Redefining Cyber Defense with Adetomiwa Dosunmu Driving Threat-Informed Protection Across the Enterprise

By Ugo Aliogo

In today’s digital battlefield, the greatest risk often lies not in the attacks themselves, but in the assumptions, organizations make about their defenses. Enterprise security controls are frequently deployed with confidence yet remain untested against the sophisticated tactics adversaries actually use. Closing this gap requires a new approach one that measures, validates, and continuously improves security control effectiveness at scale. Through threat-informed defense engineering models, Adetomiwa Dosunmu is driving this transformation, turning cybersecurity from a posture of belief into one grounded in evidence, where every control is proven to withstand real-world threats.

He centers his methodology on the principle that defenses must be evaluated in the context of real threat behavior. Threat-informed defense engineering models use intelligence about adversary tactics, techniques, and procedures to create realistic simulations that directly test how well security controls perform. Rather than relying on generic compliance metrics, he advocates for assessments aligned to credible threats relevant to the organization. This alignment ensures that measurements reflect actual risk, enabling security teams to prioritize improvements based on what attackers are most likely to exploit.

At scale, this model becomes a powerful engine for continuous validation. Large organizations operate hundreds of controls across multiple regions, networks, and technologies, making manual testing impractical. By leveraging breach and attack simulation platforms and structured threat scenarios, he enables repeatable testing across environments. This allows security teams to evaluate detection, prevention, and response capabilities consistently, revealing gaps that traditional audits or static assessments often miss.

A key strength of his approach is its focus on measurable outcomes. Security effectiveness is not defined by the presence of tools, but by their performance against adversary behavior. Through threat-informed models, he supports quantifiable metrics such as detection coverage, alert accuracy, response latency, and control resilience. These metrics transform security conversations, providing leadership with concrete evidence of how controls perform before and after remediation. As a result, improvement is no longer anecdotal but demonstrable.

He also emphasizes the importance of control-level validation. Rather than blocking threats at the perimeter alone, his models test whether controls operate as designed throughout the kill chain. Firewalls, endpoint protections, intrusion prevention systems, logging platforms, and identity controls are validated against realistic attack paths. This layered testing exposes dependencies and failure points that may remain hidden when controls are evaluated in isolation. The result is a more accurate understanding of enterprise defense readiness.

Collaboration plays an essential role in turning measurement into impact. By working with cross-functional teams, he ensures that findings from threat-informed testing led to meaningful remediation. Security engineers, infrastructure teams, and application owners gain clear insight into where controls fail and why. By tracking improvements from identification through resolution, he helps embed accountability into the defense process. This collaborative execution model accelerates risk reduction while maintaining business continuity.

Another defining feature of his work is adaptability. Threat-informed defense engineering recognizes that attackers evolve rapidly, and measurement models must evolve with them. Static test cases quickly lose relevance as threat actors adopt new techniques. He supports continuous refresh of threat scenarios based on emerging intelligence, ensuring that control effectiveness is measured against current and high-impact attack methods. This adaptability allows security programs to remain resilient despite changing threat dynamics.

His models also enhance strategic security planning. By aggregating results across regions and systems, organizations gain a macro-level view of control effectiveness at scale. Patterns emerge that highlight systemic weaknesses, duplicated controls, or underperforming technologies. This insight supports smarter investment decisions, enabling leaders to direct resources toward improvements that deliver the highest risk reduction. In this way, threat-informed measurement becomes a driver of efficiency as well as resilience.

Beyond technology, his work reinforces a culture of proof within cybersecurity teams. Engineers are encouraged to test assumptions, validate configurations, and learn from outcomes rather than rely on vendor assurances or legacy practices. This mindset strengthens organizational maturity, fostering teams that are confident in their defenses because they have been tested, challenged, and improved continuously.

Adetomiwa Dosunmu also brings visibility to the role young black professionals play in shaping the future of cybersecurity engineering. By leading complex, data-driven security validation efforts, he demonstrates that strategic insight and technical depth are inseparable in modern defense leadership. His work helps challenge outdated narratives about cybersecurity roles, highlighting the importance of diverse perspectives in confronting sophisticated adversaries.

As enterprises face growing pressure to justify security investments and demonstrate resilience, threat-informed defense engineering models offer a compelling path forward. Through his focus on realism, measurement, and scale, Adetomiwa Dosunmu is helping organizations answer the most important security question with confidence: do our controls work when it matters most.