Case Study 2: Peloton API Exposure and T-Mobile's Recurring API Breaches — A Pattern of Failure

Overview

This case study examines two organizations that suffered API security failures with distinct but instructive characteristics. Peloton, the connected fitness company, exposed user profile data through an API that allowed unauthenticated access to any user's workout data, location information, and profile details — regardless of privacy settings. T-Mobile, one of the largest US telecommunications carriers, experienced at least eight significant data breaches between 2018 and 2023, with API vulnerabilities being a recurring attack vector. Together, these cases illustrate how API security failures are not isolated incidents but systemic patterns that persist even after organizations have been breached and ostensibly improved their security posture.

Part I: Peloton API Exposure

Background

Peloton Interactive gained enormous popularity during the COVID-19 pandemic, growing from approximately 700,000 subscribers in early 2020 to over 6.9 million by mid-2021. The company's platform combines connected exercise equipment (bikes and treadmills) with a social fitness network, creating a rich data environment that includes workout statistics, personal information, and in some cases, real-time geographic location data from outdoor workouts.

The Vulnerability

In January 2021, security researcher Jan Masters discovered that Peloton's API endpoints returned user data without requiring authentication and did not properly enforce privacy settings. The vulnerabilities were documented and reported through responsible disclosure.

Unauthenticated API Access:

# No authentication required
GET /api/user/123456789/profile HTTP/1.1
Host: api.onepeloton.com

# Response included full profile regardless of privacy settings
{
  "id": "123456789",
  "username": "jsmith_fitness",
  "name": "John Smith",
  "location": "New York, NY",
  "age": 35,
  "gender": "male",
  "height": "5'10\"",
  "weight": "175 lbs",
  "is_profile_private": true,  # Privacy setting ignored!
  "total_workouts": 342,
  "image_url": "https://cdn.peloton.com/users/123456789/profile.jpg"
}

The critical detail: even when is_profile_private was set to true, the API returned the complete profile data. The privacy setting was enforced only in the Peloton mobile app and web interface — at the UI layer — but not at the API layer.

Workout Data Exposure:

GET /api/user/123456789/workouts HTTP/1.1
Host: api.onepeloton.com

# Response
{
  "data": [
    {
      "id": "workout_abc",
      "type": "outdoor_running",
      "start_time": "2021-01-15T07:00:00Z",
      "duration_seconds": 1800,
      "distance_miles": 3.2,
      "calories": 320,
      "gps_data": {
        "start_lat": 40.7128,
        "start_lng": -74.0060,
        "route": [...],  # Full GPS track
        "end_lat": 40.7145,
        "end_lng": -74.0089
      }
    }
  ]
}

The GPS data exposure was particularly concerning because: - It revealed users' home locations (where runs typically started and ended) - It established predictable routines and schedules - It affected users who had explicitly set their profiles to private - It could be correlated with known public figures (including, as was widely reported, US President Biden, who was a Peloton user)

User Enumeration:

The API used sequential numeric user IDs, allowing complete enumeration of the user base:

# Simplified enumeration script
for user_id in range(1, 7000000):
    profile = requests.get(
        f"https://api.onepeloton.com/api/user/{user_id}/profile"
    ).json()
    if profile:
        save_profile(profile)

Impact

The Peloton API vulnerabilities exposed: - Personal profiles of approximately 4.9 million users (at the time of discovery) - Workout history including precise GPS routes for outdoor workouts - Physical attributes (height, weight, age, gender) - Profile photos - Social connections and friend lists

The national security implications were highlighted when it was reported that President Biden's Peloton bike was a topic of discussion during the administration transition, with concerns about the connected device being brought into the White House. The API vulnerability demonstrated that even if the physical device was secured, the data flowing through Peloton's backend was not.

Peloton's Response

Peloton's initial response was criticized for being slow and inadequate: - The researcher reported the vulnerability on January 20, 2021 - Peloton initially required the researcher to agree to the company's terms of service to access the bug bounty program (which the researcher declined as it included an NDA) - After media coverage in May 2021, Peloton accelerated its response - The company implemented API authentication requirements and ensured privacy settings were enforced at the API layer

Lessons from Peloton

Privacy Must Be Enforced Server-Side: The most fundamental lesson is that privacy controls implemented only at the UI layer provide no actual protection. The API is the true enforcement point — if the API returns data, it is effectively public regardless of what the UI displays.

Fitness Data Is Sensitive Data: The case highlighted that fitness and location data can reveal highly personal information: home addresses, daily routines, physical conditions, and social relationships. Organizations handling such data must treat it with the same rigor as financial or health information.

Connected Device APIs Expand Attack Surface: Every IoT device that communicates with a backend API creates a new attack surface. Peloton's case demonstrated that the API security of connected devices deserves dedicated security assessment.

Part II: T-Mobile's Recurring API Breaches

A History of Breaches

T-Mobile's breach history represents one of the most striking examples of recurring API security failures in a major corporation:

The 2021 Breach: Technical Details

The most severe T-Mobile breach occurred in August 2021, when an attacker exploited an API vulnerability to access a database containing records for 76.6 million current, former, and prospective customers.

