Ever regarded closely at a Google search URL and seen a weird “ei” parameter in there? While it would not appear to occur for every search, when it does, that “ei” parameter accommodates an encoded Unix UTC timestamp (and other things Google solely knows). Interpreting this artifact can thus permit forensic analysts so far a specific search session. Because it appears to be initiated by Google’s servers, this browser independence is smart. Special Due to Phillip Moore (@phillmoore) who advised this script thought and in addition helped test it. This text additionally lists a PHP conversion script however more importantly, it exhibits an “ei” value conversion example which we will use to initially validate our script. When does “ei” occur? Whenever donkeys vote! Eee-ore! The “ei” parameter occurs with each URLs. Subsequent sub-class clicks results in numerous “ei” parameters being returned. Note: It seems that the “sei” parameter seen initially additionally comprises an identical timestamp mechanism because the “ei” parameter.
The “ei” parameter can be returned in Firefox’s Private Browser mode. The very first thing to note is that the “ei” parameter is unpadded and URL protected base64 encoded. Base64 encoding is a method of writing (binary) information using the ASCII alphabet (see here). There must be four output bytes produced for each 3 enter bytes. Note: Typically, “ei” is 22 bytes long (ie 2 bytes of padding is required) but it can be longer/shorter. If “ei” is a a number of of 4 (ie remainder is 0), then padlength must be set to 0. For instance, a 24 byte lengthy “ei” doesn’t require padding. Sixty four encoding has been performed. So now we now have our base64 decoded string, we are able to learn the primary 4 bytes and calculate the timestamp. To do that requires a little bit of background maths. Byte0 is least significant. Byte3 is most significant. Each byte vary is 256 times the previous byte’s vary. We can then name Python’s datetime’s utcfromtimestamp and strftime methods to transform/print out our human readable string. Here’s the help usage textual content for the script. It was developed and initially tested using Python 2.7 on a Window 7 Pc. It has also been examined on SANS SIFT v3. This example “ei” worth was taken from the Deed Poll weblog article and the script output matches their end result.
As people, we use pure language to communicate by means of totally different mediums. Natural Language Processing (NLP) is usually identified as the computational processing of language used in everyday communication by humans. NLP has a basic scope definition, as the field is broad and continues to evolve. NLP has been around since the 1950s, beginning with automated translation experiments. Back then, researchers predicted that there could be complete computational translation in a three to 5 years time frame, however due to the lack of pc power, the time-body went unfulfilled. NLP has continued to evolve, and serp api most lately, with the help of Machine Learning tools, elevated computational energy and huge information, we have seen fast growth and implementation of NLP duties. Nowadays many commercial products use NLP. Its actual-world makes use of range from auto-completion in smartphones, private assistants, serps, voice-activated GPS programs, and the record goes on. Python has change into the most preferred language for NLP because of its great library ecosystem, platform independence, and ease of use.
Especially its in depth NLP library catalog has made Python more accessible to builders, enabling them to analysis the sector and create new NLP tools to share with the open-source group. In the next, let’s discover out what are the widespread real-world uses of NLP and what open-source Python tools and libraries are available for the NLP duties. OCR is the conversion of analog text into its digital form. By digitally scanning an analog version of any text, OCR software program can detect the rasterized text, isolate it and at last match every character to its digital counterpart. OpenCV-python and Pytesseract are two major Python libraries commonly used for OCR. These are Python bindings for OpenCV and Tesseract, respectively. OpenCV is an open-supply library of computer vision and machine studying, whereas Tesseract is an open-source OCR engine by Google. Real-world use cases of OCR are license plate reader, the place a license plate is identified and remoted from a photo image, and the OCR process is performed to extract license quantity.