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Threat intelligence and external attack surface management (EASM) give security teams critical visibility, but they can’t keep pace with AI-powered attacks.
Threat intel delivers Indicators of Compromise (IoCs), which guide response strategies and shape defensive actions. EASM maps exposed assets to help close known gaps. Each plays a key role, but neither can address the stage that decides whether an attack succeeds or fails– the stage that MITRE ATT&CK calls resource development.
The problem comes down to speed and timing:
Attacks now move faster than defenders. AI compresses reconnaissance, setup, and launch into minutes.
Detection starts too late. By the time Indicators of Compromise appear, attacker infrastructure is already live.
Defenders lose time and control. The gap between setup and detection gives adversaries a clear advantage.
Defenders can only close this gap by acting while adversaries are still building and configuring the infrastructure that supports their campaigns. In this blog, we’ll discuss why traditional visibility tools can’t keep pace, where their coverage ends, and how a pre-attack prevention approach closes that gap.
What These Tools Actually Do
Threat intelligence platforms and EASM tools are meant to give security teams a full view of the external threat landscape, yet they can’t deliver the whole picture.
Threat intelligence platforms supply data about adversaries, including malware signatures, attack methods, Indicators of Compromise and more. EASM systems identify an organization’s internet-facing assets and exposures. Both deliver visibility that reflects a single point in time. But feeds age, assets shift, and new exposure points appear faster than analysts can manually update their inventories. Even when they’re connected to SIEM or SOAR workflows, these systems still rely on post-event data. By the time intelligence confirms an attack pattern or an EASM scan identifies a new subdomain, adversaries have already weaponized that surface.
In order to reduce exposure, security teams need visibility into what happens before indicators appear or assets are exposed. They need to see attacker activity as it forms so they can stop it before it turns into an active threat.
The Blind Spot Between Visibility and Prevention
The core limitation of threat intelligence and EASM is perspective. Threat intel looks outward, collecting fragments of attacker activity with no direct link to a specific environment. EASM looks inward, cataloging an organization’s assets but missing the adversary’s view. Each works within its own field of vision, leaving a gap where those perspectives should meet.
That gap widens with speed. AI-driven reconnaissance now compresses setup and launch into minutes, while detection and containment still unfold over days or weeks. Attackers exploit this tempo difference to build and test infrastructure before any signal reaches defensive tools. The result is a blind zone that grows faster than analysts can close it – with defenders learning about attacks only after they start. Until that gap is closed, prevention remains out of reach.
Closing the Gap: From Visibility to Prevention
Threat intelligence and EASM remain essential parts of any defense program. Each provides valuable context about the environment, yet both operate in isolation. Threat intel focuses on adversary behavior across the internet. EASM focuses on the organization’s own attack surface. Pre-attack prevention connects these views by identifying where attacker setup activity overlaps with enterprise assets, brands, and customers- the intersection where intent becomes risk.
This correlation matters because attackers rarely build infrastructure in a vacuum. Domains, phishing portals, or staging servers often mirror legitimate naming conventions, reuse internal identifiers, or spoof brand elements to appear authentic. When those early signals are matched against internal asset data, defenders can see which setups are targeting them specifically and act before those resources are used in an attack.
Rather than replacing existing tools, pre-attack prevention strengthens them. It feeds validated, real-time intelligence into SOC, SIEM, and SOAR systems, reducing noise and response times. The result is faster action and measurable prevention.
The Malanta Approach
Malanta was built to close the space between visibility and prevention. The platform identifies Indicators of Pre-Attack (IoPAs) - signals that show what adversaries are building before an attack begins. These include early-stage infrastructure signals like new domain activity, staging environments, or spoofed portals that imitate enterprise assets. Malanta collects those signals at internet scale, correlates them with an organization’s brands and infrastructure, and validates which ones present real risk. Confirmed threats trigger automated takedowns and interdictions that remove attacker infrastructure before it becomes operational.
By operating at machine speed, Malanta converts early warning into direct action. The platform feeds verified intelligence into SOC, SIEM, and SOAR systems to strengthen existing defenses without extra effort. It turns early warning into measurable prevention, stopping attacks at setup, cutting dwell time to minutes, and defining readiness by how early defenders act, not how fast they recover.
The Bottom Line
Security leaders have spent years optimizing detection and response. That investment has value, yet it assumes the attack has already begun. The next frontier is acting before that point - intercepting infrastructure while adversaries are still preparing it. Pre-attack prevention makes that possible by shifting focus from compromise to intent.
Threat intelligence and EASM remain critical, but they only show what exists now. Pre-attack visibility reveals what is coming next. When defenders can spot early attack signals, confirm which ones are real, and remove malicious infrastructure before it’s used, prevention becomes measurable. A new metric - Mean Time to Preempt (MTTP) – can track how quickly teams detect and eliminate threats before launch.
The organizations that master this shift will define the next phase of cybersecurity maturity. They will stop chasing alerts and start eliminating threats before they materialize –redefining readiness for the age of AI.
