invisible_playwright/docs/pinning.md
feder-cr 60e55491ea feat: initial public release
Stealthfox — a patched Firefox 150.0.1 for browser-fingerprint stealth,
shipped as a Playwright-compatible Python wrapper.

  * Sync + async Stealthfox launcher (firefox_user_prefs, virtual desktop
    on Windows, SOCKS5 auth via patched nsProtocolProxyService)
  * fpforge: Bayesian fingerprint sampler over GPU / audio / fonts /
    screen / TCP options / ~400 other navigator fields
  * WebRTC stealth: srflx address swap, synthetic srflx fallback,
    private-LAN host candidates — no real public IP leak via STUN
  * GPU sandbox fix for FF150 alt-desktop regression
  * Bezier-curve mouse motion baked into Juggler

Targets Windows x86_64 + Linux x86_64. Binary fetched on first run from
GitHub Release "firefox-1".
2026-05-12 21:57:18 -07:00

6.5 KiB
Raw Blame History

Pinning fingerprint fields

By default, every field of the fingerprint is sampled from a Bayesian network of real-world Firefox telemetry, seeded by an integer. Pass the same seed and you get the same fingerprint; omit it and each session is fresh.

pin lets you force specific fields while letting the rest stay seed-derived. Useful when you need to replicate a known device (e.g. an NVIDIA 1080p laptop), test a specific GPU/screen combo, or pin just one noisy signal that a target site weighs heavily.

from stealthfox import Stealthfox

with Stealthfox(
    seed=42,
    pin={
        "gpu.renderer": "ANGLE (NVIDIA, NVIDIA GeForce RTX 4090 Direct3D11)",
        "gpu.vendor":   "Google Inc. (NVIDIA)",
        "screen.width":  2560,
        "screen.height": 1440,
        "hardware.concurrency": 16,
    },
) as browser:
    ...

How sampling + pinning interact

The generator is a Bayesian network: every field has a probability distribution conditioned on its parents. For example gpu_class_tier conditions screen.tier, hardware.concurrency and webgl.msaa_samples. A high-end GPU will tend to pair with a 2560x1440+ screen and 16+ cores.

When you pin a field:

  1. The pinned value is written directly, bypassing the sampler.
  2. Unpinned children are still sampled from their conditionals — using the parent's original posterior, not the pinned value.

That last point is the subtle one: pinning breaks the conditional chain. If you pin gpu.renderer to an RTX 4090 string but leave screen unpinned, the sampler will pick screen from the seed-derived tier (which might be low_end), producing a physically implausible "RTX 4090 + 1366x768" pairing.

Rule of thumb: pin correlated fields together, or just trust the sampler.

Full list of pinnable keys

Keys are dotted paths. All values are optional — omitted keys fall back to the sampler.

gpu.*

Key Type Example Notes
gpu.class_tier str "high_end" The root of the Bayesian network. One of "low_end", "mid_range", "high_end", "integrated_old", "integrated_modern". Pin this alone to steer the whole profile (screen, concurrency, MSAA, …) toward a coherent tier without having to name each sub-field.
gpu.vendor str "Google Inc. (NVIDIA)" Must exactly match the renderer vendor prefix, otherwise detectors catch the mismatch.
gpu.renderer str "ANGLE (NVIDIA, NVIDIA GeForce RTX 4090 Direct3D11)" Windows ANGLE string. Used by WebGL UNMASKED_RENDERER_WEBGL.

Why class_tier is pinnable separately from renderer. They live at different levels of abstraction:

  • class_tier is a coarse handle over the whole Bayesian graph. It gates the distribution of screen, hardware.concurrency, webgl.msaa_samples, and storage quota. Pin {"gpu.class_tier": "low_end"} and the sampler returns a coherent low-end machine — small screen, 2-4 cores, 4x MSAA — without you having to specify each field.
  • renderer is an exact string that lands verbatim in WebGL's UNMASKED_RENDERER_WEBGL. Useful when you want to imitate a specific GPU the target site has seen before. Does not condition other fields — if you pin renderer to an RTX 4090 but leave class_tier unpinned, class_tier is re-sampled from scratch and might disagree with the renderer string (see How sampling + pinning interact).

In practice most users should pin class_tier alone, or pin renderer+vendor+class_tier together if they want full control.

screen.*

Key Type Example
screen.width int 2560
screen.height int 1440
screen.avail_width int 2560
screen.avail_height int 1400
screen.dpr float 1.0, 1.25, 1.5, 2.0
screen.tier str "1080p", "1440p", "4k", ...

hardware.*

Key Type Example Notes
hardware.concurrency int 16 navigator.hardwareConcurrency.
hardware.storage_quota_mb int 10_000 navigator.storage.estimate().quota / 1024².

audio.*

Key Type Example Notes
audio.sample_rate int 48000, 44100 AudioContext.sampleRate.
audio.output_latency_ms float 20.0 AudioContext.outputLatency * 1000.
audio.max_channel_count int 2, 6, 8 AudioDestinationNode.maxChannelCount.

codec.* (booleans)

Key Effect
codec.av1_enabled truecanPlayType('video/av01') returns "probably".
codec.webm_encoder_enabled MediaRecorder advertises WebM support.
codec.mediasource_webm MediaSource.isTypeSupported('video/webm').
codec.mediasource_mp4 MediaSource.isTypeSupported('video/mp4').
codec.webspeech_synth speechSynthesis.getVoices() returns a fabricated voice list.

webgl.*

Key Type Example Notes
webgl.msaa_samples int 4, 8, 16 MAX_SAMPLES WebGL parameter. Conditioned on gpu.class_tier when sampled.

Top-level

Key Type Example Notes
fonts list[str] ["Arial", "Segoe UI", ...] Complete font allowlist. Every other font is hidden. The sampler usually picks 1424 system fonts.
dark_theme bool False prefers-color-scheme: dark. Real traffic is ~85% light, 15% dark.

Reading the chosen values back

Every sampled (or pinned) value lands in a zoom.stealth.* pref inside the browser. Open about:config in a launched stealthfox session and filter for zoom.stealth to see the exact values in effect.

Alternatively, inspect the instance before the with block exits:

sf = Stealthfox(seed=42)
with sf as browser:
    # sf.seed is set; the full profile is in browser's prefs
    ...

Common patterns

Mimic a specific real device

Pin the whole visible tuple — GPU, screen, concurrency, fonts, audio:

pin = {
    "gpu.vendor":   "Google Inc. (Intel)",
    "gpu.renderer": "ANGLE (Intel, Intel(R) Iris(R) Xe Graphics Direct3D11)",
    "gpu.class_tier": "mid_range",
    "screen.width":  1920,
    "screen.height": 1080,
    "screen.dpr":    1.0,
    "hardware.concurrency": 8,
    "audio.sample_rate": 48000,
}

Test the low-end GPU path only

pin = {"gpu.class_tier": "low_end"}
# screen, msaa, concurrency re-sample from the seed but conditioned
# correctly on the low-end tier.