Threat Intelligence

8/4/2017
02:15 PM
Dark Reading
Dark Reading
Products and Releases
50%
50%

Perimeterx Raises $23 million to Expand AI Behavioral Threat Platform

The funding will be used to further improve its bot detection technology and expand into automated attack prevention.

SAN MATEO, CA - PerimeterX, a provider of behavior-based threat protection technology for cloud, web and mobile, has secured $23 million in Series B funding to accelerate the development of its bot attack prevention technology. Canaan Partners led the round, with participation from existing investors Vertex Ventures and Data Collective (DCVC). With the funding, PerimeterX will expand in the U.S. and internationally, and broaden its platform into new areas. PerimeterX’s web-based Bot Defender product analyzes billions of events daily and blocks hundreds of millions of bot attacks every day.

All companies operating online today face a growing number of increasingly sophisticated attacks by malicious bots. In 2016, bot activity caused $2.6 billion of losses from account takeovers, $7.2 billion in advertising fraud and $950 million in electronic gift card fraud. In her 2017 Internet Trends Report, Mary Meeker of Kleiner Perkins Caufield Byers noted that in 2016 bot-generated traffic surpassed human-generated traffic on the Internet.

"Next-generation automated web attacks today threaten the integrity of the web by impersonating humans and abusing business logic rather than breaching systems, and they even harm the integrity of our political system by spreading fake news," said Omri Iluz, CEO of PerimeterX. "With cutting-edge artificial intelligence and machine learning, the PerimeterX platform technology is purpose-built to address this problem head-on by detecting and blocking the most advanced malicious bots in real-time, at any scale."

Modern bots attempt to execute a variety of damaging acts such as account takeover, web scraping, carding, checkout abuse and online fraud. The latest generation of bots attempt to impersonate real users and real system behaviors. As a result, they can easily evade detection by legacy tools such as Web Application Firewalls.

"Malicious bot attacks hurt a company’s bottom line and erode consumer trust in a brand. Current strategies are not proving effective," said Joydeep Bhattacharyya, partner at Canaan Partners, who joined the company’s board as part of the Series B financing. "PerimeterX’s technology not only stops malicious bots in their tracks – it does so at consumer scale."

To separate the actions of bots from those of normal users, PerimeterX uses artifical intelligence and machine learning to identify behaviors that are unlikely to represent human actions – for example, landing a mouse directly on a button rather than scrolling towards it up or down the screen. As PerimeterX gathers more information about how people interact with a site, it builds more accurate models of what constitutes human versus bot behavior. This behavior based technology allows PerimeterX to detect the most sophisticated new forms of bot attacks.

PerimeterX’s API integrates with nearly any component of a company’s technology infrastructure. As a result, DevOps teams can quickly incorporate real-time behavioral analytics into their work, giving them maximum flexibility.

"Analyzing user behavior has long been a predictive staple of search engines and credit card fraud detection. It is tried, it is tested, it works and now companies that are serious about defending against bot attacks and other new cyber threats need to adopt behavior-based tools to guard against more sophisticated attacks," says Eric Ogren of 451 Group.

PerimeterX’s list of customers includes companies in the Fortune 500, the Alexa Top 500 and the Internet Retailer 100. In 2017, the company added new offices in London and Miami and significantly expanded its leadership team.

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
White House Cybersecurity Strategy at a Crossroads
Kelly Jackson Higgins, Executive Editor at Dark Reading,  7/17/2018
Lessons from My Strange Journey into InfoSec
Lysa Myers, Security Researcher, ESET,  7/12/2018
What's Cooking With Caleb Sima
Kelly Jackson Higgins, Executive Editor at Dark Reading,  7/12/2018
Register for Dark Reading Newsletters
White Papers
Video
Cartoon Contest
Current Issue
Flash Poll
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2018-14339
PUBLISHED: 2018-07-19
In Wireshark 2.6.0 to 2.6.1, 2.4.0 to 2.4.7, and 2.2.0 to 2.2.15, the MMSE dissector could go into an infinite loop. This was addressed in epan/proto.c by adding offset and length validation.
CVE-2018-14340
PUBLISHED: 2018-07-19
In Wireshark 2.6.0 to 2.6.1, 2.4.0 to 2.4.7, and 2.2.0 to 2.2.15, dissectors that support zlib decompression could crash. This was addressed in epan/tvbuff_zlib.c by rejecting negative lengths to avoid a buffer over-read.
CVE-2018-14341
PUBLISHED: 2018-07-19
In Wireshark 2.6.0 to 2.6.1, 2.4.0 to 2.4.7, and 2.2.0 to 2.2.15, the DICOM dissector could go into a large or infinite loop. This was addressed in epan/dissectors/packet-dcm.c by preventing an offset overflow.
CVE-2018-14342
PUBLISHED: 2018-07-19
In Wireshark 2.6.0 to 2.6.1, 2.4.0 to 2.4.7, and 2.2.0 to 2.2.15, the BGP protocol dissector could go into a large loop. This was addressed in epan/dissectors/packet-bgp.c by validating Path Attribute lengths.
CVE-2018-14343
PUBLISHED: 2018-07-19
In Wireshark 2.6.0 to 2.6.1, 2.4.0 to 2.4.7, and 2.2.0 to 2.2.15, the ASN.1 BER dissector could crash. This was addressed in epan/dissectors/packet-ber.c by ensuring that length values do not exceed the maximum signed integer.