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Directus Blind SSRF On File Import

Moderate severity GitHub Reviewed Published Jul 8, 2024 in directus/directus • Updated Aug 7, 2024

Package

npm @directus/api (npm)

Affected versions

< 17.1.0

Patched versions

17.1.0

Description

Summary

There was already a reported SSRF vulnerability via file import. GHSA-j3rg-3rgm-537h
It was fixed by resolving all DNS names and checking if the requested IP is an internal IP address.

However it is possible to bypass this security measure and execute a SSRF using redirects. Directus allows redirects when importing file from the URL and does not check the result URL. Thus, it is possible to execute a request to an internal IP, for example to 127.0.0.1.

However, it is blind SSRF, because Directus also uses response interception technique to get the information about the connect from the socket directly and it does not show a response if the IP address is internal (nice fix, by the way :) ).

But the blindness does not fully mitigate the impact of the vulnerability. The blind SSRF is still exploitable in the real life scenarios, because there could be a vulnerable software inside of the network which can be exploited with GET request. I will show the example in the PoC. Also, you can check HackTricks page with some known cases.

Details

Give all details on the vulnerability. Pointing to the incriminated source code is very helpful for the maintainer.

PoC

For testing I used the docker compose with the latest directus version. Here is my docker compose file

version: "3"
services:
  directus:
    image: directus/directus:10.8.3
    ports:
      - 8055:8055
    volumes:
      - ./database:/directus/database
      - ./uploads:/directus/uploads
      - ./extensions:/directus/extensions
    environment:
      KEY: "redacted"
      SECRET: "redacted"
      ADMIN_EMAIL: "admin@example.com"
      ADMIN_PASSWORD: "redacted"
      DB_CLIENT: "sqlite3"
      DB_FILENAME: "/directus/database/data.db"

As a first step it is needed to setup a redirect server which will redirect the incoming request to some internal URL. I did it on my VPS with the public IP.

image

After it I setup a simple HTTP Server emulating the vulnerable application inside the internal network. It just execute any shell command provided in the cmd GET-parameter.

image

After it the directus import functionality was used

image

It initiates the following HTTP request

POST /files/import HTTP/1.1
Host: 127.0.0.1:8055
User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:121.0) Gecko/20100101 Firefox/121.0
Accept: application/json, text/plain, */*
Accept-Language: en-US,en;q=0.5
Accept-Encoding: gzip, deflate, br
Authorization: Bearer redacteed
Content-Type: application/json
Content-Length: 44
Origin: http://127.0.0.1:8055
Connection: close
Referer: http://127.0.0.1:8055/admin/files/+
Cookie: directus_refresh_token=redacted
Sec-Fetch-Dest: empty
Sec-Fetch-Mode: cors
Sec-Fetch-Site: same-origin

{"url":"http://94.103.84.233:801","data":{}}

It can be seen on the redirect server that the request came to it.

And we can also see the request in the localhost server (the same host as directus), which confirms the bypass and the SSRF.

image

And the rce_poc file was created.

image

Impact

The impact is Blind SSRF. Using it an attacker can initiate HTTP GET requests to the internal network. For example, it can be used to exploit some GET-based vulnerabilities of other software in the internal network.

Fix proposition

I think there are two ways to fix this vulnerability:

  • Disallow redirects for the import requests
  • Check the Location header in the import request response if it is present. Drop the request if the Location url points to the internal IP.

References

@br41nslug br41nslug published to directus/directus Jul 8, 2024
Published to the GitHub Advisory Database Jul 8, 2024
Reviewed Jul 8, 2024
Published by the National Vulnerability Database Jul 8, 2024
Last updated Aug 7, 2024

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality Low
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:N/SC:L/SI:N/SA:N

EPSS score

0.045%
(15th percentile)

Weaknesses

CVE ID

CVE-2024-39699

GHSA ID

GHSA-8p72-rcq4-h6pw

Source code

Credits

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