Episode 61 — Safeguard 13.3 – Anomaly detection
Welcome to Episode 61, Control 13: Visibility, Sensors, and Telemetry, where we explore how organizations observe what happens inside their networks. This control is about knowing what traffic flows where, how events are detected, and how data about those events is collected and stored. Visibility is not a single tool; it is an architecture of sensors, logs, and analytics that together make hidden activity visible. When done correctly, this capability shortens detection time, improves investigations, and gives leadership confidence that the environment is being watched. In practice, it requires technical design, clear placement of sensors, and a disciplined way to maintain the accuracy of the data over time.
The first design principle in visibility is to plan for both breadth and depth. Breadth means seeing all key network segments, cloud zones, and user endpoints. Depth means having enough detail in the data to understand what happened and why. Enterprises often start by defining the types of telemetry they need—network packets, flow summaries, endpoint signals, and system logs—then decide how much of each they can realistically capture. It is better to have consistent visibility everywhere than perfect visibility in only a few spots. Planning also means deciding what success looks like: how fast data should appear, how long it should be retained, and who is responsible for responding when anomalies occur.
Next comes the question of packet flow versus both packet and flow capture. Packet capture records every byte of traffic and is useful for deep forensics, but it consumes large amounts of storage. Flow capture summarizes connections, showing who talked to whom, when, and how much data was exchanged. Many organizations choose a mix of both. For example, they might use full packet capture at high-value choke points and flow data elsewhere. The tradeoff depends on network speed, regulatory needs, and the team’s ability to analyze the data. What matters most is that the chosen method can reveal unusual behavior quickly without overwhelming the defenders with unnecessary detail.
Placement of sensors determines whether the visibility effort succeeds. Sensors need to see both ingress and egress traffic, as well as lateral movement inside the network. They are typically deployed at strategic aggregation points—places where many paths converge or where critical systems reside. Proper placement balances coverage and cost. Too few sensors leave blind spots that attackers can exploit, while too many create duplicate data and operational overhead. A thoughtful layout based on traffic patterns and business processes keeps monitoring both efficient and effective.
At the network’s outer edge, sensors monitor the gateways connecting to the internet and between core aggregation switches. This is where attacks most often begin and where data may leave the enterprise. By capturing flow summaries or mirrored packets at these points, analysts can detect scanning, exfiltration attempts, and abnormal connections. Within the core, sensors provide insight into internal movement, helping identify infected hosts or misconfigured services before they spread problems further. Edge and core together form the foundation of any visibility architecture.
Visibility cannot stop at headquarters. Branch offices, remote users, and third-party connections also generate traffic that must be seen. Lightweight collectors or virtual sensors can run on local routers or firewalls, forwarding summarized data back to a central repository. For teleworkers, endpoint detection and response agents can capture network events from laptops even when off the corporate network. The key is consistency: every location and user type should produce telemetry in a compatible format, timestamped and ready for correlation with other sources.
In modern cloud environments, the same visibility principle applies inside virtual private clouds. Cloud providers offer traffic mirroring features that replicate packets or flow logs from virtual networks into monitoring systems. Using these features allows defenders to apply the same analytics used on-premises. Because cloud traffic is often dynamic and distributed, automation is critical. Scripts or orchestration tools must create, attach, and remove mirrors as instances come and go. This ensures that no workload is invisible, even for short-lived resources.
Within data centers, east-west segmentation—traffic moving between servers—requires special attention. Attackers often move laterally once inside, staying within the internal network. Placing taps or virtual sensors at key junctions between segments helps reveal these movements. Some organizations also use micro-segmentation firewalls that log connection attempts, producing telemetry even when they block the traffic. The goal is to make internal movement as observable as inbound or outbound activity, reducing the attacker’s room to maneuver undetected.
Encryption adds another layer of complexity. As more traffic becomes encrypted, the content of packets may be hidden, but metadata remains valuable. Analysts can look at patterns such as certificate use, session length, and server name indicators to detect anomalies. For example, malware may use valid encryption but connect to rare domains or change certificates frequently. Combining these metadata insights with endpoint and DNS logs allows detection without breaking encryption or compromising privacy.
Endpoint and host-based sensors, including endpoint detection and response tools, fill in what network sensors cannot see. They record process creation, file changes, registry modifications, and user actions. When correlated with network telemetry, they form a full picture of events. For instance, a network alert showing suspicious outbound traffic can be traced back to the exact process that generated it. Host telemetry also helps when devices are remote or connected intermittently, ensuring visibility even outside traditional network boundaries.
Choosing sampling rates for network flow collection and setting retention periods are practical design decisions. High sampling rates capture more detail but require greater storage and processing capacity. Low rates may miss brief connections used by attackers. A common approach is to adjust sampling dynamically, using higher rates for critical segments and lower rates elsewhere. Retention policies should align with investigation needs and regulatory obligations. Keeping at least ninety days of data is common, allowing analysts to trace slow-moving threats.
Time synchronization underpins all telemetry analysis. Even small clock drift between devices can cause confusion when correlating events. Using network time protocol servers or secure time sources ensures consistent timestamps across sensors, endpoints, and cloud services. This consistency makes it possible to reconstruct event sequences accurately. Regular checks should verify that all systems remain synchronized, especially after maintenance or power disruptions.
Data pipelines and storage design determine whether visibility data can actually be used. Raw logs and flow records must move from sensors into centralized systems where they can be queried efficiently. This often involves message queues, normalization steps, and indexing for fast search. Analysts should be able to filter by host, time, or behavior without long delays. Properly engineered pipelines turn massive data streams into practical intelligence. Performance tuning and access control ensure that sensitive telemetry remains protected yet available to those who need it.
Finally, visibility systems must be validated and tuned over time. Evidence of coverage and uptime demonstrates that sensors are working as intended. Dashboards can show which segments are reporting data, when the last record was received, and whether any gaps exist. Periodic testing—by simulating attacks or network changes—confirms that alerts appear where expected. Regular review of sensor health, storage capacity, and analytic performance ensures that the visibility program continues to serve its purpose: detecting what matters most.
As we wrap up this discussion, remember that telemetry is not an end in itself but a means to improve decision-making. By continuously refining placement, coverage, and tuning, enterprises turn raw signals into insight. Visibility, when thoughtfully implemented, becomes both a mirror and an alarm system—reflecting how the environment truly operates and warning when something is wrong. In the next phase of an organization’s security maturity, this capability supports automation, faster response, and a culture of evidence-based defense.
