SMART INFORMATION FLOW TECHNOLOGIES LLC — Department of Defense STTR Phase I: N23A-T009
SMART INFORMATION FLOW TECHNOLOGIES LLC — STTR Phase I award from Department of Defense.
Phase I STTR feasibility signal
- Phase I awards fund proof-of-concept work. For capture teams, they mark early interest from Department of Defense in a technical approach.
- Watch for Phase II follow-ons from the same firm/topic family — that conversion path is where budgets and transition pressure rise.
- Obligated amount $139,877. Cross-check similar awards in the same agency and technology tags for going-rate context.
- Topic code N23A-T009 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $139,877
- Agency
- Department of Defense · Navy
- Program / Phase
- STTR · Phase I
- Topic
- N23A-T009
- Solicitation
- 23.A
- NAICS
- —
- Place of performance
- MN
- Period
- 2023-07-26 → 2024-02-01
Description
SIFT and the University of Southern California's Information Sciences Institute (USC/ISI) propose to develop the Multi-Agent Debloating Environment to Increase Robustness in Applications (MADEIRA). MADEIRA will apply AI/ML techniques to learn how to apply diverse debloating tools, automatically reducing the attack surfaces of full systems that may include firmware, OS, container, and application-level targets. We will build on SIFT's proven Cyber Reasoning System (CRS), a fully autonomous, highly parallel plug-in architecture that already applies a wide variety of software analysis and rewriting tools to complex systems. We will also incorporate methods from SIFT's related OPENSHELL system, which uses massively parallel Symbolic Reinforcement Learning methods to learn how to apply different tools. USC/ISI brings a wealth of ML techniques for extracting knowledge from software, in both binary and source code forms. Designed to maximize the automation of the debloating process, MADEIRA will learn from successful debloating efforts on one target system and apply them to new targets. By automatically assessing and validating the debloating results, MADEIRA will ensure correct application of the debloating tools, and will explore diverse settings to maximize security and integrity metrics.