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Nozomi CMC

Overview

Nozomi Central Management Console is a centralized platform that streamlines the management of cybersecurity across industrial networks. It enables users to monitor, configure, and respond to threats in real-time, ensuring enhanced visibility and control over operational technology environments. With its user-friendly interface and powerful analytics, the console simplifies security operations and strengthens defense against cyber risks.

  • Supported environment: On prem
  • Detection based on: Alerts, Audit
  • Supported application or feature:
    • Alerts
    • Health
    • Audit

Configure

  1. In the top navigation bar, select settings
  2. In the Settings section, select Data integration.
  3. In the top right section, select Add.
  4. From the Choose a configuration dropdown, select CEF.

Configuration

  1. Enter the necessary details and enable whichever log types you prefer.

Details

Create your intake

Go to the intake page and create a new intake from the Nozomi CMC.

Enjoy your events on the Events page

Raw Events Samples

In this section, you will find examples of raw logs as generated natively by the source. These examples are provided to help integrators understand the data format before ingestion into Sekoia.io. It is crucial for setting up the correct parsing stages and ensuring that all relevant information is captured.

CEF:0|Nozomi Networks|N2OS|19.0.3-10142120_A2F44|SIGN:MALWARE-DETECTED
 |Malware detected|9|
  app=smb
  dvc=4.5.6.7
  dvchost=test-host-name
  cs1=9.0
  cs2=true
  cs3=d25c520f-7f79-4820-b5ae-d1b334b05c75
  cs4={trigger_type: yara_rules, trigger_id: MALW_DragonFly2.yar}
  cs5=["5740a157-08e8-490f-85ad-eef23657e3cb"]
  cs6=1
  cs1Label=Risk
  cs2Label=IsSecurity
  cs3Label=Id
  cs4Label=Detail
  cs5Label=Parents
  cs6Label=n2os_schema
  flexString1=T0843
  flexString1Label=mitre_attack_techniques
  flexString2=Impair process (etc)
  flexString2Label=mitre_attack_tactics
  flexString3=Suspicious Activity
  flexString3Label=name
  dst=2.3.4.5
  dmac=00:00:00:00:00:00
  dpt=445
  msg=Suspicious transferring of malware named 'TemplateAttack_DragonFly_2_0'
  was detected involving resource '\\2.3.4.5\ADMIN
  \CVcontrolEngineer.docx' after a 'read' operation [rule author: US-CERT
  Code Analysis Team - improved by Nozomi Networks] [yara file name:
  MALW_DragonFly2.yar]
  src=1.2.3.4
  smac=00:11:22:33:44:55
  spt=1148
  proto=TCP
  start=1571351543431

CEF:0|Nozomi Networks|N2OS|19.0.3-10201846_FD825|AUDIT:SESSIONS:CREATE|
User signed in|0|
dvchost=local-sg-19.x
cs1=Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:69.0) Gecko/20100101
Firefox/69.0
cs6=1
cs1Label=browser
cs6Label=n2os_schema
msg=User signed in
src=1.2.3.4
suser=admin
start=1570723218425

CEF:0|Nozomi Networks|N2OS|19.0.3-10201846_FD825|HEALTH|Health problem|0|
dvchost=local-sg-19.x
cs6=1
cs6Label=n2os_schema
msg=LINK_DOWN_on_port_em0

Detection section

The following section provides information for those who wish to learn more about the detection capabilities enabled by collecting this intake. It includes details about the built-in rule catalog, event categories, and ECS fields extracted from raw events. This is essential for users aiming to create custom detection rules, perform hunting activities, or pivot in the events page.

The following Sekoia.io built-in rules match the intake Nozomi CMC [BETA]. This documentation is updated automatically and is based solely on the fields used by the intake which are checked against our rules. This means that some rules will be listed but might not be relevant with the intake.

SEKOIA.IO x Nozomi CMC [BETA] on ATT&CK Navigator

Cryptomining

Detection of domain names potentially related to cryptomining activities.

  • Effort: master
Dynamic DNS Contacted

Detect communication with dynamic dns domain. This kind of domain is often used by attackers. This rule can trigger false positive in non-controlled environment because dynamic dns is not always malicious.

  • Effort: master
Exfiltration Domain

Detects traffic toward a domain flagged as a possible exfiltration vector.

  • Effort: master
Nimbo-C2 User Agent

Nimbo-C2 Uses an unusual User-Agent format in its implants.

  • Effort: intermediate
Potential Bazar Loader User-Agents

Detects potential Bazar loader communications through the user-agent

  • Effort: elementary
Potential Lemon Duck User-Agent

Detects LemonDuck user agent. The format used two sets of alphabetical characters separated by dashes, for example "User-Agent: Lemon-Duck-[A-Z]-[A-Z]".

