A more complete picture: How IP reputation adds further insight to cyber underwriting

For cyber underwriters, assessing risk involves understanding what an organization exposes to the internet and how effectively it governs and protects that exposure. Indicators such as misconfigured domains, weak email authentication, open ports, and outdated software remain central to this process, offering reliable insight into cyber hygiene and the presence of protective measures at the point of risk selection.

But as cyberattacks accelerate and automation scales, incorporating additional indicators can help reveal hidden exposure that is increasingly relevant to the scale of automation reshaping the internet.

For the first time in over a decade, automated traffic has surpassed human activity, accounting for 51 percent of all web traffic. Of that, malicious bots alone represent more than a third of total traffic. In practical terms, the majority of what interacts with an applicant’s infrastructure today is not human, and a significant proportion of it is actively hostile.

For underwriting, this can shift the baseline. When traffic is predominantly automated and a substantial share is malicious, exposed services are probed continuously. Login portals are tested. Misconfigurations are scanned at scale. The question is no longer simply whether an organization appears vulnerable, but whether its infrastructure is actively being tested, misused, or leveraged in ways that increase loss probability.

In this environment, configuration and control indicators remain essential, but curated insight drawn from IP reputation data can introduce an additional layer of risk intelligence. It highlights when an organization’s IP addresses show patterns associated with suspicious or malicious activity, enabling clearer risk differentiation and more defensible underwriting decisions.

But what exactly is IP reputation, and what does it mean for an underwriter in practice?

What curated IP reputation data reveals about organizational risk

IP reputation examines how an organization’s internet-facing infrastructure behaves once it is live and interacting with the broader internet.

Every organization uses IP addresses to run email, host websites and applications, enable remote access, and connect cloud services. Over time, those IP addresses build a history based on how they are observed behaving. Security providers, internet service providers, and threat intelligence networks monitor patterns such as spam activity, scanning behavior, malware hosting, or communication with known malicious systems.

When an IP address is repeatedly linked to suspicious or abusive behavior, it may be listed in reputation databases or blocklists that other security tools reference. There is no single global “score,” but many filtering systems rely on shared intelligence feeds when deciding whether to trust traffic from a particular source.

These mechanisms have clear operational implications. Email gateways, firewalls, and cloud platforms often use reputation data to determine whether to allow, filter, or block traffic. If an organization’s IP space develops a poor reputation, it may experience email delivery issues, connection restrictions, or additional scrutiny from third-party systems. Reputational degradation can therefore create operational disruption in its own right.

For cyber underwriters, the value lies not in the operational impact itself, but in curated IP reputation insight that highlights observable activity associated with an applicant’s infrastructure, filtered for relevance to loss potential rather than day-to-day network management.

For example, if IP addresses associated with an applicant are observed performing brute-force attacks – repeated automated attempts to guess login credentials – this may suggest compromised systems attempting to access other networks. If infrastructure is communicating with known command-and-control (C2) servers – systems used by attackers to remotely control infected machines – this can indicate active malware within the environment. If domains linked to the organization are hosting phishing pages designed to steal credentials, that introduces not only technical exposure but potential regulatory and reputational consequences. If mail servers appear on spam blocklists, this often points to botnet activity or weak email security controls.

These signals do not automatically prove a breach has occurred. However, they are consistent with control failure, insufficient internal monitoring, or infrastructure misuse.

In practice, IP reputation signals tend to fall into two categories that matter for cyber underwriters.

• Inbound signals show that an organization is being actively targeted. For instance, repeated scanning from known malicious IP ranges suggests that exposed services are visible and being tested. Similarly, inbound traffic originating from proxy networks, Tor exit nodes, or suspicious hosting providers may indicate attempts to mask identity or bypass controls. This is not evidence of compromise, but it increases the likelihood that vulnerabilities will be identified and exploited quickly.
  
  

• Outbound signals are more concerning. When infrastructure associated with an applicant is observed sending spam, launching brute-force attempts, scanning other networks, or communicating with confirmed C2 infrastructure, the probability of active compromise rises significantly. At that stage, the focus shifts from theoretical exposure to containment capability and monitoring effectiveness.

