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Maintaining confidential information control in software is a persistentsecurity problem where failure means secrets can be revealed via programbehaviors. Information flow control techniques traditionally have been based onstatic or symbolic analyses -- limited in scalability and specialized toparticular languages. When programs do leak secrets there are no approaches toautomatically repair them unless the leak causes a functional test to fail. Wepresent our vision for HyperGI, a genetic improvement framework tha detects,localizes and repairs information leakage. Key elements of HyperGI include (1)the use of two orthogonal test suites, (2) a dynamic leak detection approachwhich estimates and localizes potential leaks, and (3) a repair component thatproduces a candidate patch using genetic improvement. We demonstrate thesuccessful use of HyperGI on several programs which have no failing functionaltests. We manually examine the resulting patches and identify trade-offs andfuture directions for fully realizing our vision.

HyperGI: Automated Detection and Repair of Information Flow Leakage