Attack Chain:

1. Initial Access: The attacker discovered an exposed API endpoint on T-Mobile's testing infrastructure that was accessible from the internet
2. Network Pivot: Through the API, the attacker gained access to a testing environment connected to T-Mobile's production network
3. Database Discovery: The attacker located and accessed an Oracle database server containing customer records
4. Data Exfiltration: Over several weeks, the attacker exfiltrated records including names, dates of birth, Social Security numbers, and driver's license information

Data Exposed: - Names, dates of birth, and Social Security numbers for approximately 40 million former and prospective customers - Names, addresses, dates of birth, phone numbers, IMEIs, and SIM card information for approximately 7.8 million current postpaid customers - Account PINs (used for account access) for approximately 850,000 active prepaid customers - Additional records for approximately 28.5 million other individuals

The attacker posted the stolen data on underground forums, initially demanding Bitcoin payment. When T-Mobile did not pay, the data was released publicly.

The 2023 Breaches: API-Specific Analysis

T-Mobile's January 2023 breach is particularly relevant because it was explicitly attributed to an API vulnerability. According to T-Mobile's SEC filing:

"A bad actor used a single Application Programming Interface (or API) to obtain limited types of information on approximately 37 million current postpaid and prepaid customer accounts."

The exposed API: - Did not require proper authentication or had weak authentication that was bypassed - Returned customer data including names, billing addresses, email addresses, phone numbers, dates of birth, T-Mobile account numbers, and account features - Was exploited over a period of approximately six weeks before detection (November 25, 2022, to January 5, 2023)

Why T-Mobile Keeps Getting Breached

T-Mobile's recurring breaches point to systemic issues rather than isolated failures:

1. API Sprawl and Shadow APIs

As a large telecommunications company, T-Mobile operates hundreds of APIs across customer-facing applications, partner integrations, device management, billing systems, and internal tools. Managing security consistently across this sprawl is enormously challenging, and "shadow APIs" — endpoints that exist but are not documented in the organization's API inventory — repeatedly serve as attack vectors.

2. Legacy System Integration

Telecommunications companies maintain extensive legacy systems. APIs that bridge legacy and modern systems often have weaker security controls because legacy systems were not designed for API-based architectures. The 2021 breach reportedly originated from a testing environment that had network connectivity to production databases — a legacy architectural pattern that modern security designs would avoid.

3. Merger Integration Challenges

T-Mobile's 2020 merger with Sprint significantly expanded its infrastructure. Integrating security controls across two organizations' API ecosystems is a multi-year effort, and during the integration period, the combined organization had an expanded and potentially inconsistent attack surface.

4. Insufficient API Monitoring

The 2023 breach went undetected for six weeks. During this time, the attacker made millions of API requests to exfiltrate 37 million records. Effective API monitoring should detect: - Unusual request volumes from individual clients - Sequential access patterns suggesting enumeration - Data exfiltration volumes exceeding normal application behavior - Requests from unusual network locations or user agents

5. Penalty Insufficiency

Despite repeated breaches, the financial consequences for T-Mobile (a $350 million settlement for the 2021 breach) represent a small fraction of the company's revenue ($79.6 billion in 2022). Critics argue that penalties must be significantly larger to incentivize meaningful security investment.

Regulatory Response

Following the repeated breaches, T-Mobile agreed to: - A $350 million settlement for the 2021 breach class-action lawsuit - Spend $150 million on cybersecurity improvements over 2022-2023 - Implement specific security measures including: - Zero-trust architecture adoption - Enhanced API security monitoring - Multi-factor authentication for all systems - Regular third-party security assessments - CISO reporting directly to the board of directors

Connecting the Cases

Peloton and T-Mobile represent different manifestations of the same fundamental problem: organizations treat API security as secondary to application functionality.

Lessons for Ethical Hackers

Testing Methodology

1. Authentication Bypass Matrix: For every API endpoint, test access with no authentication, expired tokens, tokens from different user roles, and tokens from different tenants
2. Privacy Setting Verification: When applications offer privacy settings, verify that they are enforced at the API layer, not just the UI layer
3. Data Minimization Review: Compare the data returned by API responses to what the application actually needs — flag any excessive exposure
4. Sequential ID Testing: Always test whether object identifiers are sequential and enumerable
5. Historical Endpoint Discovery: Use Wayback Machine, JavaScript analysis, and documentation discovery to find endpoints that may have been forgotten or deprecated but not removed

Reporting Recurring Vulnerabilities

When assessing an organization that has experienced previous breaches (like T-Mobile), your report should: - Reference previous incidents and note whether the same vulnerability classes persist - Assess the effectiveness of remediation measures from previous incidents - Evaluate whether systemic issues (API inventory management, monitoring, access control consistency) have been addressed - Provide measurable recommendations with specific timelines

Discussion Questions

1. Peloton enforced privacy settings at the UI layer but not the API layer. How common is this pattern? What development practices could prevent it?

2. T-Mobile has been breached at least eight times in five years. At what point does regulatory action become insufficient, and what alternative accountability mechanisms should be considered?

3. Peloton's API exposed GPS tracking data that could reveal users' home locations and daily routines. Should regulations treat location data differently from other categories of personal data? What protections are appropriate?

4. T-Mobile agreed to spend $150 million on cybersecurity improvements. How should this investment be allocated across the OWASP API Security Top 10 categories to address the most impactful risks?

5. Both cases involved sequential identifiers. Evaluate the trade-off between using UUIDs (which reduce enumeration risk) and sequential integers (which are simpler and more performant). When is the complexity of UUIDs justified?

6. As an ethical hacker hired by T-Mobile after their sixth breach, what would be the top three recommendations in your executive summary? How would you frame these to motivate board-level action?

Return to Chapter 23: API Security Testing