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Unbound

Overview

  • Vendor:
  • Plan: Defend Core & Defend Prime
  • Supported environment:
  • Version compatibility:
  • Detection based on: Telemetry
  • Supported application or feature: Unbound is a validating, recursive, and caching DNS resolver product from NLnet Labs. It is distributed free of charge in open-source form under the BSD license.

Configure

This setup guide will show you how to forward logs produced by your Unbound server to Sekoia.io by means of an rsyslog transport channel.

Configure the Rsyslog server

Please consult the Rsyslog Transport documentation to forward these logs to Sekoia.io.

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.

2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [17265:13] info: 127.0.0.1 reachms.corp.com. A IN

[3483:15] error: internal error: looping module stopped

[1678:6] error: failed to find an open port, drop msg

2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [265456:0] info: generate keytag query _ta-4f66. NULL IN

2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [27060:0] info: average recursion processing time 0.007562 sec

2019-10-08T11:29:04+02:00 hostfoo unbound[17265]: [17265:18] info: 192.168.1.1 1.1.1.1.in-addr.arpa. PTR IN

2019-10-09T18:29:22+02:00 hostfoo unbound[3888]: [3888:1f] info: 192.168.1.1 1.1.168.192.in-addr.arpa. PTR IN

2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [6634:16] info: server stats for thread 0: 11982 queries, 9074 answers from cache, 2908 recursions, 1029 prefetch, 0 rejected by ip ratelimiting

[16667:e] info: 192.168.1.1 _ldap._tcp.SXB._sites.dc._msdcs.key.corp.net. SRV IN

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 Unbound. 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 Unbound on ATT&CK Navigator

Bazar Loader DGA (Domain Generation Algorithm)

Detects Bazar Loader domains based on the Bazar Loader DGA

  • Effort: elementary
Cobalt Strike DNS Beaconing

Detects suspicious DNS queries known from Cobalt Strike beacons. The threshold is more than 50 suspicious DNS requests to avoid false positives.

  • Effort: advanced
Correlation Potential DNS Tunnel

Detects domain name which is longer than 95 characters. Long domain names are distinctive of DNS tunnels.

  • Effort: advanced
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
EvilProxy Phishing Domain

Detects subdomains potentially generated by the EvilProxy adversary-in-the-middle phishing platform. Inspect the other subdomains of the domain to identify the landing page, and determine if the user submitted credentials. This rule has a small percentage of false positives on legitimate domains.

  • Effort: intermediate
Exfiltration Domain

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

  • Effort: master
Potential DNS Tunnel

Detects domain name which is longer than 95 characters. Long domain names are distinctive of DNS tunnels.

  • Effort: advanced
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
Remote Monitoring and Management Software - Atera

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

  • 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
Sliver DNS Beaconing

Detects suspicious DNS queries known from Sliver beaconing

  • Effort: intermediate
Suspicious TOR Gateway

Detects suspicious TOR gateways. Gateways are often used by the victim to pay and decrypt the encrypted files without installing TOR. 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: advanced
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
Telegram Bot API Request

Detects suspicious DNS queries to api.telegram.org used by Telegram Bots of any kind

  • Effort: advanced

Event Categories

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

Data Source Description
DNS records unbound DNS queries

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": "2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [17265:13] info: 127.0.0.1 reachms.corp.com. A IN",
    "dns": {
        "question": {
            "class": "IN",
            "name": "reachms.corp.com",
            "registered_domain": "corp.com",
            "subdomain": "reachms",
            "top_level_domain": "com",
            "type": "A"
        },
        "size_in_char": 16,
        "type": "query"
    },
    "host": {
        "name": "hostfoo"
    },
    "related": {
        "hosts": [
            "reachms.corp.com"
        ],
        "ip": [
            "127.0.0.1"
        ]
    },
    "source": {
        "address": "127.0.0.1",
        "ip": "127.0.0.1"
    }
}