  • Effort: elementary
Remote Access Tool Domain

Detects traffic toward a domain flagged as a Remote Administration Tool (RAT).

  • Effort: master
Remote Monitoring and Management Software - AnyDesk

Detect artifacts related to the installation or execution of the Remote Monitoring and Management tool AnyDesk.

  • Effort: master
SEKOIA.IO Intelligence Feed

Detect threats based on indicators of compromise (IOCs) collected by SEKOIA's Threat and Detection Research team.

  • Effort: elementary
Sekoia.io EICAR Detection

Detects observables in Sekoia.io CTI tagged as EICAR, which are fake samples meant to test detection.

  • Effort: master
TOR Usage

Detects TOR usage, based on the IP address and the destination port (filtered on NTP). TOR is short for The Onion Router, and it gets its name from how it works. TOR intercepts the network traffic from one or more apps on user’s computer, usually the user web browser, and shuffles it through a number of randomly-chosen computers before passing it on to its destination. This disguises user location, and makes it harder for servers to pick him/her out on repeat visits, or to tie together separate visits to different sites, this making tracking and surveillance more difficult. Before a network packet starts its journey, user’s computer chooses a random list of relays and repeatedly encrypts the data in multiple layers, like an onion. Each relay knows only enough to strip off the outermost layer of encryption, before passing what’s left on to the next relay in the list.

  • Effort: master
TOR Usage Generic Rule

Detects TOR usage globally, whether the IP is a destination or source. TOR is short for The Onion Router, and it gets its name from how it works. TOR intercepts the network traffic from one or more apps on user’s computer, usually the user web browser, and shuffles it through a number of randomly-chosen computers before passing it on to its destination. This disguises user location, and makes it harder for servers to pick him/her out on repeat visits, or to tie together separate visits to different sites, this making tracking and surveillance more difficult. Before a network packet starts its journey, user’s computer chooses a random list of relays and repeatedly encrypts the data in multiple layers, like an onion. Each relay knows only enough to strip off the outermost layer of encryption, before passing what’s left on to the next relay in the list.

  • Effort: master

Event Categories

The following table lists the data source offered by this integration.

Data Source Description
Network device logs None

In details, the following table denotes the type of events produced by this integration.

Name Values
Kind alert
Category host, malware, session
Type indicator, info

Transformed Events Samples after Ingestion

This section demonstrates how the raw logs will be transformed by our parsers. It shows the extracted fields that will be available for use in the built-in detection rules and hunting activities in the events page. Understanding these transformations is essential for analysts to create effective detection mechanisms with custom detection rules and to leverage the full potential of the collected data.

{
    "message": "CEF:0|Nozomi Networks|N2OS|19.0.3-10142120_A2F44|SIGN:MALWARE-DETECTED\n |Malware detected|9|\n  app=smb\n  dvc=4.5.6.7\n  dvchost=test-host-name\n  cs1=9.0\n  cs2=true\n  cs3=d25c520f-7f79-4820-b5ae-d1b334b05c75\n  cs4={trigger_type: yara_rules, trigger_id: MALW_DragonFly2.yar}\n  cs5=[\"5740a157-08e8-490f-85ad-eef23657e3cb\"]\n  cs6=1\n  cs1Label=Risk\n  cs2Label=IsSecurity\n  cs3Label=Id\n  cs4Label=Detail\n  cs5Label=Parents\n  cs6Label=n2os_schema\n  flexString1=T0843\n  flexString1Label=mitre_attack_techniques\n  flexString2=Impair process (etc)\n  flexString2Label=mitre_attack_tactics\n  flexString3=Suspicious Activity\n  flexString3Label=name\n  dst=2.3.4.5\n  dmac=00:00:00:00:00:00\n  dpt=445\n  msg=Suspicious transferring of malware named 'TemplateAttack_DragonFly_2_0'\n  was detected involving resource '\\\\2.3.4.5\\ADMIN\n  \\CVcontrolEngineer.docx' after a 'read' operation [rule author: US-CERT\n  Code Analysis Team - improved by Nozomi Networks] [yara file name:\n  MALW_DragonFly2.yar]\n  src=1.2.3.4\n  smac=00:11:22:33:44:55\n  spt=1148\n  proto=TCP\n  start=1571351543431",
    "event": {
        "category": [
            "malware"
        ],
        "dataset": "SIGN:MALWARE-DETECTED",
        "kind": "alert",
        "module": "nozomi.cmc",
        "outcome": "success",
        "reason": "Malware detected",
        "severity": 9,
        "type": [
            "indicator"
        ]
    },
    "destination": {
        "address": "2.3.4.5",
        "ip": "2.3.4.5",
        "mac": "00:00:00:00:00:00",
        "port": 445
    },
    "host": {
        "hostname": "test-host-name",
        "ip": [
            "4.5.6.7"
        ],
        "name": "test-host-name"
    },
    "network": {
        "transport": "TCP"
    },
    "nozomi": {
        "cmc": {
            "version": "19.0.3-10142120_A2F44"
        }
    },
    "observer": {
        "product": "Nozomi CMC",
        "vendor": "Nozomi"
    },
    "related": {
        "hosts": [
            "test-host-name"
        ],
        "ip": [
            "1.2.3.4",
            "2.3.4.5",
            "4.5.6.7"
        ]
    },
    "source": {
        "address": "1.2.3.4",
        "ip": "1.2.3.4",
        "mac": "00:11:22:33:44:55",
        "port": 1148
    },
    "threat": {
        "tactic": {
            "name": [
                "Impair process (etc)"
            ]
        },
        "technique": {
            "id": [
                "T0843"
            ]
        }
    }
}

