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A military aviation and missile R&D center deploys AI agents to find vulnerabilities before adversaries do

Date

October 27, 2026

Type

Case Study

Topic

Agents

Government

Author

Seekr Team

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Agentic AI that identifies cyber, system, and mission vulnerabilities across missile defense and aviation weapon systems

Case study at a glance

Customer: A U.S. military research and development center for aviation and missile systems
Industry: Defense and national security
Challenge: Manual vulnerability analysis let cyber, system, and mission weaknesses go undetected
across critical weapon systems
Solution: SeekrFlow agentic AI models and workflows, built and fine-tuned for vulnerability
detection and threat modeling
Results: Contract awarded to identify vulnerabilities across the center’s weapon systems and
reduce the time, cost, and resources required to mitigate threats

The customer

The customer is a research and development center within a U.S. military service, focused on aviation and missile systems. Its work supports some of the nation’s most critical defense assets, including fielded air and missile defense systems.

The challenge

Adversaries are continuously developing, testing, and evolving new, unconventional methods to disrupt critical national defense systems, and their capabilities are getting more dangerous as
their technology advances.

The center relied on manual analysis to find weaknesses in its weapon systems. That approach couldn’t keep pace. Manual analysis created inefficiencies that allowed cyber vulnerabilities to go undetected, raising the risk of electronic warfare and adversarial AI threats to fielded assets.

The stakes are highest where the systems matter most. In missile defense, a vulnerability found after an adversary finds it is a vulnerability found too late.

The approach

Agentic AI built on trusted models

The center awarded Seekr a contract to deploy AI agents that identify cyber, system, and mission vulnerabilities across its weapon systems.

Purpose-built models and workflows

SeekrFlow builds and fine-tunes agentic AI models and workflows designed specifically for vulnerability detection, rather than relying on general-purpose models.

Threat intelligence-informed analysis

The agents operate in a threat intelligence-informed environment, where they identify system vulnerabilities and synthetically generate novel exploits.

Adversary emulation at machine speed

That capability lets the center pinpoint critical weaknesses and gives threat-emulation teams the means to model adversarial tactics where milliseconds matter.

The results

The center awarded Seekr the contract in early 2026 to secure critical mission functions across its weapon systems. Vulnerability detection and threat modeling are expected to reduce the time, cost, and resources required to mitigate threats, increase system resilience across missile defense and aviation assets, and replace manual analysis that left vulnerabilities undetected.

Why it worked

The customer needed precision and speed, and it needed both from models it could trust. Agentic AI on its own would have added speed. Building and fine-tuning the agents on trusted models, inside a threat intelligence-informed environment, gave the center results it could act on. The approach also turns defense from reactive to proactive. Instead of waiting for adversaries to reveal weaknesses, the center’s teams can generate novel exploits themselves and close the gaps first.

What’s next

The work starts with current air and missile defense platforms, but the threat doesn’t stop there. The same agentic approach applies to emerging threats against today’s systems and to the systems of the future, wherever the service needs to find a weakness before an adversary does.