{
    "message": "[3483:15] error: internal error: looping module stopped",
    "error": {
        "message": "looping module stopped",
        "type": "internal error"
    }
}

{
    "message": "[1678:6] error: failed to find an open port, drop msg",
    "error": {
        "message": "failed to find an open port, drop msg"
    }
}

{
    "message": "2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [265456:0] info: generate keytag query _ta-4f66. NULL IN",
    "host": {
        "name": "hostfoo"
    }
}

{
    "message": "2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [27060:0] info: average recursion processing time 0.007562 sec",
    "host": {
        "name": "hostfoo"
    }
}

{
    "message": "2019-10-08T11:29:04+02:00 hostfoo unbound[17265]: [17265:18] info: 192.168.1.1 1.1.1.1.in-addr.arpa. PTR IN",
    "dns": {
        "question": {
            "class": "IN",
            "name": "1.1.1.1.in-addr.arpa",
            "registered_domain": "1.in-addr.arpa",
            "subdomain": "1.1.1",
            "top_level_domain": "in-addr.arpa",
            "type": "PTR"
        },
        "size_in_char": 20,
        "type": "query"
    },
    "host": {
        "name": "hostfoo"
    },
    "related": {
        "hosts": [
            "1.1.1.1.in-addr.arpa"
        ],
        "ip": [
            "192.168.1.1"
        ]
    },
    "source": {
        "address": "192.168.1.1",
        "ip": "192.168.1.1"
    }
}

{
    "message": "2019-10-09T18:29:22+02:00 hostfoo unbound[3888]: [3888:1f] info: 192.168.1.1 1.1.168.192.in-addr.arpa. PTR IN",
    "dns": {
        "question": {
            "class": "IN",
            "name": "1.1.168.192.in-addr.arpa",
            "registered_domain": "192.in-addr.arpa",
            "subdomain": "1.1.168",
            "top_level_domain": "in-addr.arpa",
            "type": "PTR"
        },
        "size_in_char": 24,
        "type": "query"
    },
    "host": {
        "name": "hostfoo"
    },
    "related": {
        "hosts": [
            "1.1.168.192.in-addr.arpa"
        ],
        "ip": [
            "192.168.1.1"
        ]
    },
    "source": {
        "address": "192.168.1.1",
        "ip": "192.168.1.1"
    }
}

{
    "message": "2019-10-08T11:29:05+02:00 hostfoo unbound[17265]: [6634:16] info: server stats for thread 0: 11982 queries, 9074 answers from cache, 2908 recursions, 1029 prefetch, 0 rejected by ip ratelimiting",
    "host": {
        "name": "hostfoo"
    }
}

{
    "message": "[16667:e] info: 192.168.1.1 _ldap._tcp.SXB._sites.dc._msdcs.key.corp.net. SRV IN",
    "dns": {
        "question": {
            "class": "IN",
            "name": "_ldap._tcp.SXB._sites.dc._msdcs.key.corp.net",
            "registered_domain": "corp.net",
            "subdomain": "_ldap._tcp.SXB._sites.dc._msdcs.key",
            "top_level_domain": "net",
            "type": "SRV"
        },
        "size_in_char": 44,
        "type": "query"
    },
    "related": {
        "hosts": [
            "_ldap._tcp.SXB._sites.dc._msdcs.key.corp.net"
        ],
        "ip": [
            "192.168.1.1"
        ]
    },
    "source": {
        "address": "192.168.1.1",
        "ip": "192.168.1.1"
    }
}

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
dns.question.class keyword The class of records being queried.
dns.question.name keyword The name being queried.
dns.question.type keyword The type of record being queried.
dns.size_in_char number
dns.type keyword The type of DNS event captured, query or answer.
error.message match_only_text Error message.
error.type keyword The type of the error, for example the class name of the exception.
host.name keyword Name of the host.
source.domain keyword The domain name of the source.
source.ip ip IP address of the source.
source.port long Port of the source.
user.id keyword Unique identifier of the user.
user.name keyword Short name or login of the user.

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