Impersonate guide

Supported browser versions

curl_cffi supports the same browser versions as supported by our fork of curl-impersonate:

However, only Chrome-like browsers are supported. Firefox support is tracked in #59.

Browser versions will be added only when their fingerprints change. If you see a version, e.g. chrome122, were skipped, you can simply impersonate it with your own headers and the previous version.

If you are trying to impersonate a target other than a browser, use ja3=... and akamai=... to specify your own customized fingerprints. See below for details.

  • chrome99

  • chrome100

  • chrome101

  • chrome104

  • chrome107

  • chrome110

  • chrome116 1

  • chrome119 1

  • chrome120 1

  • chrome123 3

  • chrome124 3

  • chrome131 4

  • chrome133a 5 6

  • chrome136 7

  • chrome99_android

  • chrome131_android 4

  • edge99

  • edge101

  • safari15_3 2

  • safari15_5 2

  • safari17_0 1

  • safari17_2_ios 1

  • safari18_0 4

  • safari18_0_ios 4

  • safari18_4 7

  • safari18_4_ios 7

  • firefox133 5

  • tor145 7

Notes:

  1. Added in version 0.6.0.

  2. Fixed in version 0.6.0, previous http2 fingerprints were not correct.

  3. Added in version 0.7.0.

  4. Added in version 0.8.0.

  5. Added in version 0.9.0.

  6. The version postfix -a`(e.g. `chrome133a) means that this is an alternative version, i.e. the fingerprint has not been officially updated by browser, but has been observed because of A/B testing.

  7. Added in version 0.11.0

Which version to use?

Generally speaking, you should use the latest Chrome or Safari versions. As of 0.7, they’re chrome124, safari17_0 and safari17_2_ios. To always impersonate the latest avaiable browser versions, you can simply use chrome, safari and safari_ios.

import curl_cffi

curl_cffi.get(url, impersonate="chrome")

iOS has restrictions on WebView and TLS libs, so safari_x_ios should work for most apps. If you encountered an android app with custom fingerprints, you can try the safari_ios fingerprints given that this app should have an iOS version.

How to use my own fingerprints other than the builtin ones? e.g. okhttp

Use ja3=..., akamai=... and extra_fp=....

You can retrieve the JA3 and Akamai strings using tools like WireShark or from TLS fingerprinting sites.

# OKHTTP impersonatation examples
# credits: https://github.com/bogdanfinn/tls-client/blob/master/profiles/contributed_custom_profiles.go

url = "https://tls.browserleaks.com/json"

okhttp4_android10_ja3 = ",".join(
    [
        "771",
        "4865-4866-4867-49195-49196-52393-49199-49200-52392-49171-49172-156-157-47-53",
        "0-23-65281-10-11-35-16-5-13-51-45-43-21",
        "29-23-24",
        "0",
    ]
)

okhttp4_android10_akamai = "4:16777216|16711681|0|m,p,a,s"

extra_fp = {
    "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",
    ]
    # other options:
    # tls_min_version: int = CurlSslVersion.TLSv1_2
    # tls_grease: bool = False
    # tls_permute_extensions: bool = False
    # tls_cert_compression: Literal["zlib", "brotli"] = "brotli"
    # tls_signature_algorithms: Optional[List[str]] = None
    # http2_stream_weight: int = 256
    # http2_stream_exclusive: int = 1

    # See requests/impersonate.py and tests/unittest/test_impersonate.py for more examples
}


r = curl_cffi.get(
    url, ja3=okhttp4_android10_ja3, akamai=okhttp4_android10_akamai, extra_fp=extra_fp
)
print(r.json())

JA3 and Akamai String Format

A JA3 string is a simple, comma-separated representation of the key fields in a TLS ClientHello. It consists of five parts:

  • SSL/TLS Version, The numeric version the client requests (e.g. 771 for TLS 1.2).

  • Cipher Suites, A hyphen-separated list of all cipher suite IDs offered by the client (e.g. 4865-4866-4867-49195-49196).

  • Extension IDs, A hyphen-separated list of all TLS extension numbers the client includes (e.g. 0-11-10-35-16-5).

  • Supported Groups (aka “Elliptic Curves”), A hyphen-separated list of curve IDs the client supports for ECDHE (e.g. 29-23-24).

  • EC Point Formats, A hyphen-separated list of the point‐format IDs (almost always just 0 for “uncompressed”) (e.g. 0).

They’re concatenated in that exact order, with commas between fields. For example:

771,4865-4866-4867-49195-49196,0-11-10-35-16-5,29-23-24,0

Note that Chrome permutes the extension order on each request, so there is a new format called JA3N, which uses sorted extension_id list.

