CVE-2014-6324
The Kerberos Key Distribution Center (KDC) in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8
Executive Summary
CVE-2014-6324 is a high severity vulnerability affecting appsec. It is classified as an undisclosed flaw. This vulnerability is actively being exploited in the wild.
Precogs AI Insight
"This exposure is a direct consequence of within The Kerberos Key Distribution Center (KDC), allowing bypassed validation checks on external interactions. Exploitation typically involves an attacker attempting to execute arbitrary code on the target system, potentially leading to full system compromise. Precogs identifies insecure data flow paths before deployment to prevent unauthorized logical exploitation."
What is this vulnerability?
CVE-2014-6324 is categorized as a high security flaw with a CVSS base score of 8.8. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.
The Kerberos Key Distribution Center (KDC) in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, and Windows Server 2012 Gold and R2 allows remote authenticated domain users to obtain domain administrator privileges via a forged signature in a ticket, as exploited in the wild in November 2014, aka "Kerberos Checksum Vulnerability."
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
| Metric | Value |
|---|---|
| CVSS Base Score | 8.8 (HIGH) |
| Vector String | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H |
| Published | November 18, 2014 |
| Last Modified | April 22, 2026 |
| Related CWEs | N/A |
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-2014-6324
- Apply Vendor Patches Immediately: This vulnerability is listed in CISA's Known Exploited Vulnerabilities catalog. Apply updates per vendor instructions.
- Verify Patch Deployment: Confirm all instances are updated using Precogs continuous monitoring.
- Review Audit Logs: Investigate historical access logs for indicators of compromise related to this attack surface.
- Implement Defense-in-Depth: Deploy WAF rules, network segmentation, and endpoint detection to limit blast radius.
Defending with Precogs AI
Precogs AI Analysis Engine identifies this vulnerability class through semantic code analysis powered by Code Property Graph (CPG) technology, performing inter-procedural taint tracking to detect injection flaws, broken authentication, and insecure data flows across your entire codebase.
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.
Vulnerability Code Signature
Attack Data Flow
| Stage | Detail |
|---|---|
| Source | Untrusted User Input |
| Vector | Input flows through the application logic without sanitization |
| Sink | Execution or Rendering Sink |
| Impact | Application compromise, Logic Bypass, Data Exfiltration |
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