How Reveal(x) 360 Works

Behind the curtain on SaaS-based network detection and response

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Getting Started


Reveal(x) 360 Components and Cloud-Hosted Services

Reveal(x) 360 is a SaaS-based network detection and response (NDR) solution that provides unified security across on-premises and cloud environments, 360-degree visibility and situational intelligence without friction, and immediate value with a low management burden.

To start using Reveal(x) 360, identify the environments you want to secure. Reveal(x) 360 sensors work across edge (IoT and remote workforce), core (on-premises data centers and branch offices), and cloud (AWS, Azure, and Google Cloud) deployments.

In public cloud environments, Reveal(x) 360 leverages traffic packet mirroring features from cloud service providers—Amazon VPC Traffic Mirroring, Google Cloud Packet Mirroring, and the announced Microsoft Azure Virtual Network vTAP.

How it Works Diagram

ExtraHop sensors deployed locally in data centers, clouds, and remote sites decrypt and process network data, extracting records and de-identified metadata which are sent securely to Reveal(x) 360 for behavioral analysis, real-time threat detection, and investigation.

Real-time threat detection enables confident response to security incidents, including taking automated action on compromised workloads, domains, and IP addresses.

Through the Reveal(x) 360 cloud-based record store with 90-day lookback, you can conduct index record search, query, and drill-down investigation in every segment of your hybrid environment for situational intelligence. A cloud-hosted control plane––accessible from anywhere via the secure web-based Reveal(x) 360 user interface––provides a unified view of the environments where sensors are deployed.

Each Reveal(x) 360 sensor comes with record capacity based on the sensor size, and you can purchase additional bands of record capacity or leverage on-demand pricing for more flexibility. Record capacity is calculated at the account level by aggregating capacity across all sensor sizes. For pricing information, visit our Reveal(x) 360 pricing page.

ExtraHop Technology


Technical deep dive into network detection and response

Real-time Stream Processing

ExtraHop's real-time stream processor transforms unstructured network packets into structured wire data at line-rate. Depending on the type of traffic, protocols involved, and security policies applied, a variety of processes are performed in real time:

1. Line-Rate Decryption

For encrypted traffic, the stream processor decrypts SSL/TLS 1.3-encrypted traffic, including cipher suites that support perfect forward secrecy (PFS), at line rate. This bulk decryption can scale to 64,000 SSL transactions per second (TPS) using 2048-bit keys, which no other real-time analytics engine can match in a single unified offering. Check out this technical brief for specifics on our decryption methodology, and this blog post for more information on TLS 1.3.

2. High-Performance TCP State Machines

Starting at the most fundamental level, the stream processor recreates the TCP state machines for every sender and receiver communicating on the network. A prerequisite for deeper application-protocol analysis, this allows the platform to understand all TCP mechanisms and their impact.

3. Wire-Protocol Decoding and Full-Stream Reassembly

The real-time stream processor decodes 70+ protocols (skip to Protocols We Decode) to understand, define, and act on that protocol's unique application boundaries in hybrid and cloud IT environments. This allows the processor to construct complete flows, sessions, and transactions for total application fluency, which in turn allows for higher-order content analysis through full-stream reassembly into wire data (derived from the wire protocol itself). The processor will even automatically resynchronize and recover in the event of traffic anomalies such as microbursts, that might otherwise result in packet loss.

4. Full-Content Analysis

After reassembling packets into full streams, the stream processor analyzes the payload and content from layers 2-7, auto-discovering and classifying all devices and clients communicating on the network. The processor also continuously correlates relationships between clients, applications, and infrastructure with 5,000+ built-in metrics.

Full-content analysis supports dozens of protocols, providing key performance indicators such as database methods used, file access by user, storage errors, DNS records and errors, web URI processing time and status codes and SSL certificates with expiration. The stream processor also captures sophisticated network metrics such as receive-window throttles, retransmission timeouts, and Nagle delays.

5. Fully Programmable Telemetry

While full analytics capabilities are always available, it's also easy to customize results so you only see the precise metrics and insights that you need.