The Akamai HTTP/2 fingerprint string encodes four client‐controlled protocol parameters, joined by the pipe character (|):

  • SETTINGS, A semicolon‐separated list of ID:value pairs from the client’s initial SETTINGS frame. Each ID is a standard HTTP/2 setting identifier (e.g. 1 for HEADER_TABLE_SIZE, 4 for INITIAL_WINDOW_SIZE), and value is the client’s chosen value for that setting

  • WINDOW_UPDATE, A single integer: the value the client sends in its first WINDOW_UPDATE frame (or 0 if none was sent)

  • PRIORITY, Zero or more priority‐frame tuples, each formatted as StreamID:ExclusiveBit:DependentStreamID:Weight. Multiple tuples are comma-separated. This captures any PRIORITY frames the client issues before sending headers

  • Pseudo-Header Order, The sequence in which the client sends HTTP/2 pseudo-headers in its request HEADERS frame, encoded as comma-separated single-letter codes:

Putting it all together, an example fingerprint might look like:

1:65536;4:131072;5:16384|12517377|3:0:0:201|m,p,a,s

where:

SETTINGS = 1:65536;4:131072;5:16384
WINDOW_UPDATE = 12517377
PRIORITY = 3:0:0:201
Pseudo-Header Order = m,p,a,s

Although JA3 and Akamai fingerprint string already captures many of the aspects of a Hello Packet, there are still some fields are not covered and can be used to detect you. This is when the extra_fp option comes in, each field of this dict is pretty easy to understand. You should first set the ja3 and akamai string, then check if you have the identical fingerprint like your target. If not, use the extra_fp to further refine your impersonation.

Using CURLOPTs

The other way is to use the curlopt s to specify exactly which options you want to change.

To modify them, use curl.setopt(CurlOpt, value), for example:

import curl_cffi
from curl_cffi import Curl, CurlOpt

c = Curl()
c.setopt(CurlOpt.HTTP2_PSEUDO_HEADERS_ORDER, "masp")

# or
curl_cffi.get(url, curl_options={CurlOpt.HTTP2_PSEUDO_HEADERS_ORDER, "masp"})

Here are a list of options:

For TLS/JA3 fingerprints:

and non-standard TLS options created for this project:

  • CURLOPT_SSL_ENABLE_ALPS

  • CURLOPT_SSL_SIG_HASH_ALGS

  • CURLOPT_SSL_CERT_COMPRESSION

  • CURLOPT_SSL_ENABLE_TICKET

  • CURLOPT_SSL_PERMUTE_EXTENSIONS

For Akamai http2 fingerprints, you can fully customize the 3 parts:

  • CURLOPT_HTTP2_PSEUDO_HEADERS_ORDER, sets http2 pseudo header order, for example: masp (non-standard HTTP/2 options created for this project).

  • CURLOPT_HTTP2_SETTINGS sets the settings frame values, for example 1:65536;3:1000;4:6291456;6:262144 (non-standard HTTP/2 options created for this project).

  • CURLOPT_HTTP2_WINDOW_UPDATE sets initial window update value for http2, for example 15663105 (non-standard HTTP/2 options created for this project).

For a complete list of options and explanation, see the `curl-impersoante README`_.

Should I randomize my fingerprints for each request?

You can choose a random version from the list above, like:

random.choice(["chrome119", "chrome120", ...])

However, be aware of the browser market share, very old versions are not good choices.

Generally, you should not try to generate a customized random fingerprints. The reason is that, for a given browser version, the fingerprints are fixed. If you create a new random fingerprints, the server is easy to know that you are not using a typical browser.

If you were thinking about ja3, and not ja3n, then the fingerprints is already randomized, due to the extension permutation feature introduced in Chrome 110.

As far as we know, most websites use an allowlist, not a blocklist to filter out bot traffic. So do not expect random ja3 fingerprints would work in the wild.

Moreover, do not generate random ja3 strings. There are certain limits for a valid ja3 string. For example:

  • TLS 1.3 ciphers must be at the front.

  • GREASE extension must be the first.

  • etc.

You should copy ja3 strings from sniffing tools, not generate them, unless you can make sure all the requirements are met.

Can I change JavaScript fingerprints with this library?

No, you can not. As the name suggests, JavaScript fingerprints are generated using JavaScript APIs provided by real browsers. curl_cffi is a python binding to a C library, with no browser or JavaScript runtime under the hood.

If you need to impersonate browsers on the JavaScript perspective, you can search for “Anti-detect Browser”, “Playwright stealth” and similar keywords. Or simply use a commercial plan from our sponsors.