions will focus on identifying new in-the-wild obfuscation / evasion techniques and JavaScript browser exploits, quantifying the prevalence and distribution of well-known and newly discovered obfuscation and evasion techniques, as well as quantifying the prevalence and distribution of known and newly discovered JavaScript browser exploits.
The authors will release a previously unpublished JavaScript evasion technique and demonstrate its use in evading a variety of present-day defensive technologies. Where present-day defenses have been demonstrated to be insufficient, the authors will present new ideas for ways mitigate the new threats.
89 episodes
Partager
