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Sourcefire Launches
Open Source Razorback - Framework for Multi-Vendor Threat Detection and
Protection
July 30, 2010
The
Razorback is an open source framework designed to deliver deep
inspection capabilities for combating today's most complex threats. In
addition, Razorback has the ability to link together an organization's
detection investments and maximize their effectiveness -- providing
greater visibility and intelligence into the threats detected by a
variety of security solutions. Developed to help coordinate the response
against Advanced Persistent Threats (APT), Razorback enables users to
easily collect, analyze and store threat data from disparate
technologies, so that they can implement customized enterprise- and
threat-specific detection and remediation.
"The fear attributed to the common computer security breach has been
elevated by the concept of an adaptive persistent adversary (APA) and
the potential for multiple advanced persistent threat (APT) vectors,"
explains Andrew Hay, Senior Analyst at The 451 Group. "We are pleased to
see this evolutionary step in the right direction, and hope it is the
first of many."
Razorback's goal is to act as an overlay solution and deliver
centralized correlation, analysis and action by coordinating
Intelligence Driven Response (IDR) processes using custom built and
existing security tools (anti-virus, IDS, gateways, email, etc.). IDR
goes beyond traditional incident response. It allows users to drive the
information learned about specific attackers back into their security
infrastructure for a truly customizable response to human adversaries.
Razorback provides deep analysis and reporting by storing, in full,
every piece of data identified that could indicate a compromise or
attack and specifically highlights the components of that data which
cause the system to trigger an alert. Additionally, Razorback enables
targeted forensics information on common attack vectors.
"Open source is at the core of everything Sourcefire does, and Razorback
is the latest innovation providing users with the ability to protect
themselves from today's sophisticated threats," said Martin Roesch,
Founder and CTO of Sourcefire and Creator of Snort. "Sourcefire is known
for pushing the detection envelope and Razorback's near-real time
detection and analysis engine delivers a timely solution for addressing
client-side malware and attacks. We leveraged this knowledge to provide
a framework that can tie together disparate security technologies and
convert intelligence gathered on attacker methodology into detection and
remediation capabilities."
The
innovative Razorback framework performs detection in near-real time (in
terms of seconds), allowing for in-line blocking on "store and forward"
services, such as email services or web proxies, and providing timely
alerts in the event of an attack. It also provides enterprises with the
ability to convert intelligence gathered on attacker methodology into
detection capabilities, enabling them to rapidly develop and protect
against targeted threats or Zero-Day vulnerabilities.
"Razorback was designed to address the current challenges of today's
threat landscape where attackers are specifically creating attacks to
avoid off the shelf tools and technologies," said Matt Watchinski,
Senior Director of the Sourcefire Vulnerability Research Team (VRT).
"The power is in combining the intelligence of an organization's
security infrastructure with fast and detailed analysis. By providing
advanced detection capabilities for uncovering highly obfuscated,
difficult-to-detect attacks along with detailed output, Razorback gives
response teams a head start on analyzing attacks."
A simple interface allows enterprises to integrate and extend
functionality quickly and easily. Sourcefire will continue to develop
additional capabilities and publish data collectors, detection engines,
analysis software and output handlers to maximize the value of Razorback
and encourage innovation from the open source community. Like other open
source technologies, Razorback is available at no charge. |