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FlowFrame enforces information flow control policies in Scala Spark applications.

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FlowFrame

FlowFrame is a Scala compiler plugin that performs static, fine-grained information flow analysis on code to detect privacy violations, in the spirit of the Jif compiler (https://www.cs.cornell.edu/jif/).

The project is organized as a hierarchy of top-level traits, each of which extend the functionality of the previous trait: CheckLabels extends SparkSignatures extends DefaultPolicies extends AbstractPolicies extends Solvers extends Constraints extends Policies.

Here is a quick rundown of what’s in each file:

  • purpose/PurposePolicies.scala - implementation of Purpose Policies
  • purpose/PurposePolicyParser.scala - parser for Purpose Policy annotations
  • purpose/predicates/Predicates.scala - incomplete implementation of PurposePolicy predicates (i.e. the stuff that comes after the with operator in Purpose Policies)
  • CheckLabels.scala - implements constraint generation pass
  • Constraints.scala - data structures for policy constraints
  • DefaultPolicies.scala - code for calculating default policies in the absence of policy annotations
  • FlowFramePlugin.scala - implements Scala’s plugin interface
  • Policies.scala - basic data structure for policies
  • AbstractPolicies.scala - data structures for abstract policies, policy references, policy signatures and policy structures
  • PolicyViolationDebugInfo.scala -helpful information for debugging policy violations
  • Solvers.scala - policy constraint solver
  • SparkSignatures.scala - policy signatures for Spark operations

Requirements

FlowFrame currently supports Scala 2.11 and 2.12.

Building FlowFrame

Run sbt package to create jars for the compiler plugin and the runtime. You can find these jars in flowframe-plugin/target and flowframe-runtime/target.

Using FlowFrame

To use FlowFrame, add the following commandline options to scalac:

  • -Xplugin:</path/to/plugin/jar>
  • -P:flowframe:lang:<policy language>

Currently, FlowFrame only supports the purpose policy language.

How FlowFrame works

FlowFrame uses @policy annotations on case classes representing database table rows accessed through the Spark Dataset API. Any named entity can be given explicit policy annotations, but FlowFrame attempts to infer annotations whenever possible. Ideally, only input and output Datasets will require annotations.

See the CONTRIBUTING file for how to help out.

License

FlowFrame is Apache 2.0 licensed, as found in the LICENSE file.

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FlowFrame enforces information flow control policies in Scala Spark applications.

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