An event-driven programmable interface enables you to customize the telemetry captured by the stream processor. You can programmatically extract wire data events and threat indicators that are specific to your organization.

With this Application Inspection Triggers functionality, you can be as surgical or as verbose as necessary to extract anything from a simple header to the full application payload. For example, this data can include specific HTTP or SQL query strings used in injection attacks.

The same principle and functionality holds true for all of our natively decoded protocols. You can also use triggers to extract, measure, and visualize data from defined fields, or to decode proprietary protocols based on TCP and UDP.

Machine Learning and Global Intelligence

Real-time intelligence derived from petabytes of anonymized threat telemetry collected daily makes Reveal(x) 360 cloud-based machine learning uniquely reliable—all without impacting sensor performance. Cloud-scale machine learning provides more than 1 million predictive models for a typical enterprise deployment to identify suspicious behaviors and potential threats. ExtraHop's machine learning service detects cyber kill chain behaviors such as reconnaissance, exploitation, lateral movement, command and control, and actions on objective. ExtraHop ML also provides coverage for the MITRE ATT&CK Enterprise Matrix and detects ransomware, botnets, unauthorized data exfiltration, and much more.

Machine Learning Algorithms

Reveal(x) 360 uses a suite of machine learning algorithms to provide advanced, SaaS-based network detection and response, including:

  • Attack detection - Hundreds of self-adaptive unsupervised attack-detection models leveraging proprietary time series analysis and outlier detection algorithms.
  • Entity importance - Inference engine for inferring entity importance and entity network privilege level based on observed behaviors and innovative graph analytics.
  • Device identification - Entity clustering engine for identifying behaviorally similar devices.
  • Peer group identification - Peer group outlier detection engine.
  • Risk score determination - Risk score estimation engine that combines domain expertise and customer base telemetry.

Continuous Global Intelligence

Reveal(x) 360 automatically updates detectors, threat intelligence feeds, and IoT profiles via the cloud, eliminating the need for manual intervention to ensure that policies or software on sensors are always up to date.

Customer Data Security

Only de-identified metadata is sent to ExtraHop's cloud-based machine learning service, meaning that no payloads, filenames, strings, or other data categories that might contain sensitive data will leave your protected environment. ExtraHop has received SOC 2, Type 1 compliance certification for our machine learning technology, which you can learn about on our Compliance page.

ExtraHop machine learning performs the following processes:

  1. Network traffic is analyzed locally to extract and store 5,000+ metrics including IP addresses, URIs, database queries, CIFS filenames, VoIP phone numbers, and other potentially sensitive data. Metrics collection can be customized as needed.
  2. A subset of these metrics are de-identified and sent to a customer-dedicated cloud-computing instance operated by ExtraHop.
  3. ExtraHop ML then compares device and application behavior against predictive models and flags any significant anomalies.
  4. Anomaly events are sent back to your environment, where you can re-identify and decrypt them with your private key for alerting and investigation.

Cloud Record Store and Data Indexing

ExtraHop leverages the power of the cloud to provide scalability as businesses grow or security needs fluctuate. By providing cloud-based record storage, Reveal(x) 360 transforms both how and where NDR capabilities can be deployed, and how and when they can be consumed. When required, enterprises can now augment record capacity by utilizing cost-efficient upfront capacity reservations, pay-for-use record capacity as needed, or both methods—making unpredictable loads manageable and providing value for customers with more predictable needs.

From a SecOps perspective, a cloud-based record store provides fully hosted and managed search capability for streamlined incident investigation. Security teams can also leverage index record search and query of data from every segment of the hybrid environment for 360-degree visibility and situational intelligence.

Data Visualization and Exploration

One of the most challenging aspects of real-time analytics at cloud scale is, well, the scale itself. At ExtraHop, we do our best to make this easy for you as a user to parse the immense wealth of information that is wire data and derive meaningful insights no matter which perspective you're coming from.

We start you off with a simple, intuitive user interface for teams across your organization.

Customized Dashboards

ExtraHop enables you to create bespoke dashboards quickly. Drag-and-drop functionality enables you to build dashboards with widgets; if you want to create your own widget, all you have to do is select your desired data source and metrics, pick a visualization type, and save it to your dashboard of choice. You can quickly and easily export charts and background data points to PDF, Excel, or CSV.

