This is a light weight Python wrapper to the Censys REST API.
The egg can be installed using Pip or easy_install (e.g., sudo pip install censys).
There are three API endpoints that the library provides access to: Index, Query, and Export. More details about each can be found in the Censys API documentation: https://censys.io/api.
The index APIs allow you to perform full-text searches, view specific records,
and generate aggregate reports about the IPv4, Websites, and Certificates
endpoints. There is a Python class for each index: CensysIPv4,
CensysWebsites, and CensysCertificates. Below, we show an example for
certificates, but the same methods exist for each of the three indices.
import censys.certificates
c = censys.certificates.CensysCertificates(api_id="XXX", api_secret="XXX")
# view specific certificate
print c.view("a762bf68f167f6fbdf2ab00fdefeb8b96f91335ad6b483b482dfd42c179be076")
# iterate over certificates that match a search
fields = ["parsed.subject_dn", "parsed.fingerprint_sha256"]
for cert in c.search("github.com and valid_nss: true", fields=fields):
print cert["parsed.subject_dn"]
# aggregate report on key types used by trusted certificates
print c.report(query="valid_nss: true", field="parsed.subject_key_info.key_algorithm.name")The SQL Query endpoint allows running SQL against the indices.
import censys.query
c = censys.query.CensysQuery(api_id="XXX", api_secret="XXX")
# find datasets (e.g., ipv4) that have exposed data
print c.get_series()
# get schema and tables for a given dataset
print c.get_series_details("ipv4")
# Start SQL job
res = c.new_job("select count(*) from certificates.certificates")
job_id = res["job_id"]
# Wait for job to finish and get job metadata
print c.check_job_loop(job_id)
# Iterate over the results from that job
print c.get_results(job_id, page=1)The SQL Export API allows exporting large subsets of data using SQL.
import censys.export
c = censys.export.CensysExport(api_id="XXX", api_secret="XXX")
# Start new Job
res = c.new_job("select count(*) from certificates.certificates")
job_id = res["job_id"]
# Wait for job to finish and fetch results
print c.check_job_loop(job_id)The Data API allows programatic access to the raw data files.
import censys.data
c = censys.data.CensysData(api_id="XXX", api_secret="XXX")
# Get a Series
ssh_series = c.view_series('22-ssh-banner-full_ipv4')
# View all the files in each scan
for scan in ssh_series['results']['historical']:
print c.view_result('22-ssh-banner-full_ipv4', scan['id'])
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