It is also important to recognize that attackers deliberately exploit reputation dynamics. Compromised legitimate infrastructure is often used to send spam or host malicious content because it initially appears trustworthy. In other cases, attackers rotate IP infrastructure frequently to avoid detection. Either way, the behavioral trace is often visible externally before an organization realizes something is wrong internally.

Examples of behavioral signals revealing hidden risk

To see how behavioral signals complement underwriting risk assessment, let’s take a look at real-world patterns where IP reputation adds important context to the overall risk profile.

• Hijacked or misused domains
  
  Organizations often register additional domains for marketing campaigns, defensive registration, or future projects, but those domains are not always actively managed. If a secondary domain has outdated DNS settings, which determine where its internet traffic is directed, or weak email authentication controls, attackers can exploit it to send spam or host phishing pages. In recent studies of malicious domain activity, researchers have identified thousands of newly registered or compromised domains used for phishing and other attacks, demonstrating how quickly overlooked or low-cost domains can be weaponized.
  
  In these situations, risk analysis may indicate that the organization’s registered domains and core systems are correctly configured at a point in time. Behavioral signals, such as an IP address linked to a secondary domain appearing on phishing or spam blocklists, can surface issues as those assets are used or misused in practice. That external activity draws attention to governance gaps across the broader digital estate, not just the flagship domain.

• Compromised infrastructure becoming part of a botnet
  Servers and devices that appear secure from the outside can still be compromised through stolen credentials, supply chain issues, or vulnerable third-party components. Once compromised, these hosts may be quietly enrolled in a botnet and begin scanning external networks or launching brute-force attempts. Observable external activity may reveal unusual outbound behavior from those IP addresses, even if internal monitoring has not yet flagged any issues. Botnet membership and related abuse have been studied for years and are well-established drivers of malicious traffic and reputational damage.
  
  

• Open resolvers and DNS abuse
  

  DNS can itself be a vector for misuse. A misconfigured DNS server can act as an “open resolver,” responding to requests from anywhere. Attackers exploit open resolvers in amplification attacks, where a small query generates a large response that overwhelms a target, contributing to some of the largest distributed denial-of-service (DDoS) events in history. In a major DDoS attack against a global spam-tracking organization, attackers leveraged vulnerable DNS resolvers to generate massive traffic floods.

  From an underwriting perspective, this is not just a technical oversight. It indicates gaps in ongoing control management and monitoring, and the behavioral footprint may appear on abuse databases long before anything is noticed internally.

• Early signals of phishing and credential theft
  Attackers increasingly use newly registered or compromised domains to support phishing campaigns that harvest credentials or deliver malware. In recent research into malicious domain usage, analysts identified hundreds of phishing sites positioned just ahead of credential-stealing forms, often hosted on domains that appeared innocuous at first glance.
  
  This kind of behavior, where infrastructure associated with an organization is used to funnel traffic into scams, can be detected in IP reputation feeds even when risk assessments show few vulnerabilities.

These examples illustrate a broader truth: individual configuration issues may seem isolated or low priority on their own. But when infrastructure begins to behave in ways associated with abuse, such as spam, scanning, brute-force activity, phishing hosting, or DNS exploitation, that external footprint provides additional, valuable risk signals.

By layering IP reputation data onto asset-level risk analysis pre- and post-bind, underwriters gain greater visibility into how an organization actually performs when exposed to real-world threat activity.

Focusing on insight that supports decision-making

As cyber activity becomes increasingly automated and infrastructure-driven, highly curated and focused IP reputation intelligence can provide underwriters with additional risk signals without overwhelming them with data that does not translate into action.

By surfacing observable misuse that correlates with control breakdowns, monitoring gaps, or active compromise, it brings relevant behavioral signals directly into the underwriting process and helps focus attention on indicators with a demonstrable link to loss.

At KYND, our focus has always been on identifying the external signals that demonstrably correlate with cyber loss, not just theoretical exposure. Integrating curated IP reputation insights into underwriting workflows strengthens that approach by adding observable behavioral context to traditional control assessments. As automation continues to reshape the threat landscape, underwriters who combine configuration analysis with behavioral intelligence will be better positioned to differentiate risk, price accurately, and defend their decisions with confidence.