No Scripting? No Problem.

Our visual query language gives you the power to refine or change your search queries by clicking UI elements that control everything from grouping, to filtering, to time-range selection. Whether you stick with the hundreds of built-in record attributes or branch out and define your own, this functionality means any user can quickly answer questions during an investigation without needing to learn a query language.

For example, if you sort SQL messages by query string, you can identify attempted SQL injection attacks, pinpoint the malicious IP, and then instantly pivot to see all the activity of that client on the network over a given length of time. By exporting that information to Excel, CSV, or a visualization tool like Tableau or Qlik, you'll have a step-by-step map of what the attacker did so you can both respond with confidence and be better equipped to prevent future attacks.

Live Activity Maps

Along with traditional methods of data visualization like charts and graphs, ExtraHop uses live activity maps to present a dynamic and intuitive view of your environment. Instead of manually creating and updating network diagrams as your IT environment changes, you can use live activity maps to visualize protocol-based connections between devices and applications in real time.

By allowing you to filter by time interval and broaden or narrow your scope as needed, activity maps make it easy to answer multi-part questions like, "How are devices interacting within a certain tier, and how have those devices been interacting across the network in the last hour?" Anomalous behavior detections also appear on live activity maps, so you can see the context of the detection before clicking down into the transaction or even into the precise packets straight from the map.

This blog post goes into a lot more detail about the latest capabilities of live activity maps and provides some more ideas about how you might use them in your day to day.

Protocols We Decode

ExtraHop decodes the following enterprise protocols with real-time fluency at the application layer. Protocol modules offer varying levels of analysis, starting with L7 classification, and Application Inspection Triggers allow you to create a custom metric.

AAA: RADIUS ActiveMQ HTTP-AMF ARP
AAA: DIAMETER AJP DSCP GRE
CIFS DICOM* iSCSI ICMP6
Citrix ICA* HL7* MS-RPC IEEE 802.1X
DHCP LLDP WebSocket IKE
DNS MSMQ SSL IMAP
Database: DB2 Telnet SSH IPSEC
Database: Informix SMTP SMPP* IPX
Database: Microsoft SQL VoIP: SIP* VoIP: RTP* IRC
Database: MongoDB VoIP: RTCP XR* VoIP: RTCP* ISAKMP
Database: MySQL Redis POP3 LACP
Database: Oracle NFS Memcache L2TP
Database: Postgres LDAP Kerberos MPLS
Database: Sybase VNC Syslog NTP
Database: Sybase IQ ICMP IBM MQ OpenVPN
FIX* STP SNMP RCoIP
FTP HTTP/S RDP CDP

* Not included in Reveal(x) 360 base license

Of particular interest to SecOps analysts, Reveal(x) 360 analyzes application-layer metadata for databases, Active Directory, web, SSL, and storage systems:

Database: RDBMSs: Oracle, Microsoft SQL Server, MySQL, PostgreSQL, Informix, Sybase, and DB2. NoSQL databases: MongoDB, Memcached, Redis, Riak. Metadata extracted include transaction timing, table/user access patterns, query errors, SQL queries and responses, and system-level commands.

Identity and Access Management: Active Directory visibility (includes LDAP, Kerberos, and DNS) for monitoring of privileged identities and service accounts to improve detection and facilitate audits. Reveal(x) extracts metadata including user/computer account activity, invalid or expired passwords, new privileged access, privileged access errors, DNS SRV lookups, Plain-text LDAP binds, Plain-text HTTP authentications, Unknown SPNs, and Golden Ticket detection.

Web Transactions: Full HTTP payload analysis of user activity, SOAP/XML, JSON, Javascript, APIs, etc. Extracted metadata includes URI, query parameters, host headers, and user agent, among others.

Storage: Metadata extraction for all NAS and SAN transactions (iSCSI, NFS, and CIFS) enables machine learning detections based on actual file details and equips security analysts to track file access patterns and detect ransomware activity by examining file extensions and WRITE operations.