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D24/D6.4 Second Open Workshop Proceedings

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This is the deliverable for the second wombat open workshop, BADGERS, that took place within the EuroSys 2011 conference on April 10 in Salzburg (Austria). In this document we discuss the preparation of the second workshop, our expectations vs. feedback and impressions we collected by authors and attenders. Proceedings are included.


FP7-ICT-216026-Wombat_WP6_D24_V01_Second-Open-Workshop-Proceedings-BADGERS-2011.pdf

D23/D5.3 Early Warning System: Experimental report

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A large part of Workpackage 5 concerns the Early Warning System functionality. This deliverable offers a report of the experiments carried out as part of the effort to create the Early Warning System. Several specialized alerting systems are presented, including FIRE, Exposure, BANOMAD and HoneyBuddy myIMhoneypot


FP7-ICT-216026-Wombat_WP5_D23_V01_Early-warning-system-experimental-report.pdf

D22/D5.2 Root Causes Analysis: Experimental Report

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This deliverable offers an extensive report of all experiments carried out with respect to root cause analysis techniques. This final deliverable for Workpackage 5 (Threats Intelligence ) builds upon D12 (D5.1 - Technical Survey on Root Cause Analysis) and benefits from the modifications made to the various software modules developed in WP4, following up the experimental feedback.
The R&D efforts carried out in WP5 with respect to root cause analysis have produced a novel framework for attack attribution called triage. This framework has been successfully applied to various wombat datasets to perform intelligence analyses by taking advantage of several structural and contextual features of the data sets developed by the different partners. These experiments enabled us to get insights into the underlying root phenomena that have likely caused many security events observed by sensors deployed by wombat partners.
In this deliverable, we provide an in-depth description of experimental results obtained with triage, in particular with respect to (i) the analysis of Rogue AV campaigns (based on  HARMUR data), and (ii) the analysis of different malware variants attributed to the Allaple malware family (based on data from SGNET, VirusTotal and Anubis).
Finally, we describe another experiment performed on a large spam data set obtained from Symantec.Cloud (formerly MessageLabs), for which triage was successfully used to analyze spam botnets and their ecosystem, i.e., how those botnets are used by spammers to organize and coordinate their spam campaigns. Thanks to this application, we are considering a possible technology transfer of triage to Symantec.Cloud, who is interested in carrying out regular intelligence analyses of their spam data sets, and may ralso consider the integration of triage to their Skeptic ○ spam filtering technology.



FP7-ICT-216026-Wombat_WP5_D22_V01_Root-Cause-Analysis-Experimental-report.pdf

D21/D4.7 Consolidated report with evaluation results

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This is the final deliverable for Workpackage 4 within the wombat project. In this document we discuss the final extensions and improvements to our data collection and analysis techniques that were implemented as part of wombat. Furthermore, we present some additional results obtained from the analysis of data collected within wombat.


FP7-ICT-216026-Wombat_WP4_D21_V01_Consolidated-reports-with-evaluation-results.pdf

The Wombat API (WAPI) is now available on sourceforge

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WAPI, or WOMBAT API, is a SOAP-based API built in the context of the project to facilitate the remote access and exploration of security-related datasets.

The package contains all the essential code to start using the WAPI. The WAPI represents an attempt to tackle two main challenges for security data providers:

- Many of the data access primitives are not easily scriptable. Many data sources provide web-based interfaces that, while easily accessible by human operators, are not convenient for automated analysis.

- The interfaces for security datasets are very diverse in structure and methodology. The analyst who wants to take advantage of multiple data sources to perform correlations among them is thus forced to implement ad-hoc plugins and parsers for each data feed. This process is not necessarily a simple task, and requires the analyst to fully understand, for example, the schema of the SQL database provided by the data owner.



You can find the package on sourceforge : http://sourceforge.net/projects/wombat-api/


More information and details on WAPI are available in the deliverable D10/D6.3.

Wombat Deliverable D18/D4.6 Final description of contextual features

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The objective of Workpackage 4 is to develop techniques to characterize the malicious
code that is collected in the previous workpackage. The main idea is to enrich the
collected code thanks to metadata that might reveal insights into the origin of the code
and the intentions of those that created, released or used it.
This deliverable is an extension of D15 (D4.5), and provides a final description of the
contextual features collected within the wombat consortium. Furthermore, it presents
initial results, statistics, and insights obtained by analyzing the collected contextual
features.

FP7-ICT-216026-Wombat_WP4-D18_V01_Final-Contextual-features.pdf

Hispasec announces participation to WOMBAT on its blog

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