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My experience with network security monitoring has been hands-on and spans various tools and techniques, all aimed at gaining visibility into network traffic to detect and respond to threats. I believe robust network monitoring is fundamental because the network is the artery of any organization; nearly all malicious activity, from initial access to data exfiltration, leaves traces there.
I've worked extensively with network intrusion detection/prevention systems (NIDS/NIPS), primarily Suricata and Snort. In my last role, we deployed Suricata sensors at key network choke points, including our internet perimeter and between major internal network segments. My daily routine included reviewing Suricata alerts, which could range from attempts to exploit known vulnerabilities to detection of malware command and control traffic. For example, if Suricata flagged an alert for "ET INFO EXE Download via HTTP" followed by an alert for "ET POLICY Possible External IP Lookup for Local System," I'd immediately investigate. I'd pivot to our SIEM, correlate these Suricata alerts with firewall logs, proxy logs, and DNS query logs for the source IP. I remember an instance where this chain of alerts led me to discover a user on a segmented guest network attempting to download an unauthorized executable, which our IPS then blocked, preventing a potential infection before it reached our internal production network. I've also contributed to fine-tuning Suricata rules, sometimes by creating custom rules based on specific IOCs from threat intelligence, or by suppressing known false positives after thorough investigation.
Beyond signature-based detection, I've used NetFlow/IPFIX data for anomaly detection and behavioral analysis. NetFlow provides summarized network session information – who talked to whom, when, how much data was transferred, and over what protocol. While it doesn't give full packet content, it's invaluable for spotting unusual traffic patterns at scale. For example, if I saw an internal host suddenly initiating large, continuous data flows to an unusual external IP address, especially outside of business hours, that would trigger an investigation. I recall a time I used NetFlow to identify a rogue internal device, possibly an unauthorized IoT device, making continuous connections to an external server on a non-standard port. It wasn't malware, but it was an unauthorized device potentially exfiltrating small amounts of data, which violated our security policy. NetFlow allowed me to quickly pinpoint the source internal IP and the destination, leading to the device's identification and removal.
I also have strong experience with packet capture and analysis using Wireshark. When a high-fidelity alert from our NIDS or SIEM pointed to suspicious network activity, and NetFlow didn't provide enough detail, I'd often resort to a full packet capture. Wireshark is an indispensable tool for deep-dive investigations. I've used it to reconstruct entire network sessions, examine malicious payloads, and understand the precise sequence of events during an attack. For example, investigating a suspected web application compromise, I used Wireshark to analyze HTTP traffic and identified unusual POST requests containing SQL injection attempts. I could see the exact malicious payloads being sent and the server's responses, which helped our development team patch the vulnerability accurately and quickly. This detailed level of analysis is often impossible without raw packet data.
In essence, my approach to network security monitoring is multi-layered. I leverage NIDS/NIPS for real-time threat detection and prevention, NetFlow for high-level anomaly detection and traffic visibility, and Wireshark for granular, deep-dive forensic analysis. This combination allows me to effectively detect, investigate, and respond to network-based threats.