Varonis Data Security

Overview

Varonis offers solutions to track and protect data.

• Vendor: Varonis
• Plan: Defend Core & Defend Prime
• Supported environment: SaaS
• Detection based on: Alert
• Supported application or feature: Data loss prevention

Configure

This setup guide will show you how to forward your Varonis Data Security logs to Sekoia.io by means of a syslog transport channel.

Prerequisites

• Have an internal log concentrator (Rsyslog)

Enable Syslog forwarding for Varonis Data Security

You can configure the Syslog server address in DatAlert so that alerts are sent to SEKOIA. To configure the Syslog server address in DatAlert:

1. In DatAdvantage, select Tools > DatAlert. DatAlert is displayed.
2. From the left menu, select Configuration.
3. In the Syslog Message Forwarding section, fill the Syslog server IP address and the Port with the ip address and the port of the log concentrator.
4. The expected severity is info
5. Click OK

Create a message forwarding template

1. In DatAlert, select Alert Templates
2. Select External system default template (CEF) and click Edit Alert Template
3. In Apply to alert methods, select Syslog message
4. Click OK

Create the intake

Go to the intake page and create a new intake from the format Varonis Data Security

Forward logs to Sekoia.io

Please consult the Syslog Forwarding documentation to forward these logs to Sekoia.io.

Currently, the syslog format generated by Varonis does not comply with RFC standards. As a result, the transmitted data is not inherently compatible with the Sekoia forwarder. Therefore, it is necessary to refer to this documentation in order to extend the default configuration of the forwarder (available since version 2.4) and add this specific configuration for Varonis logs:

input(type="im$PROTOCOL" port="$PORT" ruleset="remoteVaronis")
template(name="SEKOIAIO_Varonis_Template" type="string" string="<%pri%>1 %timegenerated:::date-rfc3339% %hostname% $APP-NAME - LOG [SEKOIA@53288 intake_key=\"$INTAKE-KEY\"] %msg:R,ERE,1,FIELD:.*(CEF.*)$--end%\n")
ruleset(name="remoteVaronis"){
action(
    name="varonis"
    type="omfwd"
    protocol="tcp"
    target="intake.sekoia.io"
    port="10514"
    TCP_Framing="octet-counted"
    StreamDriver="gtls"
    StreamDriverMode="1"
    StreamDriverAuthMode="x509/name"
    StreamDriverPermittedPeers="intake.sekoia.io"
    Template="SEKOIAIO_Varonis_Template"
    )
}

Note

Don't forget to replace the variables $PROTOCOL (tcp or udp) to choose the protocol by which Varonis logs are received, the $PORT of entry, your $APP-NAME syslog, and your $INTAKE-KEY Sekoia.

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.

test_email_eventtest_network_alert

CEF:0|Varonis|DatAdvantage|0.0.1|666|Alert|Medium|cat=Alert cs1=joh.doe@gmail.com cs3=runme.exe cs5=Mon Aug  1 06:40:30 2022 deviceCustomDate1=Mon Aug  1 06:40:35 2022 suser=fool rt=2023-06-09T14:16:15.212418 cs2=Abnormal admin behavior: access to atypical mailboxes cn1=Rule Name end=2023-06-09T14:16:15.212435 duser=root dhost=127.0.0.1 filePath=~/pub.key act=Alert dvchost=HOSTNAME dvc=192.168.0.1 outcome=failure msg=Hello externalId=172ae7a0-e2c6-4b0d-a48e-b2cb8ead2481

CEF:0|Varonis|DatAdvantage|0.0.1|666|Alert|Medium|cat=Alert cs2=SomeRule cs2Label=RuleName cn1=Some rule description cn1Label=RuleID end= duser= dhost=1.2.3.4 filePath= fname= act= dvchost= outcome= msg= cs3= cs3Label=AttachmentName cs4= cs4Label=ClientAccessType deviceCustomDate1= fileType= cs1= cs1Label=MailRecipient suser= cs5= cs5Label=MailboxAccessType cnt= cs6= cs6Label=ChangedPermissions oldFilePermission=555 filePermission=777 dpriv= start=

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.

Related Built-in Rules

The following Sekoia.io built-in rules match the intake Varonis Data Security. 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 Varonis Data Security on ATT&CK Navigator

Adidnsdump Enumeration

Detects use of the tool adidnsdump for enumeration and discovering DNS records.

• Effort: advanced

Advanced IP Scanner

Detects the use of Advanced IP Scanner. Seems to be a popular tool for ransomware groups.

• Effort: master

Certify Or Certipy

Detects the use of certify and certipy which are two different tools used to enumerate and abuse Active Directory Certificate Services.

