Ed Higgins | Security Insights | CISO Perspective on Relevant Topics

When Exploits Move at Machine Speed, Defense Must Too

By Ed Higgins, Exec Director, Security & Compliance

The cybersecurity world is about to experience a shift that many are underestimating.

Emerging AI research efforts like Project Glasswing and capabilities previewed in models such as Claude Mythos point toward a future where large-scale models can systematically analyze vast codebases, historical CVEs, and system architectures to identify patterns of weakness across every major operating system lineage. By combining this knowledge with generative capabilities, these systems can simulate exploit development in near real time, rapidly testing, refining, and producing viable attack paths with minimal human involvement.

While not yet fully realized at scale, and thankfully relegated to but a few of the largest security researchers, the trajectory suggests a world where vulnerability discovery and weaponization are no longer constrained by human speed but instead operate continuously, autonomously, and at light speed fundamentally shifting the balance between attackers and defenders.

Projects like Glasswing and emerging AI model capabilities such as Claude Mythos Preview represent a new phase, not just in AI innovation, but in how vulnerabilities are discovered, understood, and ultimately exploited.

Sure, these tools are currently positioned for research and advanced development scenarios,  the trajectory is quite clear:

The time between vulnerability disclosure and weaponization has collapsed

From Days to Minutes: The New Exploit Timeline

Historically, defenders had time.

A vulnerability would be disclosed.
Security teams would assess exposure.
Patching cycles would begin.

Even if imperfect, there was a window.

AI is closing that window.

Emerging AI capabilities can:

• Interpret CVEs instantly
• Generate exploit logic with minimal input
• Simulate attack paths across environments
• Refine payloads iteratively

What once required skilled adversaries and time now requires access and intent.

This is not theoretical. It’s inevitable.

The Real Risk: Scale + Speed + Accessibility

The real concern isn’t just sophistication it’s accessibility at scale.

When these capabilities mature and inevitably reach broader audiences, we will see:

• Faster exploitation of unpatched systems
• More adaptive and evasive attack patterns
• Increased success rates for low-skill attackers

Attackers will operate at machine speed

Why Traditional Vulnerability Management Breaks

Most vulnerability management programs today are built on:

• Periodic scanning
• Manual prioritization
• Scheduled patch cycles

That model assumes:

• Human-paced attackers
• Predictable exploit timelines

Those assumptions are no longer valid.

You cannot defend at quarterly or even weekly speed against threats that evolve hourly

Reimagining Defense “At the Speed of the Wire”

At Quisitive, we’re rethinking vulnerability detection and response with a simple premise:

If attackers are accelerating with AI, defenders must operate with AI-assisted velocity

This means shifting from:

• From Reactive to Predictive
• From Periodic to Continuous
• From Manual to Augmented

In practice, this shows up as:

• Continuous exposure monitoring instead of periodic scans
• Risk-based prioritization tied to active threat signals
• Integrated detection and response across identity, endpoint, and cloud

Organizations that are beginning to move in this direction are already seeing the benefit of shortening their exposure windows, not just identifying risk, but actively reducing it in near real time.

Where Microsoft’s Security Stack Changes the Game

Microsoft’s ecosystem provides a foundation to meet this moment when used together, not in isolation.  However, this is not a silver bullet for the challenges what’s coming our way…

Microsoft Defender – Continuous Exposure Awareness

Defender plays a critical role in:

• Identifying vulnerable assets in real time
• Mapping exposure across endpoints, identities, and cloud workloads
• Prioritizing vulnerabilities based on actual risk—not just severity

In an AI-driven threat landscape, knowing what is exposed immediately is now table stakes.

Organizations that operationalize these insights, rather than just report on them, are far better positioned to act before vulnerabilities are exploited.

Microsoft Sentinel – Correlating the Signal

As attack patterns become more complex and faster-moving, correlation becomes critical.

Sentinel enables:

• Cross-domain visibility (identity, endpoint, cloud, network)
• Detection of anomalous behavior patterns
• Rapid identification of potential exploitation attempts

This is how organizations move from: “We have a vulnerability” to “We are actively being targeted”. 

Teams that mature here begin to treat vulnerability management as a live security signal, not a static backlog.

Security Copilot – Compressing the Response Timeline

Perhaps the most important shift comes from Security Copilot.

Not as a replacement for security teams, but as a force multiplier.

Security Copilot enables:

• Instant interpretation of new vulnerabilities and threats
• Rapid generation of detection logic and hunting queries
• Accelerated incident investigation and response

When new exploit techniques emerge, Copilot helps teams:

Understand faster, act faster, and close gaps before they are exploited

For organizations exploring this space, the biggest gains come when Copilot is integrated into existing workflows not treated as a standalone tool.

The Future of Patching: From Schedule to Signal

Patching itself must evolve.

The future is not:

• Monthly cycles
• Static prioritization

The future is:

• Risk-triggered remediation
• Real-time prioritization based on active threats
• Automation where confidence is high

We’re seeing leading organizations begin to shift toward models where:

• Vulnerabilities tied to active threat signals are prioritized immediately
• Remediation workflows are partially automated
• Security and operations teams are aligned around shared risk signals

This is where vulnerability management becomes a security capability, not just an IT function.

A Call to Action

The question is no longer: “Are we managing vulnerabilities?”

The question now is: “Can we respond at the speed attackers now operate?”

Organizations that are beginning to ask this question are often taking a step back to:

• Reassess how quickly they can detect exposure
• Evaluate how long it takes to act on critical vulnerabilities
• Identify where automation and AI can reduce response time

Final Thought

AI will not just change how we build and work. Frankly, that has already happened.

It is fundamentally changing how we are attacked, and crucially how we must defend.

Organizations that continue to rely on traditional vulnerability management models will find themselves outpaced. Those who embrace AI-assisted defense, continuous visibility, and rapid response will be the ones who stay ahead.

At Quisitive, our Spyglass and AI Strategy teams are actively working to modernize how we detect, prioritize, and respond to vulnerabilities, aligning security operations to move at the same speed as emerging threats.

If you’re starting to rethink how your organization approaches vulnerability management in an AI-driven threat landscape, now is the right time to begin that conversation.

Until next time,

Ed Higgins