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Fastly Next-Gen WAF

Overview

Fastly Next-Gen WAF is a web application firewall solution designed to protect online assets by mitigating web application threats, ensuring security, and enhancing application performance with its edge-based, real-time protection capabilities.

  • Vendor: Fastly
  • Supported environment: SaaS
  • Version compatibility:
  • Detection based on: Alert
  • Supported application or feature: WAF Alerts

Warning

Important note - This format is currently in beta. We highly value your feedback to improve its performance.

Step-by-Step Configuration Procedure

Instructions on the 3rd Party Solution

Creating API access tokens

  1. Go to the Fastly WAF and log in.
  2. From the My Profile menu, select API access tokens.
  3. Click Add API access token.
  4. In the Token name field, enter a name to identify the access token.
  5. Click Create API access token.
  6. Record the token in a secure location for your use. Then, click Continue to finish creating the token.

Warning

This is the only time the token will be visible. Record the token and keep it secure.

Instruction on Sekoia

Configure Your Intake

This section will guide you through creating the intake object in Sekoia, which provides a unique identifier called the "Intake key." The Intake key is essential for later configuration, as it references the Community, Entity, and Parser (Intake Format) used when receiving raw events on Sekoia.

  1. Go to the Sekoia Intake page.
  2. Click on the + New Intake button at the top right of the page.
  3. Search for your Intake by the product name in the search bar.
  4. Give it a Name and associate it with an Entity (and a Community if using multi-tenant mode).
  5. Click on Create.
  6. You will be redirected to the Intake listing page, where you will find a new line with the name you gave to the Intake.

Note

For more details on how to use the Intake page and to find the Intake key you just created, refer to this documentation.

Configure Your Playbook

This section will assist you in pulling remote logs from Sekoia and sending them to the intake you previously created.

  1. Go to the Sekoia playbook page.
  2. Click on the + New playbook button at the top right of the page.
  3. Select Create a playbook from scratch, and click Next.
  4. Give it a Name and a Description, and click Next.
  5. Choose a trigger from the list by searching for the name of the product, and click Create.
  6. A new Playbook page will be displayed. Click on the module in the center of the page, then click on the Configure icon.
  7. On the right panel, click on the Configuration tab.
  8. Select an existing Trigger Configuration (from the account menu) or create a new one by clicking on + Create new configuration.
  9. Configure the Trigger based on the Actions Library (for instance, see here for AWS modules), then click Save.
  10. Click on Save at the top right of the playbook page.
  11. Activate the playbook by clicking on the "On / Off" toggle button at the top right corner of the page.

Note

For this procedure, you will need the Intake key created on the previous step, and User's email, API token, Corporation name and Site name from the Fastly WAF dashboard

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.

{
    "id": "54de69dcba53b02fbf000018",
    "timestamp": "2015-02-13T21:17:16Z",
    "source": "162.245.23.109",
    "remoteCountryCode": "AU",
    "remoteHostname": "",
    "userAgents": [
        "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT 5.0)"
    ],
    "action": "flagged",
    "type": "attack",
    "reasons": {
        "SQLI": 99
    },
    "requestCount": 1,
    "tagCount": 1,
    "window": 60,
    "expires": "2015-02-14T21:17:16Z",
    "expiredBy": ""
}

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 Fastly Next-Gen WAF Alerts [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 Fastly Next-Gen WAF Alerts [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 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
WAF Correlation Block actions

Detection of multiple block actions (more than 30) triggered by the same source by WAF detection rules

  • Effort: master

Event Categories

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

Data Source Description
Web application firewall logs Fastly WAF protects web application with its web application firewall

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

Name Values
Kind alert
Category network
Type ``

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": "{\"id\": \"54de69dcba53b02fbf000018\", \"timestamp\": \"2015-02-13T21:17:16Z\", \"source\": \"162.245.23.109\", \"remoteCountryCode\": \"AU\", \"remoteHostname\": \"\", \"userAgents\": [\"Mozilla/4.0 (compatible; MSIE 5.5; Windows NT 5.0)\"], \"action\": \"flagged\", \"type\": \"attack\", \"reasons\": {\"SQLI\": 99}, \"requestCount\": 1, \"tagCount\": 1, \"window\": 60, \"expires\": \"2015-02-14T21:17:16Z\", \"expiredBy\": \"\"}",
    "event": {
        "action": "flagged",
        "category": [
            "network"
        ],
        "kind": "alert",
        "module": "fastly.waf",
        "type": [
            "denied"
        ]
    },
    "@timestamp": "2015-02-13T21:17:16Z",
    "fastly": {
        "waf": {
            "expires": "2015-02-14T21:17:16Z",
            "reasons": {
                "SQLI": 99
            },
            "request_count": 1,
            "tag_count": 1,
            "user_agents": [
                "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT 5.0)"
            ],
            "window": 60
        }
    },
    "host": {
        "geo": {
            "country_iso_code": "AU"
        }
    },
    "observer": {
        "product": "Fastly Next-Gen WAF",
        "vendor": "Fastly"
    },
    "related": {
        "ip": [
            "162.245.23.109"
        ]
    },
    "source": {
        "address": "162.245.23.109",
        "ip": "162.245.23.109"
    },
    "user_agent": {
        "device": {
            "name": "Other"
        },
        "name": "IE",
        "original": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT 5.0)",
        "os": {
            "name": "Windows",
            "version": "2000"
        },
        "version": "5.5"
    }
}

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.
event.action keyword The action captured by the event.
event.category keyword Event category. The second categorization field in the hierarchy.
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.
fastly.waf.expired_by keyword Email of the user if the event is expired manually
fastly.waf.expires keyword Expires RFC3339 date time
fastly.waf.reasons object Key attack type - value number of
fastly.waf.request_count long Total number of requests
fastly.waf.tag_count long Total number of tags
fastly.waf.user_agents keyword
fastly.waf.window long Time window in seconds where the items were detected
host.geo.country_iso_code keyword Country ISO code.
host.name keyword Name of the host.
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.
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.