Streaming fraud happens when users exploit streaming platforms by violating policies, creating multiple accounts, or manipulating access, most commonly to share account passwords with others to avoid paying for additional subscriptions or to bypass content restrictions. In some cases, scammers gain unauthorized access to accounts through account takeovers, using stolen credentials to stream content or resell access on the deep or dark web. This fraud trend is gaining momentum as streaming platforms continue to grow.
In one example, a 2023 Parks Associates study estimated that streaming services lost over $2.5 billion annually due to credential sharing and account abuse. In another report, Antennas Research found that nearly 30% of streaming users admit to sharing their passwords with people outside their household, undermining platform revenue and security.
As streaming becomes more central to how people consume media, protecting accounts and ensuring that only authorized users access content is becoming increasingly important for the industry’s health. This article covers how these fraudulent activities work, the consequences they bring, and how solutions like Sift can help platforms address the growing challenge of password sharing, account takeovers, and platform abuse.
How Does Streaming Fraud Work?
Streaming fraud typically begins with users or scammers gaining unauthorized access to streaming accounts.
Legitimate subscribers willingly share their login credentials with friends or family to avoid paying for extra subscriptions. While this practice is largely seen as harmless by consumers, it can lead to significant revenue loss for streaming platforms. In more illicit cases, fraudsters obtain credentials through phishing, data breaches, or the deep or dark web. They use these stolen accounts to stream content, resell access at a discount, or operate fake user networks.
An example of streaming fraud is a fraudster using a bot to create multiple accounts, each tied to a fake or stolen credit card or user account. In such instances, the legitimate user will find unauthorized access or charges and file a dispute. All the streaming service can do is try to recover from the reputational damage and absorb the cost of the chargebacks.
These fraudulent activities undermine the integrity of streaming platforms and can be difficult to detect because of VPN services and deceptive tactics. It has prompted many streaming services to become increasingly strict about logins, raise prices, and add friction that ends up disrupting the user experience.
What are the Different Types of Streaming Fraud?
Streaming fraud takes many forms, from policy abuse to deliberate and organized schemes. Understanding the main types helps platforms, creators, and advertisers recognize and combat these threats effectively.
Account Takeover
A more serious threat is account takeover, where attackers steal credentials through phishing, data breaches, or the dark web. These stolen accounts are then used or sold for unauthorized streaming, compromising both users and the platform. These types of attacks can result in unauthorized transactions that lead to chargebacks, damaging both revenue and streaming service reputation.
Multi-Account Fraud
Multi-account fraud is when a single individual or group creates and operates several accounts on the same platform with the intent to deceive or gain an unfair advantage. People use it to exploit sign-up bonuses and referral programs, manipulate ratings or reviews, hide fraudulent activity, or bypass bans and restrictions. To combat it, companies rely on techniques like device fingerprinting, behavioral analysis, and identity authentication.
Password Sharing
Easily the most common form of streaming fraud is password sharing, where subscribers share their login credentials with individuals outside their household. This violates platform terms of service, reduces revenue, and gives unauthorized users free access to premium content.
The Consequences of Streaming Fraud
The most apparent consequence of streaming fraud is the loss of revenue suffered by a streaming service. Some studies show that streaming services lose over $9 billion every year due to fraud, while music streaming services lose around $2 billion.
Password sharing in the United States is at all time highs, with 79% of users admitting to sharing passwords, despite only 13% being concerned with identity theft—a risk that increases with sharing credentials. This widespread behavior diminishes revenue that could otherwise fund content creation, platform innovation, and infrastructure improvements.
The sheer prevalence of streaming fraud necessitates the investment in fraud detection, enforcement mechanisms, and customer communication to stem losses, all of which add operational costs. While the overall issue is difficult to tackle, there are best practices that streaming services can follow to mitigate the effect of streaming fraud. The most expedient and efficient countermeasure is the integration of payment protection platforms like Sift.
How Can Streaming Platforms Prevent Streaming Fraud?
Streaming platforms can prevent fraud by combining technology, policy enforcement, and user education.
Platforms should enforce policies that limit the number of devices or users per account while regularly prompting users to confirm their login credentials. Multi-factor authentication (MFA) adds an extra layer of security, making it harder for attackers to access accounts even if they obtain access.
Educating users about the risks of sharing credentials and how to recognize phishing attempts can help reduce unintentional misuse. Users will be more likely to adhere to platform policies if they understand how such practices can impact their account safety and privacy.
Finally, implementing payment protection platforms and fraud detection systems that monitor account behavior in real time can help identify unusual purchase and use patterns, institute fake account creation prevention, and stay ahead of emerging fraud trends. This includes multiple logins from different locations or excessive simultaneous streams, which often indicates password sharing or an account takeover. This is where Sift’s Global Data Network, Clearbox Decisioning, and AI-powered fraud detection can help.
How Does Sift Address Streaming Fraud?
Sift helps streaming platforms fight fraud by using machine learning, the Global Data Network, and Clearbox Decisioning to detect and stop suspicious activity before it affects your business.
The Sift Global Data Network includes user behavior and activity from multiple sectors across the globe. Through AI-powered pattern recognition, Sift uses 16,000+ risk signals to determine the relative trustworthiness of each user that opens an account, flagging users that have suspicious behavior or fraudulent histories. The network is self-learning, with over 1 trillion annual events helping businesses stay ahead of emerging fraud trends and protect the bottom line.
Clearbox Decisioning is the transparent reasoning that sets Sift apart. Every industry, region, and individual business has different tolerances for fraud and suspicious behavior. Clearbox Decisioning gives those businesses agency by explaining exactly why a user is flagged. Businesses can create customizable workflows to block fraudulent activity most common for their business and industry. This has the added benefit of streamlining the process for legitimate customers while stopping suspicious users in their tracks.
The Sift Platform identifies patterns of multi-account fraud, account takeovers, and other forms of abuse, even when fraudsters try to disguise their actions as legitimate user behavior. This is because any piece of information tied to fraudulent activity (email addresses, credit card information, names, locations, IP addresses, and more) has likely already been flagged across the Sift Global Data Network. Extra scrutiny can be exercised in such cases, while giving vetted users a frictionless experience and encouraging overall company growth.
Emerging Fraud Requires Evolving Solutions
Emerging forms of streaming fraud are becoming more sophisticated, blending legitimate and fraudulent behaviors to evade detection. One such trend in 2025 is the use of real human activity through click farms combined with stolen credentials and legitimate devices to appear authentic. Every indication points to fraud becoming more dynamic, especially as AI becomes widely accessible.
To address these evolving threats, streaming platforms need fraud prevention solutions that adapt as quickly as fraudsters do. Sift helps platforms stay one step ahead by gathering data across multiple industries to learn from the fraudsters themselves, documenting when a user is tied to suspicious behavior, signals, and activity. This allows Sift to get ahead of fraudsters, detecting even subtle signs of policy abuse, account takeover, or credential sharing.
By anticipating how fraud evolves and proactively adjusting defenses, Sift ensures that streaming platforms can protect their ecosystems, maintain user trust, and encourage growth with legitimate users. This ongoing documentation and transparency is key to keeping fraud at bay in an ever-changing digital economy.
Streaming Fraud Primer
See how Sift helps prevent streaming fraud.
