Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

IoT/Embedded Security //

Botnet

12/6/2017
08:35 AM
Michael Lynch
Michael Lynch
News Analysis-Security Now
50%
50%

Surviving the Holiday Bot Security Surge

Bots can make security life interesting at any time. In the holiday shopping frenzy they're going to cause problems for retailers, wholesalers and anyone else touching the public Internet.

Every holiday season, the use of automated bots to grab the hottest toys, electronics and other items en masse aggravates shoppers and retailers alike. These sophisticated bots are able to make legitimate purchases of high demand, limited quality items at superhuman speed. In turn, the items purchased are then resold for a premium (sometimes exorbitant) price on auction sites like eBay.

Even the most tech savvy online shoppers are no match for these sophisticated bots. They can outmaneuver humans in terms of speed and even outwit solutions like CAPTCHA, the technology designed to sift real humans from bots. Some retailers use blacklists in attempt to keep track of known bad devices, but this can be easily defeated if a bot shopper was trying to make the mass purchases look like they were coming from hundreds or even thousands of devices instead of just one.

The headaches caused by bots abound for retailers. They are hard to detect and shut down without sophisticated detection capabilities. And bots can slow down a website, a big motivator for retailers to block them. The holiday shopping season exacerbates the problem, since digital traffic naturally spikes on key shopping days such as Black Friday, Cyber Monday and the last few days before Christmas.

The good, the bad... and the annoying
The growth of bots on the net is well documented. A report by the security firm Imperva found that bots overall are responsible for 52 percent of web traffic. Consider that this is the first time that there are more bots than humans roaming the Internet.

Generally speaking, bots can fit into one of two basic categories: bad bots and good bots. The former type is used by fraudsters with malicious intent to harm or defraud. Some of the most egregious are deployed by fraudsters to take over users' personal accounts, something that is becoming widespread, in part, because of the high return on the fraudsters' investment. According to a 2016 report from Trend Micro, a compromised account is worth around three dollars on the black market, while a stolen credit card number is only valued at 22 cents.

Retailers may also be familiar with malicious bots that can be used at checkout to hoard popular items. This is where bots can put the season's hottest items in their shopping cart and let them sit there, never intending to finalize the purchases. Hoarding is designed to intentionally disrupt the retailers supply chain, and can bring a business' online shopping capabilities to a screeching halt by preventing them from seeing where they stand on inventory, sales, profits, etc.

On the other hand, so-called "good" bots, such as shopping bots, are used to automate the entire online buying process, enabling bot creators to buy up huge chunks of a retailer's available inventory for a popular item, such as the latest sneakers or electronic device.

Calling these bots "good" is potentially a misnomer. Annoying might be a better description. While these types of bots are not illegal, they can be extremely frustrating to online shoppers and retailers who want to serve their loyal customers and not allow a handful of people to usurp what should be a level purchasing playing field. It is therefore up to the individual retailer to decide whether or not they want to allow this activity or not.

To provide a better experience for consumers, many retailers and ecommerce platforms are working hard to mitigate these bots. They're building technology to identify bot activity before the checkout process has been completed.

There is one key market segment where it is illegal to use shopping bots: ticketing. Ticket bots have been used for years to scoop up tickets in bulk to coveted shows and events in order to resell at much higher prices-in other words, scalping. That came to an end last December, when the Better Online Ticket Sales (BOTS) Act of 2016 was passed and signed into law.

These abuses, in part, came to a head in 2013 when Ticketmaster, the largest online distributor of tickets in the US, estimated that bots were being used by scalpers to purchase about 60% of tickets to the hottest shows, seriously disappointing longstanding customers trying to secure tickets to high-profile events. The law was an effort to combat this widespread abuse.

Defenses to date
To detect and stop bots from interfering with your organization's lucrative holiday shopping season requires diligence surrounding security, a multi-layered approach to device intelligence and authentication-and the technology behind a "no bot" strategy.