{
    "message": "CEF:0|Nozomi Networks|N2OS|19.0.3-10201846_FD825|AUDIT:SESSIONS:CREATE|\nUser signed in|0|\ndvchost=local-sg-19.x\ncs1=Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:69.0) Gecko/20100101\nFirefox/69.0\ncs6=1\ncs1Label=browser\ncs6Label=n2os_schema\nmsg=User signed in\nsrc=1.2.3.4\nsuser=admin\nstart=1570723218425",
    "event": {
        "category": [
            "session"
        ],
        "dataset": "AUDIT:SESSIONS:CREATE",
        "module": "nozomi.cmc",
        "outcome": "success",
        "reason": "User signed in",
        "type": [
            "info"
        ]
    },
    "nozomi": {
        "cmc": {
            "version": "19.0.3-10201846_FD825"
        }
    },
    "observer": {
        "product": "Nozomi CMC",
        "vendor": "Nozomi"
    },
    "related": {
        "ip": [
            "1.2.3.4"
        ],
        "user": [
            "admin"
        ]
    },
    "source": {
        "address": "1.2.3.4",
        "ip": "1.2.3.4",
        "user": {
            "name": "admin"
        }
    },
    "user_agent": {
        "device": {
            "name": "Mac"
        },
        "name": "Firefox",
        "original": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:69.0) Gecko/20100101\nFirefox/69.0",
        "os": {
            "name": "Mac OS X",
            "version": "10.15"
        },
        "version": "69.0"
    }
}

{
    "message": "CEF:0|Nozomi Networks|N2OS|19.0.3-10201846_FD825|HEALTH|Health problem|0|\ndvchost=local-sg-19.x\ncs6=1\ncs6Label=n2os_schema\nmsg=LINK_DOWN_on_port_em0",
    "event": {
        "category": [
            "host"
        ],
        "dataset": "HEALTH",
        "module": "nozomi.cmc",
        "outcome": "success",
        "reason": "LINK_DOWN_on_port_em0",
        "type": [
            "info"
        ]
    },
    "nozomi": {
        "cmc": {
            "version": "19.0.3-10201846_FD825"
        }
    },
    "observer": {
        "product": "Nozomi CMC",
        "vendor": "Nozomi"
    }
}

Extracted Fields

The following table lists the fields that are extracted, normalized under the ECS format, analyzed and indexed by the parser. It should be noted that infered fields are not listed.

Name Type Description
destination.ip ip IP address of the destination.
destination.mac keyword MAC address of the destination.
destination.port long Port of the destination.
event.category keyword Event category. The second categorization field in the hierarchy.
event.dataset keyword Name of the dataset.
event.kind keyword The kind of the event. The highest categorization field in the hierarchy.
event.module keyword Name of the module this data is coming from.
event.outcome keyword The outcome of the event. The lowest level categorization field in the hierarchy.
event.reason keyword Reason why this event happened, according to the source
event.severity long Numeric severity of the event.
event.type keyword Event type. The third categorization field in the hierarchy.
host.hostname keyword Hostname of the host.
host.ip ip Host ip addresses.
network.transport keyword Protocol Name corresponding to the field iana_number.
nozomi.cmc.version keyword
observer.product keyword The product name of the observer.
observer.vendor keyword Vendor name of the observer.
source.ip ip IP address of the source.
source.mac keyword MAC address of the source.
source.port long Port of the source.
source.user.name keyword Short name or login of the user.
threat.tactic.name keyword Threat tactic.
threat.technique.id keyword Threat technique id.
user_agent.original keyword Unparsed user_agent string.

For more information on the Intake Format, please find the code of the Parser, Smart Descriptions, and Supported Events here.

Further Readings