• Effort: advanced

Cobalt Strike Default Beacons Names

Detects the default names of Cobalt Strike beacons / payloads.

• Effort: intermediate

Credential Dump Tools Related Files

Detects processes or file names related to credential dumping tools and the dropped files they generate by default.

• 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

Exfiltration Domain

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

• Effort: master

HTA Infection Chains

Detect the creation of a ZIP file and an HTA file as it is often used in infection chains. Furthermore it also detects the use of suspicious processes launched by explorer.exe combined with the creation of an HTA file, since it is also often used in infection chains (LNK - HTA for instance).

• Effort: intermediate

HTML Smuggling Suspicious Usage

Based on several samples from different botnets, this rule aims at detecting HTML infection chain by looking for HTML created files followed by suspicious files being executed.

• Effort: intermediate

HackTools Suspicious Names

Quick-win rule to detect the default process names or file names of several HackTools.

• Effort: elementary

ISO LNK Infection Chain

Detection of an ISO (or any other similar archive file) downloaded file, followed by a child-process of explorer, which is characteristic of an infection using an ISO containing an LNK file. For events with host.name.

• Effort: intermediate

NTDS.dit File In Suspicious Directory

The file NTDS.dit is supposed to be located mainly in C:\Windows\NTDS. The rule checks whether the file is in a legitimate directory or not (through file creation events). This is usually really suspicious and could indicate an attacker trying copy the file to then look for users password hashes.

• Effort: advanced

OneNote Embedded File

Detects creation or uses of OneNote embedded files with unusual extensions.

• Effort: intermediate

PasswordDump SecurityXploded Tool

Detects the execution of the PasswordDump SecurityXploded Tool

• Effort: elementary

Process Trace Alteration

PTrace syscall provides a means by which one process ("tracer") may observe and control the execution of another process ("tracee") and examine and change the tracee's memory and registers. Attacker might want to abuse ptrace functionnality to analyse memory process. It requires to be admin or set ptrace_scope to 0 to allow all user to trace any process.

• Effort: advanced

RSA SecurID Failed Authentification

Detects many failed attempts to authenticate followed by a successfull login for a super admin account.

• Effort: advanced

RTLO Character

Detects RTLO (Right-To-Left character) in file and process names.

• 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

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

SecurityScorecard Vulnerability Assessment Scanner New Issues

Raises an alert when SecurityScorecard Vulnerability Assessment Scanner find new issues.

• Effort: master

Sekoia.io EICAR Detection

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

• Effort: master

Suspicious Email Attachment Received

Detects email containing an .exe|.dll|.ps1|.bat|.hta attachment. Most of the time files send by mail like this are malware.

• Effort: elementary

Suspicious File Name

Detects suspicious file name possibly linked to malicious tool.

• Effort: advanced

Suspicious PROCEXP152.sys File Created In Tmp

Detects the creation of the PROCEXP152.sys file in the application-data local temporary folder. This driver is used by Sysinternals Process Explorer but also by KDU (https://github.com/hfiref0x/KDU) or Ghost-In-The-Logs (https://github.com/bats3c/Ghost-In-The-Logs), which uses KDU. Note - Clever attackers may easily bypass this detection by just renaming the driver filename. Therefore just Medium-level and don't rely on it.

• 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

WCE wceaux.dll Creation

Detects wceaux.dll creation while Windows Credentials Editor (WCE) is executed.

• Effort: intermediate

Webshell Creation

Detects possible webshell file creation. It requires File Creation monitoring, which can be done using Sysmon's Event ID 11. However the recommended SwiftOnSecurity configuration does not fully cover the needs for this rule, it needs to be updated with the proper file names extensions.

• Effort: master

ZIP LNK Infection Chain

Detection of an ZIP download followed by a child-process of explorer, followed by multiple Windows processes.This is widely used as an infection chain mechanism.

• Effort: advanced

Event Categories

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

Data Source	Description
Data loss prevention	Varonis detects data exportation

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

Name	Values
Kind	alert
Category	``
Type	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.

