XL-Parser provides a bunch of functions for data extraction and analysis. It also provides web log analysis features like a tool for detection of suspicious activities. More details and screenshots on http://le-tools.com.
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| Website |
http://le-tools.com/XL-Parser.html |
| Tags |
Log Analysis |
| License |
GNU General Public License version 3.0 (GPLv3)
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| Platform |
Windows
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| Features |
- Input can be a directory, a file or multiple files, or the clipboard
- File formats: XL-Parser supports many file formats like plain text, unicode, text inside binaries, doc and docx, xls and xlsx, evt and evtx, pdf, msg and text inside zip files. You can even extract a file using a different parser. For example, you can extract data from a docx file, but open it as a zip, so you will have access to xml file inside it.
- File filters: If the input is a directory, you can include the subfolder or not. You can also set a combinaison of filters: keyword or regex that match filename, size of the file, last modified time or last accessed time. Your combinaison of filters can be save for a later use.
- Extraction: You can extract data using a combinaison of keyword or regex or use the special objects already set which are: IPv4, IPv6, URLs, Emails, Hostnames, Domain names, MAC addresses or credit card numbers. XL-Parser provides a lot of options for extraction and for report.
- Web log analysis: One specialty of XL-Parser is web log analysis. When you analyse web logs, you can extract data using anything that is in the logs. For example, you can extract all requests related to a particular IP address, but you cannot search for requests related to an ISP, because this information is not in the log. XL-Parser provides you the way to do this and much more. First, XL-Parser will help you parse the log and build a SQlite database from it. When it's done, XL-Parser provides a bunch of functions to query the database and find suspicious activities. Cool!
- Split logs: This goal of this function is to split logs but it can be used to split any text file, if you want to preserve the integrity of each line. Logs can be splitted by file size, by date object (by hour, by day, by week, by month) or by number of rows.
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