When you are dealing with a huge amount of data, it can be very useful to enhance them by adding more valuable content. Example:
When you are processing many URLs during a security incident investigation or while extracting IOC's from a malware sample or logs, it can also be very interesting to categorize them. The process of categorization helps to tag an URL with a label like the classic "Adult Content", "Government", "Forums", etc. Many commercial solutions offer this feature. It can be very powerful to configure your firewall to deny access to non-business categories. But, integrated in closed solutions, it's not easy to re-use them to benefit of this information in your own scripts. For years, Bluecoat has a product called "K9" that helps to protect kids surfing the web. It's free, you just can get a license key and install the tool or... use the online API! I had to categorize a bunch of URLs , so I decided to take some time to write a few lines of Python to automate this task. My script webcat.py fetches the defined categories at regular interval (every two hours) and perform a lookup for each URL passed as argument: $ ./webcat.py isc.sans.org isc.sans.org,Education Multiple URLs can be passed on the same command line or the script can be fed via STDIN if you use "-" as parameter: $ ./webcat.py isc.sans.org blog.rootshell.be isc.sans.edu,Education blog.rootshell.be,Technology/Internet $ cat suspicious-urls.tmp | ./webcat.py - getmooresuccess.com,Business/Economy weddingme.net,Business/Economy riverbird.usa.cc,Malicious Outbound Data/Botnets 1ntershipping.co,Malicious Outbound Data/Botnets secureemail.bz,Malicious Sources/Malnets vsreviewsa.com,Malicious Sources/Malnets felceconserve.com,Malicious Outbound Data/Botnets flashsync.cf,Uncategorized cy-m0ld.com,Malicious Outbound Data/Botnets berettitdint.ru,Malicious Outbound Data/Botnets vehanmace.ru,Malicious Outbound Data/Botnets redderbest.gq,Uncategorized googlemails.ga,Uncategorized msportf1.com,Sports/Recreation www.vai-t.com,Malicious Sources/Malnets duotthenaning.ru,Malicious Sources/Malnets duotthenaning.ru,Malicious Sources/Malnets littrecdintoft.ru,Malicious Sources/Malnets vsreviewsa.com,Malicious Sources/Malnets doncglobal.com,Malicious Outbound Data/Botnets The API returns an hexadecimal code corresponding to the web category. That's why the script fetches them at regular interval and store them in a local file: $ ./webcat.py -h usage: webcat.py [-h] [-f CACHEFILE] [-F] [URL [URL ...]] Categorize URL using BlueCoat K9 positional arguments: URL the URL(s) to check. Format: fqdn[:port] optional arguments: -h, --help show this help message and exit -f CACHEFILE, --file CACHEFILE Categories local cache file (default: /var/tmp/categories.txt) -F, --force force a fetch of categories Before using the script, you have to register to get your K9 license, add it to the script (line 30). Note: I'm not aware of any rate-limit in place while querying the API. During my investigations, I was never blocked. Xavier Mertens |
Xme 697 Posts ISC Handler Jan 29th 2016 |
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Jan 29th 2016 6 years ago |
I tried the (webcat.py)script and getting something like " No JSON object could be decoded". Any help is appreciated. ( windows 8, Python 2.7)
C:\Python27>python webcat.py -F www.dshield.org Traceback (most recent call last): File "webcat.py", line 133, in <module> main() File "webcat.py", line 107, in main webCats = fetchCategories(args.cacheFile) File "webcat.py", line 43, in fetchCategories data = json.load(r) File "C:\Python27\lib\json\__init__.py", line 290, in load **kw) File "C:\Python27\lib\json\__init__.py", line 338, in loads return _default_decoder.decode(s) File "C:\Python27\lib\json\decoder.py", line 366, in decode obj, end = self.raw_decode(s, idx=_w(s, 0).end()) File "C:\Python27\lib\json\decoder.py", line 384, in raw_decode raise ValueError("No JSON object could be decoded") ValueError: No JSON object could be decoded |
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Feb 29th 2016 6 years ago |
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