How Observability Changes Proactive Government IT Security
Security visibility has traditionally been focused mostly on active threats. “Right of boom” teams looked for malware, suspicious behavior and evidence that someone had already entered the environment.
Threat hunting pushed that model further. Security teams could use threat intelligence to search for indicators of compromise, known malicious IP addresses or behavior associated with a particular attacker. This practice is sometimes called proactive but still focuses on active threats “right of boom.” Once an attack is identified, you are still reacting after it occurred.
These practices still matter. But today, proactive security also means looking for weaknesses before an attacker exploits them.
The question is no longer simply, “Is someone attacking us?”
Security teams also need to know whether a system has been exposed in a way that violates policy, if a critical vulnerability remains open or whether sensitive data has been placed in a service without the required controls.
That shift is central to observability. A truly proactive security operations center puts focus on today’s “left of boom” exposures that turn into tomorrow’s “right of boom” threat hunts and active attacks.
READ MORE: Continuous threat exposure management is a risk-driven approach.
Treat Exposures With the Urgency of Active Threats
Many state and local agencies have well-developed procedures for active cyber incidents. Once an attack is detected, teams know how to escalate it. Incident response, forensics and case management resources may all come into play.
We need to apply similar urgency to critical exposures.
Consider a cloud storage resource that has been exposed to the internet without proper identity and access management policies. Or an employee who creates a cloud-based data warehouse platform and begins putting production data into it without multifactor authentication or other required controls. This happens all the time.
The security team needs to know that resource exists before it becomes part of an active incident.
That requires visibility into where systems and data are located, how they are configured and whether they comply with the organization’s security standards. Once an exposure appears, the organization can assess it and take action.
This is also why Gartner’s continuous threat exposure management (CTEM) framework has gained attention, with agencies such as the Cybersecurity and Infrastructure Security Agency recommending continuous monitoring approaches. Vulnerability scanning has been part of security programs for decades, but weekly or monthly scans provide only a snapshot. The environment can change immediately after the scan is completed.
A continuous approach gives security teams a better chance to identify exposures as systems appear, disappear or change configuration.
LEARN MORE: Cyber resilience helps agencies to harness AI infrastructure.
Scheduled Scans Are Insufficient for Government Cybersecurity
State and local governments also face a challenge that private sector organizations do not always encounter in the same way: Cyber risk can be difficult to express in financial terms.
A company may be able to identify a revenue-generating system, estimate what an outage would cost and calculate the value of a security investment against that number.
But government agencies often have different measures of value. The impact of an unavailable public service or compromised government system does not always translate neatly into lost revenue.
That makes standards especially important.
Government organizations often rely on frameworks and defined security requirements to establish what acceptable security looks like. Federal zero-trust initiatives are one example of an effort to move organizations away from older, perimeter-based security assumptions and toward a defined set of modern security practices.
Observability supports that work by showing security teams where systems fall outside those requirements.
Artificial intelligence actually has an important role here. AI is really good at analyzing exposure data and suggesting possible remediation based on the context surrounding an issue. Some remediation can be automated; other cases still require a person to decide what action makes sense.
The important change is the frequency of the work. Every new exposure requires discovery, prioritization, analysis, validation and mobilization.
If an agency waits for the next weekly, monthly or quarterly scan to discover a dangerous configuration, that exposure may remain open for weeks. CTEM gives security teams the chance to find it much sooner — while it’s still just an exposure rather than an active incident.
