Harnessing Predictive Threat Intelligence for Robust Operational Technology Security
The modern cybersecurity landscape is increasingly challenged by the speed, volume, and variety of cyberattacks, often outpacing the capabilities of human defenders. In the recent Gartner webinar, “Preemptive Cybersecurity – A Top 5 Disruptive Trend in Cybersecurity for 2025”, the analyst firm reports that “Preemptive cybersecurity will soon be the new gold standard for every entity operating on, in, or through the various interconnected layers of the global attack surface grid (GASG)”.
As ongoing digital transformation continues to integrate Information Technology (IT) with Operational Technology (OT), the need for an anticipatory security approach has never been more critical. Predictive Threat Intelligence (PTI) represents a paradigm shift away from the traditional reactive security models, focusing instead on identifying and preempting threats before they can impact highly sensitive OT environments.
PTI is designed to offer the “foresight” needed to take preemptive action, fundamentally changing the security posture from being a victim to being an active defender.
The Reactive Trap in Cyber-Physical Systems (CPS) Security
For years, the cybersecurity industry has been dominated by a reactive, “assume breach” mentality centered on detection and response. This mindset, in which the defender resigns themselves to the idea that it is not a matter of IF they will be breached, but WHEN, means that defender is knowingly accepting the role of a victim. While detection and response are crucial elements of a security program and must continue, relying solely on them is the “most expensive posture,” necessitating remediation and forensics after an attack occurs.
This reactive mindset is particularly perilous in Cyber-Physical Systems (CPS), Industrial Control Systems (ICS), and OT environments, such as manufacturing or utilities facilities. Here, a successful cyberattack results in process downtime, which carries severe financial consequences. For instance, a “back of the envelope” calculation of the cost of a factory being down is to take the annual revenue, divide it by 365 days, and then divide it by the number of facilities. Most will find that this cost generally outpaces the cost of the actual attack. Furthermore, many industrial systems and edge devices face limitations in deploying traditional security controls. This drives the need for more dynamic and non-invasive Automated Moving Target Defense (AMTD) techniques and predictive security approaches that address exposures before malicious campaigns execute.
Understanding How Predictive Threat Intelligence Works
Predictive threat intelligence relies on advanced prescriptive Artificial Intelligence (AI) and machine learning (ML) algorithms, drawing an analogy to a modern weather forecast system, which uses comprehensive monitoring, advanced modeling, and extensive sensor data to accurately predict weather. An advanced predictive threat intelligence system constantly observes the entire internet at the network metadata layer, collecting information regularly regarding routing announcements, DNS changes, IP addressing, and the movement of infrastructure between cloud providers (known as “jumping hosts”). Critically, this data is collected externally and does not require sensors within the customer’s network.
The machine learning algorithms convert these continuous snapshots of network changes into billions of infrastructure “behaviors”. The system is then trained using supervised learning, fed examples of historically known good and bad infrastructure behaviors. This training allows the system to establish a “knowledge graph” containing over 5 billion behaviors.
PTI functions by observing the behavioral changes of infrastructures, essentially monitoring the “devops of the criminal” as they set up their attack infrastructure. When an infrastructure that may have been stable for months begins deviating toward known malicious behaviors, the system assigns a predictive score. This process allows threat vectors to be predicted with remarkable anticipation, ranging from a median of three weeks up to nine months for complex threats like ransomware in the case of BforeAI PreCrime™ Intelligence.
Applying Predictive Threat Intelligence to OT Security Use Cases
The predictive methodology, centered on observing infrastructure behavior rather than content, is inherently threat-agnostic and robust against new attack techniques, making it highly applicable to diverse industrial environments. In fact, here at BforeAI, the very first customer use case for this predictive technology was in a manufacturing facility’s OT environment.
Key applications of PTI in OT security include:
Defensive Filtering for Perimeter Controls: PTI delivers machine-to-machine (M2M) actionable prediction data via API to existing peripheral security controls, such as OT firewalls and DNS resolvers. This enables preemptive blocking of communication with predicted malicious sources, mitigating infiltration, exfiltration, and command and control communication before the attack starts.
Network Allow Listing: In a manufacturing environment, customers employ PTI to identify benign behaviors and use those predictions to create allow lists, permitting only known good communications.
Supplier and Partner Impersonation Protection: Criminals often target suppliers because they are less protected than large corporations, using them as a trusted conduit. PTI helps protect against impersonation of third-party suppliers (like project management firms or facilities contractors such as plumbers or HVAC) who might be used for business email compromise or social engineering attacks against facility operators who often receive less security training.
Hybrid Environment Readiness: As IT and OT converge, particularly in remote operation scenarios (e.g., connecting a ship using Starlink to an operating center), PTI is relevant. Even air-gapped OT networks can receive this external intelligence because the technology is designed to work in such disconnected environments.
Benefits: Moving to Preemption and Deterrence
The primary advantages of adopting Predictive Threat Intelligence are measurable and transformative, particularly when compared to standard threat intelligence:
Superior Speed and Accuracy: In our case, PTI typically identifies threats an average of 18 days in advance of other detection-based threat intelligence tools. In 90% of cases, predictions outperform other security vendors in speed, often identifying threats more than three weeks ahead. This high performance is delivered with an exceptionally low false positive rate of less than 0.05%.
Disruption and Preemption: The rapid identification allows for immediate defensive measures, such as collaborating with global partners (like DNS providers and web filters) to block up to 85% of users protected from the malicious asset in as little as seven minutes. Concurrently, preemptive takedowns can be initiated with infrastructure providers (registrars, hosters), resulting in a high percentage of malicious infrastructures (as many as 93%) being taken offline before any content is ever loaded.
Cyber Deterrence: By consistently stopping attacks before the first victim is made and before criminals gain any return on investment (ROI), PTI increases the operational cost for the attackers. This predictable failure leads to a measurable deterrence effect, causing criminals to divert their attention to less secure targets.
Quantifiable ROI: PTI offers CISOs a valuable mechanism to quantify the cost and losses avoided due to preemptive blocking, enabling them to generate a strong Return on Security Investment (ROSI) KPI for board and management reporting.
Ultimately, cybersecurity leaders must strive to rebalance their security budget away from a total reliance on detection/response toward integrating prediction and preemption, thereby focusing human capabilities on managing unavoidable risks. This new philosophy prioritizes preparation and ensures resources are spent proactively mitigating risk.
This innovative approach, anchored by the PreCrime™ platform, enables organizations to preemptively address OT security challenges by delivering Predictive Threat Intelligence feeds to security controls, significantly enhancing protection before threats ever materialize.
Disrupt malicious infrastructure before it can be used in an attack
