CVE-2014-0114

What is this vulnerability?

CVE-2014-0114 is categorized as a unknown Improper Input Validation flaw. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

Apache Commons BeanUtils, as distributed in lib/commons-beanutils-1.8.0.jar in Apache Struts 1.x through 1.3.10 and in other products requiring commons-beanutils through 1.9.2, does not suppress the class property, which allows remote attackers to "manipulate" the ClassLoader and execute arbitrary code via the class parameter, as demonstrated by the passing of this parameter to the getClass method of the ActionForm object in Struts 1.

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-2014-0114

1. Apply Vendor Patches: Upgrade affected components to their latest, non-vulnerable versions immediately.
2. Implement Input Validation: Ensure all user-supplied data is validated, sanitized, and type-checked before processing.
3. Deploy Runtime Protection: Use Precogs continuous monitoring to detect exploitation attempts in real time.
4. Audit Dependencies: Review and update all third-party libraries and transitive dependencies.

Defending with Precogs AI

Apache Commons BeanUtils contains a classloader manipulation vulnerability. Attackers manipulate the class.classLoader property to modify server configuration or achieve remote code execution via object deserialization. Precogs Application Security Module tracks insecure object property bindings.

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