APIs are the foundation of today's digital ecosystem. With APIs handling a large portion of internet traffic(83 % of all Internet traffic), securing them has become one of the most critical challenges in modern cybersecurity. But API protection is not simple. Unlike traditional web applications, APIs provide direct, structured access to data and functionality, making it easier for attackers to exploit weaknesses. API misconfigurations and logic flaws have already led to some of 2024–2025’s most significant data leaks: Spoutible, Feb 2024: 207,000+ user records (email, phone, bcrypt password hashes, 2FA secrets); Dell Technologies, May 2024: ~49 million records (customer names, physical addresses, and order details); McDonald’s, Jun 2025: ~64 million job-applicant records (names, contact info, chat transcripts, form data). Spoutible, Feb 2024: 207,000+ user records (email, phone, bcrypt password hashes, 2FA secrets); Dell Technologies, May 2024: ~49 million records (customer names, physical addresses, and order details); McDonald’s, Jun 2025: ~64 million job-applicant records (names, contact info, chat transcripts, form data). A Mistake Waiting to Be Found Recently, I had a real-life experience that highlighted this risk. While reviewing my own web profile on one platform, I noticed a pattern in how the API exposed some data. There was something wrong with it, and out of curiosity, I examined a few API endpoints. To my surprise, I found a pathway to access others' PII data via API endpoints. With some automation, it was possible to enumerate through what appeared to be hundreds of thousands of unique records.After that, I documented the finding, wrote a PoC script to demonstrate the issue without exposing any real data, and submitted a disclosure report to the platform. My goal was to raise awareness and help them fix the problem before bad actors could exploit it. From Curiosity to Understanding This experience taught me important lessons about API implementation and privacy. Maybe most auditors focus only on endpoints when testing APIs. However, it is equally important to examine files exposed via the web interface. These files may not appear to contain sensitive content at first glance. However, they may include metadata, such as record identifiers, that can be extracted and used to discover other endpoints and data.Here is how I see it: on one side, you have a direct API analysis approach that focuses only on endpoints and parameters. On the other hand, there is a fully data-driven approach in which even seemingly harmless files can leak structural clues. If overlooked, this can lead to automated discovery of exposed data at scale. Such pathways might be hard to detect. These edge cases may be missed during standard assessment because they do not involve obvious vulnerabilities. They require combining logic, file structure analysis, and awareness of how different layers of a system interact.These edge cases may be missed in standard penetration testing because they do not involve obvious vulnerabilities. They require combining logic, file structure analysis, and awareness of how different layers of a system interact. Final Thoughts It is a good practice to audit API implementations, both internal and external regularly. Document all public and private endpoints, and review how auxiliary files might contribute to data exposure. Penetration testing should also include non-standard approaches. Sometimes it is better to check by hand than run standard, well-known tools and scanners. This approach helps reduce the risk of overlooked privacy issues in complex systems.
