HTTP/2 & TLS Fingerprint Manipulation Toolkit

A powerful toolkit for manipulating TLS and HTTP/2 fingerprints to simulate different browser behaviors and evade detection. Built for researchers, red teamers, and developers needing fine-grained control over TLS handshakes and HTTP/2 characteristics.

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📄 Overview

This toolkit allows you to:

• Generate realistic browser-specific JA3 and Akamai fingerprints (Chrome, Firefox, Safari, Edge)
• Randomize TLS cipher suites, extensions, curves, and JA3 strings
• Customize HTTP/2 settings, window update values, priority frames, and pseudo-header order
• Integrate easily with curl_cffi for actual HTTP requests

Perfect for:

• Penetration testing & bypassing bot detection
• TLS/HTTP/2 fingerprint evasion
• Automated scraping
• Security research

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🛠️ Installation

git clone https://github.com/muzzii255/fing.git
cd fing
pip install -r requirements.txt  # Requires curl-cffi

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🚀 Features

TLS Fingerprints

• Generate valid JA3 fingerprints for modern browsers
• Simulate TLS handshakes with custom curve lists, extension order, GREASE, and cipher suite shuffling

HTTP/2 Fingerprints (Akamai Style)

• Full control over SETTINGS, WINDOW_UPDATE, PRIORITY frames, and pseudo-header order

Browser Profiles Supported

• Chrome
• Firefox
• Safari
• Edge

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📚 Usage Examples

Generate JA3 Fingerprints

from main import generate_browser_ciphers

chrome_ja3 = generate_browser_ciphers("chrome")
print(chrome_ja3)

Generate HTTP/2 (Akamai) Fingerprints

from akamai import generate_akami_fingerprint

firefox_fp = generate_akami_fingerprint("firefox")
print(firefox_fp)

Perform HTTP Request with Fingerprints

from curl_cffi import requests
from fp_gen import generate_browser_ciphers
from akamai import generate_akami_fingerprint

ja3 = generate_browser_ciphers("chrome")
akamai_fp = generate_akami_fingerprint("chrome")
extra_fp = requests.ExtraFingerprints(
        tls_signature_algorithms=[
            "ecdsa_secp256r1_sha256",
            "rsa_pss_rsae_sha256",
            "rsa_pkcs1_sha256",
            "ecdsa_secp384r1_sha384",
            "rsa_pss_rsae_sha384",
            "rsa_pkcs1_sha384",
            "rsa_pss_rsae_sha512",
            "rsa_pkcs1_sha512",
            "rsa_pkcs1_sha1"],
        tls_grease=True,
        tls_permute_extensions=True)



response = requests.get(
    'https://tls.browserleaks.com/json',
    ja3=ja3,
    akamai=akamai_fp,
    extra_fp=extra_fp,
    headers={
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)...'
    }
)

print(response.json())

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🔧 Advanced Options

New TLS 1.3 Cipher Support

Add to TLS_CIPHER_NAME_MAP inside curl_cffi:

0x1305: "TLS_AES_128_CCM_8_SHA256",
0x1306: "TLS_AEGIS_256_SHA512",
0x1307: "TLS_AEGIS_128L_SHA256",

Firefox Curves

Add to TLS_EC_CURVES_MAP:

256: "ffdhe2048",
257: "ffdhe3072",

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🔍 HTTP/2 Akamai Format Guide

Each fingerprint contains 4 fields:

1. SETTINGS: e.g., 1:65536;4:4194304
2. WINDOW_UPDATE: e.g., 15663105
3. PRIORITY: e.g., 3:0:0:201,...
4. Pseudo-header order: e.g., m,a,s,p

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🎓 Research-Based

Built upon Akamai's research into passive fingerprinting and TLS/HTTP/2 client identification.

Passive-Fingerprinting-Of-HTTP2-Clients TLS Fingerprinting with JA3 and JA3S

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📅 License

MIT License © Muzzii255

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✨ Credits

Special thanks to:

• Salesforce for the original JA3 whitepaper
• Akamai for publishing fingerprinting research
• curl_cffi for enabling fine-tuned TLS control

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