- SolutionsUSE CASES
Protect users’ accounts
Slash fraud losses
Prevent spam and bots
International Revenue Share Fraud
Stop fake account registrations
Stop malicious scraping
Secure API traffic
Banking & fintech accounts
reCAPTCHA Alternative: Why 10 companies switched from reCAPTCHA to Arkose Labs to win against bots.
Bad Bots and Beyond: 2023 State of the Threat
With Arkose Labs’ 2023 State of the Threat Report, you will find extensive information and best practices around
USE CASESProtect users’ accounts
Slash fraud losses
International Revenue Share Fraud
Banking & fintech accounts
Stop fake account registrations
Stop malicious scraping
Secure API traffic
Prevent spam and bots
INDUSTRIESProtect users’ accounts
Slash fraud losses
Prevent spam and bots
International Revenue Share Fraud
Secure API traffic
Stop fake account registrations
Stop malicious scraping
Banking & fintech accounts
Banking & fintech accounts
- ProductsPRODUCTS
Stop bot attacks by driving up adversarial effort and cost
Assess email risk at bot scale
Detect and block reverse-proxy phishing attacks
Unique, customizable & performance improvement challenges
WHY ARKOSE LABSSabotage attacker’s ROI
Industry-first SLA guarantee
Industry-first SLA guarantee
Industry-first SLA guarantee
SERVICES & SUPPORTProfessional services expertise
Fast, reliable support
Flexible open platform
- Industries
- ResourcesINSIGHTS
Read our thought leadership blogs
Customer success stories
Videos from the Arkose Labs team
EVENTSEDUCATIONExpert Guide to Account & Identity Fraud
THOUGHT LEADERSHIPData-driven research reports
Fraud prevention guides
Fraud thought leadership
Learn how Arkose Labs prevents fraud
View all Arkose Labs content
INSIGHTSEVENTSEDUCATIONTHOUGHT LEADERSHIP - Company
- Customers
Summary
Customer
Global Social Media Platform
Business Problem
- Large-scale scraping of public profiles
- Targeting information which is the platform's source of revenue
- Difficulty differentiating between good traffic and malcious users
Solution
- Arkose Labs detected and stopped automated attacks
- Malicious traffic faced repeated enforcement challenges, preventing scraping at scale
- Good users faced no negative impact to their experience
Results
- 19% uplift in good user throughput
- 22% reduction in scraping
- Overall better customer experience for good users
Overview
The client is a major social media platform with more than 600 million users and a prime destination for networking, sharing content and job postings, among other things. It is a well-known and trusted brand among its customer base, however that same popularity has made it a major target for fraudsters looking to steal information from the platform.
The Business Problem
This large social networking site was facing a major issue where fraudsters would employ bots at scale in order to scrape information from the public profiles of real users. For fraudsters, this information could then be used for malicious reasons, such as to create synthetic identities or launch targeted phishing scams. The platform needed to ensure it was protecting its users from downstream abuse.
Additionally, user information is core to the business’ commercial viability. Offering products to third parties based on access to user information is the source of revenue for the platform. Therefore, anyone disseminating this information for their own purposes was in fact depriving the networking site of potential revenue millions of dollars. That’s why it was so important for the platform to protect itself from this large-scale scraping of public profiles.
They had to ensure that any solution would not impact the experience of good users. This meant that they needed a scraping solution that would not simply block any traffic that might appear suspicious, but rather a more nuanced approach. They needed to better differentiate between automated scraping and good users who represented future revenue-generating customers. This was critical in order to protect consumers from downstream abuse that was fueled by the information gathered on their platform from the mass scraping.

We are seeing higher legitimate user engagement alongside lower scraping activity, which are the critical metrics for us.

The Arkose Labs Solution
The social network decided to deploy Arkose Labs on their website in order to detect automated programs carrying out scraping activity and prevent malicious activity. When Arkose Labs detects potentially suspicious behavior – for example if one session viewed multiple user profiles, without logging in as a recognized user – they were presented with an enforcement challenge. Proprietary, interactive challenges are made using 3D visuals rendered in real time, with countless possible variations. These are designed and tested to ensure that all automated attacks fail, are resilient to being solved en masse by computer vision technology, and are resilient to large-scale human-driven attacks. Incrementally complex challenges are presented to bad actors attempting to gain information from the public profiles, in order to sap their time and efficiency and erode the potential profitability of attacks.
Legitimate users who may see a challenge, however, were able to quickly and simply solve them with no negative implications for the overall user experience. By preventing bad actors from carrying out scraping at scale, this eliminated the ROI of these attacks and led to attackers abandoning their efforts against the platform.
The Arkose Advantage
Reduce False Positives
Rather than outright blocking, Arkose Labs instead profiles and classifies traffic, and pushes authentication challenges to suspicious traffic.
100% SLA Guarantee
Authentication puzzles generated by Arkose Labs could not be solved by automation, even using the most robust machine vision tools.
Seamless customer Experience
Since no users are ever blocked, customer experience is not adversely affected. Good users rarely see a challenge, and if they do, they only have to complete it once.
Intent-based Analysys of Traffic
In-band authentication did not disrupt the users’ flow and improved good customer throughput.
Demonstrated Results
- 19% uplift in good user throughput
- Greatly reduced instances of false positives.
- 22% reduction in scraping
- Millions of dollars of potential revenue protected
- Vastly improved experience for good users.
Book a Meeting
Meet with a fraud and account security expert