SBIR/STTR Research Award

Expanding Software Integrity Platform (SIP) Coverage Beyond Basic Windows Software Applications

Award identifier 638a513d5b46f684df39461b37012f734dd46fd1341ccd103c66dae9b245d866Awarding agency Department of Defense · Air Force

Award amount

$1,246,880

Program and phase

SBIR · Phase II

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
D&G ANALYTICS INC.
Proposal award date
2025-07-16
Contract end date
2027-04-15
UEI
KSBFGT5HG1F5
Solicitation number
X24.5
Topic code
AFX245-PCSO1

Research abstract

The Department of the Air Force (DAF) faces a critical cybersecurity challenge: nation-state adversaries, such as Russia and China, have developed advanced techniques to infiltrate U.S. software supply chains. Traditional security tools detect only known vulnerabilities, leaving the Air Force vulnerable to hidden threats embedded in third-party applications. To address this, the Air Force Life Cycle Management Center (AFLCMC) EZAS office is responsible for ensuring the security of all software deployed across Air Force platforms. However, with a small team manually reviewing software authorization packages of up to 300,000 pages per package, the process is unsustainable, delaying mission-critical deployments and increasing cyber risk. D&G Analytics proposes to extend its Software Integrity Platform (SIP) to provide automated, scalable software assurance beyond Windows-based applications, incorporating support for Linux, macOS, and Java-based software. This Phase II effort will enhance SIP’s ability to detect unknown software threats before deployment, integrating deep code inspection, AI-driven behavioral analysis, and automated rule-based threat detection. By leveraging the MITRE ATT&CK framework, SIP will systematically identify adversary tactics in software binaries, reducing the need for exhaustive manual reviews and accelerating approval timelines. The proposed solution is designed to integrate seamlessly with the Air Force’s software distribution infrastructure, automating the Integration, Inspection, and Identification of third-party software risks. SIP will achieve this by developing a Deep Code Inspection Engine capable of decompiling and analyzing multi-platform binaries, enhancing rule-set evaluation, and integrating with software repositories such as APT (Linux) and Jamf (macOS). These capabilities will enable real-time detection of supply chain infiltrations and provide EZAS with comprehensive software visibility. Beyond its defense applications, SIP has significant commercial potential. The global Zero Trust Security market is projected to reach $60 billion by 2030, with enterprises increasingly seeking automated software assurance solutions. D&G Analytics has secured commercial contracts with Equinix and AAA, demonstrating early market adoption. Expanding SIP’s capabilities beyond Windows will position it as a pioneering solution in the cybersecurity industry, helping organizations mitigate third-party software risks proactively. Through this Phase II effort, D&G Analytics will provide the Air Force with a scalable, automated software integrity solution, reducing operational risks and enhancing cyber resilience across mission-critical platforms. The project directly supports DAF’s Operational Imperatives by fortifying the software supply chain, ensuring that deployed applications meet the highest security standards before reaching Air Force and Space Force operations.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

5 SBIR/STTR records share this UEI (2024–2025). Reported award amounts total $4,476,937. Reported amounts are not federal obligations.

Phases: Phase II, Phase I, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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