Network

1. What Are Network Features in Browser Fingerprinting

Modern browsers expose various network-related APIs that can be leveraged to uniquely identify and fingerprint a user. These include:

• navigator.connection: Provides network type and speed (effectiveType, rtt, downlink)
• WebRTC: Enables detection of local IP addresses, often bypassing public proxy visibility
• Resource Timing: Precise timestamps of network transactions (performance.getEntriesByType("resource"))
• DNS Leak Detection via <img> or fetch() timing and failures
• fetch() and XMLHttpRequest behavior – such as proxy alignment and HTTP version reporting
• RTCPeerConnection ICE candidates: Used to collect internal IP addresses of the user’s local device

These network features help distinguish between real users and automated tools by retrieving real-time device connectivity features, connection types, or internal IP bindings.

A high fingerprint similarity score across multiple sessions using the same proxy or consumer-grade anonymity stack is often heavily penalized by systems performing account linking analysis, especially in high-value KYC verification, ad fraud prevention, and bot mitigation fields.

2. How Platforms Detect Network Feature Fingerprints

Web fingerprinting systems exploit the following to identify a device or browser uniquely via network features:

1. IP Address Enumeration via WebRTC: Websites can bypass traditional proxy settings and detect internal or public IPs using WebRTC’s ICE candidate gathering mechanism.

2. navigator.connection API Inspection: Properties such as effectiveType ("4g", "3g", "wifi"), rtt (round-trip time), and downlink (network bandwidth estimation) give insight into:

   • User’s physical location
   • Internet infrastructure quality
   • Device carrier or enterprise status

3. Resource Timing Delays and Load Fingerprints: Through timing metrics like fetchStart, responseEnd, and CORS behaviors, platforms can:

   • Analyze actual network conditions
   • Identify spoofed user agent or IP if resource retrieval behavior is mismatched

4. Consistency Across Web Requests: Detection systems cross-reference:

   • Proxy IP
   • WebRTC-local IPs
   • Initial connect() response origin host
   • Resource timing drifts or match anomalies to look for synthetic or altered sessions.

5. HTTPS vs HTTP Behavior and TLS Fingerprints Analysis: Advanced target systems monitor:

   • TLS stack variants
   • Cipher acceptance lists from JavaScript-initiated requests
   • HTTP/2 or QUIC capabilities from synthetic browser sessions

These network-level behavioral signals are layered into the fingerprint recognition matrix as hard-to-fake, context-aware attributes—especially when dynamically analyzing synthetic browsing sessions.

3. How FlashID Masks Network Feature Fingerprints

FlashID dynamically controls and replicates realistic networking behaviors — not only of the proxy and IP — but also of signal-level information such as navigator.connection, RTT metrics, DNS behavior, and request timing patterns.

With FlashID, each profile can simulate:

✅ Realistic navigator.connection Behavior

You can define or randomize the effectiveType, rtt, and downlink values to reflect any expected user profile (e.g., "4g", "wifi", "slow-2g"), avoiding suspicion in regions where access speed is mismatched against IP location or claimed operating conditions.

✅ Complete WebRTC Control

Unlike many anti-fingerprint services which simply disable WebRTC or hardcode fakes, FlashID:

• Masks the user’s internal IPs
• Emulates behavior of specific communication environments
• Can toggle or spoof IP interface types (IPv4/IPv6 leaks, LAN or public)

FlashID can also fake ICE candidate leak behavior while avoiding total disconnection detection, enabling full protection without triggering browser disconnection logic.

✅ Network Timing and Resource Alignment

FlashID modifies key performance timing APIs to simulate realistic task delays across:

• Resource load segment (fetch, requestStart, etc.)
• Connection timing (secureConnectionStart, domainLookup)
• DOM processing timings during asynchronous loads

These values coordinate with selected user agent and IP timing patterns so all behaviors remain consistent across fingerprinting engines.

✅ Proxy-aware Network Behavior

FlashID:

• Adapter (override) Content-Type, Accept, and Proxy settings according to your profile
• Blocks suspicious DNS fingerprint attacks and prevents JavaScript from profiling actual system interfaces
• Synchronizes resource fetching using proxy-aware behavioral cues to mimic real geolocation

🔥 Why Network Feature Masking Matters

Fingerprints based on network APIs are particularly valuable for detecting proxy reuse, resource timing spoofing, and platform divergence. Platforms using behavior-based models or AI-powered session learners may silently rate session anomalies.

FlashID ensures:

• Local machine IPs are not revealed
• navigator.connection mimics any expected speed or connection mode
• Timing APIs and networking consistency remain aligned across profiles

This prevents websites from detecting synthetic or altered sessions, enabling users to safely perform:

• Multi-accounting online
• Ad ops at scale
• Realistic testing and automation

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