Mount Laurel, NJ – June 1, 2025 – NetQuest Corporation, a worldwide leader in hyperscale network intelligence solutions, today announced a significant expansion of its NetworkLens™ enriched dataset portfolio. The latest addition to the NetworkLens Network Telemetry dataset category delivers detailed traffic characteristics of network management transactions — giving security teams the granular, AI-ready intelligence needed to detect threats hiding inside the very protocols used to manage and monitor network infrastructure.
The AI Advantage Starts With the Right Data
The cybersecurity industry has made massive investments in agentic AI, machine learning, and automated threat detection platforms. Yet the effectiveness of these tools is directly constrained by the quality, depth, and context of the data they consume. Data is the foundation. Without it, even the most sophisticated AI engine is flying blind.
NetworkLens™, powered by NetQuest’s Streaming Network Sensor (SNS) platform, addresses this challenge head-on by generating structured, context-rich network intelligence datasets engineered specifically to maximize AI-driven threat detection effectiveness. This latest expansion continues that mission — arming security pipelines with highly contextual telemetry data about network management transactions that legacy flow records simply cannot provide.
Legacy Network Management Protocols: A Soft Target
for Threat Actors
Network management protocols such as SNMP (Simple Network Management Protocol) have been foundational to network operations for decades. Their age and ubiquity, however, make them attractive targets for adversaries. Key threat vectors include:
- Plaintext authentication vulnerabilities — Broadly deployed SNMPv1/v2c relies on community strings transmitted in cleartext, enabling credential theft and unauthorized device access or reconfiguration.
- Network reconnaissance — Threat actors performing lateral movement routinely probe SNMP to enumerate network topology, query device configurations, and map high-value targets using Object Identifier (OID) requests.
- Insider and supply-chain abuse — Compromised monitoring systems, rogue contractors, or malicious insiders can issue unauthorized SNMP queries or configuration changes that are invisible without dedicated transaction monitoring.
- Polling storms and denial-of-service — Excessive SNMP polling can overload legacy devices and degrade performance — a tactic that is difficult to distinguish from misconfiguration without detailed transaction-level visibility.
- Brute-force credential attacks — Spikes in authentication failures, unknown usernames, or repeated transaction timeouts are key indicators of SNMP brute-force attempts that only become visible at the transaction record level.
Despite these risks, SNMP traffic has historically been an undermonitored blind spot — largely because existing telemetry tools lack the protocol-aware depth to generate actionable transaction records. NetworkLens changes that.
Expanding NetworkLens Network Telemetry:
SNMP Transaction Records
The new NetworkLens Network Telemetry datasets extend the platform’s capabilities beyond traditional flow metadata to include detailed transaction-level records for network management protocols. As an illustrative example, the new SNMP Transaction Record dataset uses Deep Packet Inspection (DPI) to automatically discover and decode SNMP traffic, correlate individual request-response pairs into bi-directional transaction records, and stream richly annotated records to downstream AI analytics pipelines via Apache Kafka.
Each transaction record captures the contextual fields that security AI models require to detect anomalous behavior: protocol version, community strings and usernames, security level, transaction method (GET, SET, TRAP, etc.), OID request and response varbinds, error status, and precise timing — all correlated into a single, AI-consumable record. This approach dramatically reduces the ETL burden on backend security platforms and delivers the transaction fidelity that modern threat detection demands.
“The promise of AI-driven cyber threat detection can only be realized when security tools have access to rich, contextual network data,” said Jesse Price, NetQuest CEO. “NetworkLens was purpose-built to close that gap, and this expansion into detailed network management transaction monitoring is a perfect example of that philosophy in action.”
Availability and Additional Resources
The new NetworkLens Network Telemetry datasets are available as part of the NetQuest Streaming Network Sensor platform. For detailed technical background on SNMP transaction monitoring and the threat landscape it addresses, visit the NetQuest SNMP Transaction Monitoring blog. To learn more about the full NetworkLens dataset portfolio, visit netquestcorp.com/networklens.
Availability and Additional Resources
NetQuest Corporation is a worldwide leader in hyperscale network intelligence solutions, delivering carrier-grade visibility and AI-ready datasets to network service providers, telecommunications operators, government defense agencies, national intelligence organizations, and security-focused enterprises. NetQuest’s NetworkLens™ portfolio, powered by the Streaming Network Sensor platform, provides the structured, context-rich network intelligence that modern AI-driven cyber threat detection requires. Learn more at netquestcorp.com.