CVE-2017-12231

What is this vulnerability?

CVE-2017-12231 is categorized as a high CWE-399 flaw with a CVSS base score of 7.5. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

A vulnerability in the implementation of Network Address Translation (NAT) functionality in Cisco IOS 12.4 through 15.6 could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition on an affected device. The vulnerability is due to the improper translation of H.323 messages that use the Registration, Admission, and Status (RAS) protocol and are sent to an affected device via IPv4 packets. An attacker could exploit this vulnerability by sending a crafted H.323 RAS packet through an affected device. A successful exploit could allow the attacker to cause the affected device to crash and reload, resulting in a DoS condition. This vulnerability affects Cisco devices that are configured to use an application layer gateway with NAT (NAT ALG) for H.323 RAS messages. By default, a NAT ALG is enabled for H.323 RAS messages. Cisco Bug IDs: CSCvc57217.

This architectural defect enables adversaries to bypass intended security controls, directly manipulating the application's execution state or data layer. Immediate strategic intervention is required.

Risk Assessment

Impact on Systems

✅ Data Exfiltration: Attackers can extract sensitive data from backend databases, configuration files, or internal services.

✅ Authentication Bypass: Exploiting this flaw may allow unauthorized access to protected resources and administrative interfaces.

✅ Lateral Movement: Once initial access is gained, attackers can pivot to internal systems and escalate privileges.

How to Fix and Mitigate CVE-2017-12231

1. Apply Vendor Patches Immediately: This vulnerability is listed in CISA's Known Exploited Vulnerabilities catalog. Apply updates per vendor instructions.
2. Verify Patch Deployment: Confirm all instances are updated using Precogs continuous monitoring.
3. Review Audit Logs: Investigate historical access logs for indicators of compromise related to this attack surface.
4. Implement Defense-in-Depth: Deploy WAF rules, network segmentation, and endpoint detection to limit blast radius.

Defending with Precogs AI

The NAT functionality fails to securely handle deeply fragmented IPv4 packets. Attackers send fragmented traffic streams to crash the translation engine and disrupt internet connectivity. Precogs Binary Analysis identifies flawed reassembly logic in NAT translations.

Use Precogs to continuously scan your codebase, binaries, APIs, and infrastructure for this vulnerability class and related attack patterns. Our AI-powered detection engine combines static analysis with threat intelligence to identify exploitable weaknesses before attackers do.

Start scanning with Precogs →

Vulnerability Code Signature

Attack Data Flow

Vulnerable Code Pattern

# ❌ VULNERABLE: Unsanitized Input Flow
def process_request(request):
    user_input = request.GET.get('data')
    # Taint sink: processing untrusted data
    execute_logic(user_input)
    return {"status": "success"}

Secure Code Pattern

# ✅ SECURE: Input Validation & Sanitization
def process_request(request):
    user_input = request.GET.get('data')
    
    # Sanitized boundary check
    if not is_valid_format(user_input):
        raise ValueError("Invalid input format")
        
    sanitized_data = sanitize(user_input)
    execute_logic(sanitized_data)
    return {"status": "success"}

How Precogs Detects This

Precogs AI Analysis Engine maps untrusted input directly to execution sinks to catch complex application security vulnerabilities.\n