A security-first approach for modern applications
Fake users are not just a growth problem — they are a security problem.
From bot-driven signups and SIM farms to recycled phone numbers and fake messaging accounts, fake users can quietly damage your app by:
- Inflating metrics
- Abusing resources
- Distorting analytics
- Creating downstream fraud risks
Below are practical, security-oriented strategies to reduce fake users before they enter your system.
1. Fake Users Often Start With Phone Numbers
Many apps use phone numbers as a primary identity signal. Unfortunately, attackers know this too.
Common fake-user patterns include:
- Virtual or disposable numbers
- Bulk-purchased SIM cards
- Numbers that are not registered on WhatsApp or Telegram
A phone number that looks valid is not necessarily usable or trustworthy.
Security teams should treat phone numbers as risk signals, not just login credentials.
2. Format Validation Is Not Real Validation
Regex and format checks (E.164, country codes, length) only answer one question:
“Does this string look like a phone number?”
They do not answer:
- Is the number active?
- Is it actually used by a real person?
- Is it registered on WhatsApp or Telegram?
In fake user prevention, format validation is only the first gate, never the final one.
3. Validate Platform-Level Registration
One of the most effective ways to block fake users early is platform-level validation.
Before allowing signups, messaging, or onboarding flows, ask:
- Is this number registered on WhatsApp?
- Is it active on Telegram?
- Has it been seen as usable recently?
Numbers that are not active on any major messaging platform are often:
- Bots
- Test numbers
- Low-quality or recycled data
Services like NumberChecker are commonly used to perform batch checks for WhatsApp and Telegram availability, helping teams filter risky users before OTP abuse or account creation.
4. Stop OTP Abuse Before It Starts
OTP systems are a frequent attack surface.
Fake users exploit them by:
- Requesting OTPs at scale
- Rotating large lists of phone numbers
- Consuming SMS or WhatsApp resources
Security best practices include:
- Rate limiting OTP requests
- Monitoring signup velocity
- Blocking numbers that fail platform-level validation
If a number cannot even receive messages on WhatsApp or Telegram, sending OTPs to it is often wasted effort.
5. Use Batch Intelligence, Not One-by-One Checks
Fake users rarely arrive individually — they come in batches.
If your app supports:
- Bulk imports
- Referral programs
- Campaign-based growth
Then batch phone validation is essential.
With batch detection, you can:
- Pre-screen large number lists
- Remove high-risk entries early
- Protect onboarding and messaging systems
Platforms such as https://www.numberchecker.ai/ focus on large-scale phone number detection and enrichment, which is more aligned with real-world attack patterns than single-number checks.
6. Enrich Numbers to Reduce Risk
Treating all phone numbers as equal is another common security mistake.
In practice, useful enrichment signals include:
- Age range
- Gender
- Region
- Activation or usage status
These attributes help security and growth teams:
- Adjust verification levels
- Add friction only where needed
- Reduce false positives
Enrichment turns phone numbers from raw input into actionable risk data.
Final Thoughts
Fake users are evolving quickly, and basic validation is no longer enough.
To prevent fake users effectively:
- Don’t rely on format checks alone
- Validate real platform usage
- Detect risk at batch scale
- Treat phone numbers as dynamic security signals
Preventing fake users early leads to cleaner data, lower costs, and safer systems.
How are you currently detecting fake users in your app?
Do you validate phone numbers beyond format and OTP?
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