Storage

1. What Are Storage Features in Browser Fingerprinting

Storage features refer to how a browser manages stateful and stateless data through mechanisms like localStorage, sessionStorage, Cookies, IndexedDB, and more advanced constructs like CacheStorage and Web SQL Database. These mechanisms are not only functional but have also become rich sources of fingerprinting identifiers.

Storage feature fingerprinting typically involves tracking:

• Availability and support for each storage type
• Maximum storage capacity estimates
• Data persistence behavior (cookies expiration, indexedDB cleanup settings)
• Behavior under storage pressure (how data is evicted when quotas are reached)
• Detected quotas and thresholds via timing attacks and limits
• Storage usage patterns (e.g., frequency of write/read, APIs called)

Sites use this fingerprint signal to detect whether a browser profile claims to be “clean” when it actually retains state. It’s also used by multi-account detection systems to find overlaps in persistent identifiers or cache behaviors.

2. How Platforms Use Storage for Fingerprint Detection

Storage-based fingerprinting is especially powerful because it combines behavior, capability, and persistence. Detection platforms analyze it through:

1. Storage API Availability Checks:
   Injects code to check whether APIs like localStorage, IndexedDB, or cookieStore are available and how they behave.

2. Cookies Behavior Monitoring:
   Examines first-party vs. third-party cookie handling, cookie isolation per origin, and blocking behavior under cross-context scenarios.

3. Storage Quota Estimation Techniques:
   Uses JavaScript and API timing to estimate storage limits and detect discrepancies (e.g., limited localStorage size can indicate sandboxing or isolation).

4. IndexedDB Fingerprinting:
   Some systems monitor how databases and object stores are initialized, what cmp() values they return for custom keys, and how transactions are handled.

5. Persistence Cross-checks Across Sessions:
   Fingerprint tools write data and clear cookies to test whether storage remnants (or their fingerprints) are recoverable — a technique known as evercookie or respawning detection.

6. Behavior Matching to User-Agent or OS:
   Storage usage patterns such as sessionStorage fallback timing or cookie expiration on Safari vs. Chrome are cross-checked with claimed OS or browser identity to detect spoofing.

This type of fingerprint is deeply behavioral and can be used in banking, marketplaces, and advertising environments to enforce strong user boundaries and prevent abuse.

3. How FlashID Simulates and Masks Storage Features

FlashID gives users total control over storage-based fingerprinting behaviors, creating fully isolated and configurable browser profiles that simulate real-world storage logic and persistence models.

FlashID’s storage-based protections include:

1. Separate Storage Environments:
   Each browser instance runs with a unique, dedicated storage context, preventing cross-profile contamination of cookies, local storage, and indexedDB.

2. Storage API Consistency Control:
   FlashID lets users choose which storage features appear enabled (e.g., localStorage on/off per profile), simulating browser configurations from different users or devices.

3. Quota and Capacity Spoofing:
   FlashID randomly or deterministically generates plausible storage size responses, masking real disk/storage thresholds, which confuses quota-based detection heuristics.

4. IndexedDB Transactions and Key Comparisons:
   All IndexedDB APIs, such as indexedDB.cmp(), IDBFactory.databases(), and IDBKeyRange operations, are intercepted and tailored to the selected browser profile characteristics.

5. Cookie Handling and Cleanup Timing Simulation:
   FlashID simulates browser-specific cookie retention behavior — supporting granular options such as time-based deletions for Safari and long-persistence cookies for Chrome-based browsers.

6. FlashID Fingerprint Masking for Cookie SameSite Restrictions:
   Granular emulation of SameSite, Secure, and Partitioned cookie treatment, ensuring that cookies behave in line with the expected browser and OS combination.

7. Storage Behavior Over Time:
   FlashID simulates realistic data growth and cache cleaning over sessions, offering profiles that age gracefully without standing out due to unnaturally clean or overly large storage history.

By implementing deep isolation, controlled scripting, and fingerprint prediction modeling, FlashID allows users to spoof and modify storage fingerprint characteristics on the fly — creating clean, independent browser profiles that maintain expected behaviors with granular realism.

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