Rami Essaid, Distil Networks’ CEO and co-founder, takes just three minutes to run through how Distil Networks can protect your web applications from bad bots, API abuse, and fraud. As explained in this video, Distil Networks incorporates advanced techniques like hi-def device fingerprinting, machine learning and behavioral modeling, browser validation, advanced device rate limiting, and the world’s largest known violators database of bad bots.
Distil Networks gives you complete visibility and control over human, good bot, and bad bot website traffic, enabling you to block 99.9% of malicious bots without impacting legitimate users.
Hi, my name's Rami Essaid, I'm co-founder and CEO of Distil Networks. Distil Networks protects your web application from bad bots and API abuse. Automated threats, or bad bots, are being used by hackers and fraudsters to exploit your web applications. Whether it's account takeovers, unauthorized vulnerability scans, testing stolen credit cards, or denial-of-service attacks bringing down your site, bots are being leveraged by the bad guys to attack you at scale.
Twenty percent of all of your web traffic is made up of bad bots, and most clients can't tell the difference between humans and bots. Distil Networks is a first, easy and accurate way to detect and mitigate bad bots. With an easy-to-install inline proxy, we're able to detect over 99% of bot attacks with little or no false positives. And with both cloud and physical or virtual appliance options, Distil can be easily deployed no matter what your infrastructure looks like.
We started by divorcing ourselves from an IP to track and identify malicious users. Instead, we created a device fingerprint to identify a bad bot, no matter what IP it's coming in from. Unlike every other security device that has to constantly play the game of IP whack a mole, we catch a bad bot once and can track it no matter where it's coming from around the globe. We then aggregate the knowledge of every malicious fingerprint that we've identified across our network, so we don't have to reinvent the wheel.
Once we identify a bad bot for one particular customer, that knowledge is instantly aggregated across the globe in minutes. Security shouldn't be done in isolation, and at Distil, we have the largest community of customers working together to block bad bots. Most importantly, security shouldn't be reactive. At Distil, we don't wait for a malicious actor to do something bad before we identify and block them.
We use machine learning to predict when a connection's going to be malicious, and intercept that traffic. We then challenge it with a test to measure whether or not it's truly a bot. If it passes a test, then the connection goes through, but when it fails a test, we know we've prevented an attack, and were able to apply those algorithms more broadly. This serves as a feedback mechanism into the system to allow it to continue to self-learn.
We're protecting hundreds of enterprises against automated threats. So let's take a look at a couple customer examples:
- EasyJet, one of Europe's largest airlines, was having their brand diluted and losing customers due to aggregator bots. Using Distil's appliance, they've been able to put a stop to all competitive aggregation and scalping.
- We helped Whitepages reduce its workload on customer service in DevOps by 20%. These are just a couple of our success stories.
- Distil helped GuideStar save 20 hours a week of IT time.
- We helped Manta reduce overall cost by 35% a year.
- Distil helped TravelBrands increase uptime and reduce CDN usage cost by 65%.
- We helped Lamudi's IT staff save over 30 hours each week.
If you're interested in learning on how Distil can help you improve your security posture and block bad bots, contact us today. Thank you for taking the time to learn about the automated threat.