Implement Field Level Redaction¶

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Procedure

The $redact pipeline operator restricts the contents of the documents based on information stored in the documents themselves.

Diagram of security architecture with middleware and redaction.

To store the access criteria data, add a field to the documents and embedded documents. To allow for multiple combinations of access levels for the same data, consider setting the access field to an array of arrays. Each array element contains a required set that allows a user with that set to access the data.

Then, include the $redact stage in the db.collection.aggregate() operation to restrict contents of the result set based on the access required to view the data.

For more information on the $redact pipeline operator, including its syntax and associated system variables as well as additional examples, see $redact.

Procedure¶

For example, a forecasts collection contains documents of the following form where the tags field determines the access levels required to view the data:

{
   _id: 1,
   title: "123 Department Report",
   tags: [ [ "G" ], [ "FDW" ] ],
   year: 2014,
   subsections: [
       {
           subtitle: "Section 1: Overview",
           tags: [ [ "SI", "G" ], [ "FDW" ] ],
           content:  "Section 1: This is the content of section 1."
       },
       {
           subtitle: "Section 2: Analysis",
           tags: [ [ "STLW" ] ],
           content: "Section 2: This is the content of section 2."
       },
       {
           subtitle: "Section 3: Budgeting",
           tags: [ [ "TK" ], [ "FDW", "TGE" ] ],
           content: {
               text: "Section 3: This is the content of section3.",
               tags: [ [ "HCS"], [ "FDW", "TGE", "BX" ] ]
           }
       }
   ]
}

For each document, the tags field contains various access groupings necessary to view the data. For example, the value [ [ "G" ], [ "FDW", "TGE" ] ] can specify that a user requires either access level ["G"] or both [ "FDW", "TGE" ] to view the data.

Consider a user who only has access to view information tagged with either "FDW" or "TGE". To run a query on all documents with year 2014 for this user, include a $redact stage as in the following:

var userAccess = [ "FDW", "TGE" ];
db.forecasts.aggregate(
   [
     { $match: { year: 2014 } },
     { $redact:
         {
           $cond: {
                    if: { $anyElementTrue:
                           {
                             $map: {
                                     input: "$tags" ,
                                     as: "fieldTag",
                                     in: { $setIsSubset: [ "$$fieldTag", userAccess ] }
                                   }
                           }
                        },
                     then: "$$DESCEND",
                     else: "$$PRUNE"
                  }
         }
     }
   ]
)

The aggregation operation returns the following “redacted” document for the user:

{ "_id" : 1,
  "title" : "123 Department Report",
  "tags" : [ [ "G" ], [ "FDW" ] ],
  "year" : 2014,
  "subsections" :
     [
        {
          "subtitle" : "Section 1: Overview",
          "tags" : [ [ "SI", "G" ], [ "FDW" ] ],
          "content" : "Section 1: This is the content of section 1."
        },
       {
         "subtitle" : "Section 3: Budgeting",
         "tags" : [ [ "TK" ], [ "FDW", "TGE" ] ]
       }
     ]
}