Content Abuse Prevention

Stop fraudulent content, before it’s even created

Get the Full Content Abuse Prevention Kit

Thousands of sites and apps are protected by Sift Science


Content abuse is eroding the digital trust between users and businesses

Content abuse – including scams, spam and other fraudulent content – is one of the fastest growing types of fraud. It’s never been more critical to protect your community from malicious attacks, while creating the best experience possible for good users.

Watch bad content disappear from your platform, faster

Sift Science uses Live Machine Learning™ to help you identify and stop bad users before they can post content. Our Content Abuse Prevention solution protects the community from multiple forms of content abuse, helping leading businesses across the world automate content review, improve brand perception and conversion rates, and increase user engagement and retention rates.

Catch more abusive users faster, and see the volume of flagged content go down by as much as 70%.

Protect your users from content abuse

From bulk attacks to sleeper accounts, we’ve helped many customers uncover fraudulent content and behavior that was previously impossible to discover on their platform.

  • Marketplace fraud

    Malicious sellers create spammy listings, attempting to take your users off of the platform to defraud them.

    Content Abuse


    Financial loss, degraded trust


    Customers and revenue loss to competitors, higher customer acquisition costs

  • Fake profiles and romance scams

    An increasing number of fraudsters are creating online profiles solely to catfish, harass, and manipulate others.

    Content Abuse


    Poor user experience, emotional trauma


    Reduced customer lifetime value and user engagement, brand and reputation damage

  • Social network spam

    Spammy postings, phishing, cyberbullying, and malware: all are ways scammers can gain personal information from unsuspecting users.

    Content Abuse


    Compromised personal information, poor user experience


    Higher customer acquisition costs, declines in search engine rankings

  • Toxicity and profanity

    Fake and malicious reviews, comments, and replies harm businesses and are used for harassment, malware distribution, spam, and other harmful ends.

    Content Abuse


    Poor user experience


    Increased fraud and risk management costs, financial and legal liabilities

Check out our Content Abuse Prevention eBook

Step into the bright side of fighting fraud

Use Live Machine Learning™ to protect your business from content abuse

Existing rules-based or manually intensive solutions are reactive, expensive, and difficult to maintain as your business grows. The Sift Science solution includes built-in automation tools and easy-to-use dashboards to help you stop content abuse in real time.

Watch content abuse prevention demo

Key benefits

Stop fraudsters early.

Don’t wait for fraudsters to act. Examine bad users’ behavior in real time and stop them before they create fake listings, spammy comments, and malicious messages.

Catch bad content, faster.

Identify and remove malicious content before the community sees or flags it, drastically reducing its exposure rate.

Automate away your risks and worries as you scale.

Protect your community without worrying about the need for larger content moderation teams.

Grow your business with trust.

Build better communities. Grow your top-line revenue by improving the user experience for your good customers.

Uncover more bad users than you are finding today

We helped a major dating site find 35% more bad users than their existing system, and brought another dating site’s false positive rate to nearly zero.

Increase speed and accuracy, all with your existing headcount

Poshmark, one of the largest social marketplaces for fashion, has seen a 70% decrease in spam comments since implementing Sift Science Content Abuse Prevention

Key features

Instant, accurate content and behavior analysis for all your users

Content analysis + behavioral footprint

Our machine learning models analyze the content and how your users create content: timing and sequence of behaviors, velocity of different activities, unique users they interact with, and more.

Global and custom models across our network

Sift Science tracks fraudulent behavior across our global network in real time. If fraud is attempted on any of our 12,000+ customers’ sites or apps, we learn from and prevent similar behavior on your site – instantly.

Language-agnostic algorithms

Our models will automatically pick up the new ways fraudsters adapt their language patterns, so your team does not have to continuously identify and blacklist new terms.

Enterprise security and scale

We protect millions of user accounts every day, ingesting over 3,000 events per second, with 200ms score latency and 99.95%+ uptime. We are SOC 2 compliant, and our data protection policies align with GDPR and Privacy Shield.

Transparent scoring and signals

We use 16,000+ signals to get the most holistic view possible. Our transparent scoring makes it easy to understand why a user is risky or safe. Our machine learning models, including deep learning and natural language processing, unlock insights from each piece of content and data point.

96Sift Score
  • Volume and velocity of content shared
  • IP address and device used
  • Deep textual analysis (natural language processing)
  • Number of duplicate or similar messages posted
  • Site or app navigation
  • Repeat versus first-time actions
  • Email, mail exchanger (MX) records, and domain analysis
  • Social data

The Sift Science content abuse prevention console

  • Investigate and flag risky users and content

    Review user risk and content risk in one place and take action on users and content directly. We surface suspicious activity, and tell you why we think there’s risk.

  • Network of linked users

    A visualization of how users are connected to each other lets you find rings of users committing content abuse so you can make efficient bulk decisions.

  • Manage automation policies with ease

    Automate how you want to treat users and their content. Workflows and Queues let moderation teams act on suspicious content and users quickly, without involving engineering resources.

Get started with a Content Abuse Prevention Specialist

Get started