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Fastly Next-Gen WAF Alerts

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.

Warning

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

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
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

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 ``

Event Samples

Find below few samples of events and how they are normalized by Sekoia.io.

{
    "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.

Configure

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.

Sekoia.io configuration procedure

Create your intake

  1. Go to the intake page and create a new intake from the Fastly WAF.
  2. Copy the associated Intake key

Pull the logs to collect them on Sekoia.io

Go to the Sekoia.io playbook page, and follow these steps:

  1. Click + PLAYBOOK button to create a new one
  2. Select Create a playbook from scratch
  3. Give it a name in the field Name
  4. Open the left panel, click Fastly then select the trigger Fetch new events from Fastly WAF

  5. Click Create

  6. Create a Module configuration. Name the module configuration as you wish.

  7. Create a Trigger configuration using: 7.1. Type the Intake key created on the previous step 7.2 Enter User's email, API token, Corporation name and Site name from the Fastly WAF dashboard

  8. Click the Save button

  9. Activate the playbook with the toggle button in the top right corner of the page

Enjoy your events on the Events page