One way to identify bots vs. humans lies in their pattern. The pattern behind bot attacks is their high rate of speed. Technology is available that can detect potential velocity attacks, a sign of bots. This would enable organizations to identify and screen them out. Such solutions work by flagging devices that are used to perform multiple unusual behaviors, typically at a high rate of speed. If a device performs multiple login attempts on multiple accounts over a short period of time, this could signal the use of a bot.

That said, many of these bot detection tools fall short of true identification because they rely on IP addresses or cookies in their model. This method of identification is easily thwarted by sophisticated bots that change their IP address continually or clear/disallow cookies. Sophisticated bots require more sophisticated screening technologies.

The next generation arsenal of bot-prevention tools includes device intelligence, device fingerprinting, malware detection, machine learning and behavioral analysis. This model relies more on identifying the bot at the device level or identifying behavior such as the fact that a mouse or keyboard isn't used, potential evidence of a "scripted" or automated session.

It is important to employ both static techniques, such as detecting the presence of malware on the device, and a more comprehensive behavioral analysis such as a high number of attempts, a high number of failures, unusual traffic patterns, unusual speed of access and access attempts, etc. This combination of techniques can be more accurate and not so easily fooled.

A multi-modal, layered approach to screen out the bots is a crucial factor if your organization wants to stop these practices and provide a more level playing field for your loyal customers to successfully interact with you. Bots are not going away anytime soon, so companies that do business online would be wise to invest in the necessary technology, infrastructure and security protocols that will help put the joy back into digital shopping during the holidays for both customers and businesses.

Related posts:

Michael Lynch is InAuth's Chief Strategy Officer and is responsible for developing and leading the company's new products strategy, as well as developing key US and international partnerships.

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
COVID-19: Latest Security News & Commentary
Dark Reading Staff 8/10/2020
Researcher Finds New Office Macro Attacks for MacOS
Curtis Franklin Jr., Senior Editor at Dark Reading,  8/7/2020
Exploiting Google Cloud Platform With Ease
Dark Reading Staff 8/6/2020
Register for Dark Reading Newsletters
White Papers
Video
Cartoon Contest
Write a Caption, Win an Amazon Gift Card! Click Here
Latest Comment: They said you could use Zoom anywhere.......
Current Issue
Special Report: Computing's New Normal, a Dark Reading Perspective
This special report examines how IT security organizations have adapted to the "new normal" of computing and what the long-term effects will be. Read it and get a unique set of perspectives on issues ranging from new threats & vulnerabilities as a result of remote working to how enterprise security strategy will be affected long term.
Flash Poll
The Changing Face of Threat Intelligence
The Changing Face of Threat Intelligence
This special report takes a look at how enterprises are using threat intelligence, as well as emerging best practices for integrating threat intel into security operations and incident response. Download it today!
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2020-13285
PUBLISHED: 2020-08-13
For GitLab before 13.0.12, 13.1.6, 13.2.3 a cross-site scripting vulnerability exists in the issue reference number tooltip.
CVE-2020-16087
PUBLISHED: 2020-08-13
An issue was discovered in Zalo.exe in VNG Zalo Desktop 19.8.1.0. An attacker can run arbitrary commands on a remote Windows machine running the Zalo client by sending the user of the device a crafted file.
CVE-2020-17463
PUBLISHED: 2020-08-13
FUEL CMS 1.4.7 allows SQL Injection via the col parameter to /pages/items, /permissions/items, or /navigation/items.
CVE-2019-16374
PUBLISHED: 2020-08-13
Pega Platform 8.2.1 allows LDAP injection because a username can contain a * character and can be of unlimited length. An attacker can specify four characters of a username, followed by the * character, to bypass access control.
CVE-2020-13280
PUBLISHED: 2020-08-13
For GitLab before 13.0.12, 13.1.6, 13.2.3 a memory exhaustion flaw exists due to excessive logging of an invite email error message.