CVE-2017-12235

What is this vulnerability?

CVE-2017-12235 is categorized as a high Improper Input Validation 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 the PROFINET Discovery and Configuration Protocol (PN-DCP) for Cisco IOS 12.2 through 15.6 could allow an unauthenticated, remote attacker to cause an affected device to reload, resulting in a denial of service (DoS) condition. The vulnerability is due to the improper parsing of ingress PN-DCP Identify Request packets destined to an affected device. An attacker could exploit this vulnerability by sending a crafted PN-DCP Identify Request packet to an affected device and then continuing to send normal PN-DCP Identify Request packets to the device. A successful exploit could allow the attacker to cause the affected device to reload, resulting in a DoS condition. This vulnerability affects Cisco devices that are configured to process PROFINET messages. Beginning with Cisco IOS Software Release 12.2(52)SE, PROFINET is enabled by default on all the base switch module and expansion-unit Ethernet ports. Cisco Bug IDs: CSCuz47179.

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-2017-12235

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 PROFINET DCP protocol implementation fails to validate incoming discovery requests. Attackers broadcast malformed PROFINET frames to crash industrial control systems. Precogs Binary SAST specifically uncovers memory boundary violations in ICS protocols.

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.

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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