RAM LABORATORIES — Department of Defense SBIR Phase II: MDA19-009

RAM LABORATORIES — SBIR Phase II award from Department of Defense.

Phase II SBIR prototype / development signal

  • Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
  • Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
  • At $1,509,997, this is a large obligation for typical SBIR Phase sizing — worth reviewing for scope breadth and teaming opportunity.
  • Topic code MDA19-009 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.

Informational capture context from public federal data — not legal or bid advice.

Amount
$1,509,997
Agency
Department of Defense · Missile Defense Agency
Program / Phase
SBIR · Phase II
Topic
MDA19-009
Solicitation
19.2
NAICS
Place of performance
CA
Period
2020-12-16 → 2022-12-15

Description

When deploying software to systems running in secure environments, it is of upmost importance that everything is done to ensure the software is secure and free of bugs and cyber vulnerabilities. While there exists a large number of tools that scan source code to find potential bugs and vulnerabilities, it is left to developers and subject matter experts (SMEs) to manually fix all of the identified issues. Not only is this a time-consuming process, it is made even worse by the large number of false positives, code that is actually bug free but still flagged by the tool as containing a vulnerability. To address this large technical gap, RAM Laboratories is proposing the Deep Learning for Precise, Automatic and Trusted Code Hardening and Error Removal (DL-PATCHER) solution. Leveraging recent state-of-the-art advances in deep learning, DL-PATCHER is able to use large and diverse code repositories to build neural network models that are able to reason over source code and automatically generate patches that fix bugs and vulnerabilities with astonishingly high accuracy rates. Approved for Public Release | 20-MDA-10643 (3 Dec 20)