test_email_event.jsontest_network_alert.json

{
    "message": "CEF:0|Varonis|DatAdvantage|0.0.1|666|Alert|Medium|cat=Alert cs1=joh.doe@gmail.com cs3=runme.exe cs5=Mon Aug  1 06:40:30 2022 deviceCustomDate1=Mon Aug  1 06:40:35 2022 suser=fool rt=2023-06-09T14:16:15.212418 cs2=Abnormal admin behavior: access to atypical mailboxes cn1=Rule Name end=2023-06-09T14:16:15.212435 duser=root dhost=127.0.0.1 filePath=~/pub.key act=Alert dvchost=HOSTNAME dvc=192.168.0.1 outcome=failure msg=Hello externalId=172ae7a0-e2c6-4b0d-a48e-b2cb8ead2481",
    "event": {
        "action": "Alert",
        "category": [
            "email"
        ],
        "dataset": "Alert",
        "end": "2023-06-09T14:16:15.212435Z",
        "kind": "alert",
        "reason": "Hello",
        "type": [
            "info"
        ]
    },
    "@timestamp": "2023-06-09T14:16:15.212418Z",
    "email": {
        "attachments": [
            {
                "file": {
                    "mime_type": "",
                    "name": "runme.exe"
                }
            }
        ],
        "delivery_timestamp": "2022-08-01T06:40:35Z",
        "from": {
            "address": "fool"
        },
        "to": {
            "address": "joh.doe@gmail.com"
        }
    },
    "file": {
        "directory": "~",
        "name": "pub.key",
        "path": "~/pub.key"
    },
    "host": {
        "name": "127.0.0.1"
    },
    "observer": {
        "product": "DatAdvantage",
        "vendor": "Varonis",
        "version": "0.0.1"
    },
    "related": {
        "hosts": [
            "HOSTNAME"
        ],
        "ip": [
            "192.168.0.1"
        ],
        "user": [
            "root"
        ]
    },
    "rule": {
        "description": "Abnormal admin behavior: access to atypical mailboxes",
        "id": "666",
        "name": "Rule Name"
    },
    "source": {
        "address": "HOSTNAME",
        "domain": "HOSTNAME",
        "ip": "192.168.0.1"
    },
    "user": {
        "name": "root"
    },
    "varonis": {
        "datalert": {
            "id": "172ae7a0-e2c6-4b0d-a48e-b2cb8ead2481",
            "outcome": "failure"
        }
    }
}

{
    "message": "CEF:0|Varonis|DatAdvantage|0.0.1|666|Alert|Medium|cat=Alert cs2=SomeRule cs2Label=RuleName cn1=Some rule description cn1Label=RuleID end= duser= dhost=1.2.3.4 filePath= fname= act= dvchost= outcome= msg= cs3= cs3Label=AttachmentName cs4= cs4Label=ClientAccessType deviceCustomDate1= fileType= cs1= cs1Label=MailRecipient suser= cs5= cs5Label=MailboxAccessType cnt= cs6= cs6Label=ChangedPermissions oldFilePermission=555 filePermission=777 dpriv= start=",
    "event": {
        "category": [
            "network"
        ],
        "dataset": "Alert",
        "kind": "alert",
        "type": [
            "info"
        ]
    },
    "host": {
        "name": "1.2.3.4"
    },
    "observer": {
        "product": "DatAdvantage",
        "vendor": "Varonis",
        "version": "0.0.1"
    },
    "rule": {
        "description": "SomeRule",
        "id": "666",
        "name": "Some rule description"
    },
    "varonis": {
        "datalert": {
            "file": {
                "old_permission": "555",
                "permission": "777"
            }
        }
    }
}

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
@timestamp	date	Date/time when the event originated.
email.attachments	nested	List of objects describing the attachments.
email.delivery_timestamp	date	Date and time when message was delivered.
email.from.address	keyword	The sender's email address.
email.to.address	keyword	Email address of recipient
event.action	keyword	The action captured by the event.
event.category	keyword	Event category. The second categorization field in the hierarchy.
event.dataset	keyword	Name of the dataset.
event.end	date	event.end contains the date when the event ended or when the activity was last observed.
event.kind	keyword	The kind of the event. The highest 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.
event.url	keyword	Event investigation URL
file.name	keyword	Name of the file including the extension, without the directory.
file.path	keyword	Full path to the file, including the file name.
host.name	keyword	Name of the host.
observer.product	keyword	The product name of the observer.
observer.vendor	keyword	Vendor name of the observer.
observer.version	keyword	Observer version.
rule.description	keyword	Rule description
rule.id	keyword	Rule ID
rule.name	keyword	Rule name
source.domain	keyword	The domain name of the source.
source.ip	ip	IP address of the source.
user.name	keyword	Short name or login of the user.
varonis.datalert.file.old_permission	keyword	The permissions before the change. Data is not collected for all event types.
varonis.datalert.file.permission	keyword	The permissions after the change. Data is not collected for all event types.
varonis.datalert.file.permissions_change	keyword	The specified changes in permissions. Data is not collected for all event types.
varonis.datalert.id	keyword	The ID of the triggered alert within DatAlert.
varonis.datalert.num_events	number	The number of events which triggered the alert.
varonis.datalert.outcome	keyword	Whether the event which triggered the alert succeeded or failed.

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