Not all formats, such as ABW, are created to be easily edited. Even though numerous tools can help us tweak all document formats, no one has yet invented an actual all-size-fits-all tool.
DocHub gives a simple and efficient tool for editing, taking care of, and storing documents in the most widely used formats. You don't have to be a technology-savvy user to erase PII in ABW or make other modifications. DocHub is robust enough to make the process straightforward for everyone.
Our feature enables you to modify and edit documents, send data back and forth, create dynamic documents for information gathering, encrypt and protect documents, and set up eSignature workflows. Additionally, you can also generate templates from documents you use on a regular basis.
You’ll find a great deal of other functionality inside DocHub, such as integrations that let you link your ABW document to various business applications.
DocHub is an intuitive, fairly priced way to deal with documents and improve workflows. It provides a wide selection of features, from creation to editing, eSignature solutions, and web form building. The program can export your files in many formats while maintaining maximum safety and following the greatest information protection criteria.
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Hi - my name is Luke Cartey and Iamp;#39;m a member of the field engineering team here at Semmle. This video is about writing a QL query to find sensitive or personally identifiable information, so called PII, that gets written to log files and application runtime. Today, weamp;#39;ll be looking at a open source e-commerce platform called Shopizer. Itamp;#39; s written in Java and weamp;#39;ll be trying to see whether we can find any of any PII vulnerabilities in Shopizer. Now in order to do that weamp;#39;re going to need to find a way to identify personal identifiable information in the source code. Unfortunately, Shopizer as with many applications doesnamp;#39;t have any sort of semantic markers in the code that tell you what is PII. So what going to do is weamp;#39;re going to start off by writing a heuristic query that selects all fields in the program whose name matches either email percentage credit card percentage or percentage phone percentage. This percentage here is a