CVE-2015-8351

Code Injection in PHP remote file inclusion vulnerability in the Gwolle Guestbook plugin before 1

Verified by Precogs Threat Research
Last Updated: Apr 20, 2025
Base Score
9CRITICAL

Executive Summary

CVE-2015-8351 is a critical severity vulnerability affecting appsec. It is classified as Code Injection. Ensure your systems and dependencies are patched immediately to mitigate exposure risks.

Precogs AI Insight

"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."

Exploit Probability (EPSS)
High (69.4%)
Public POC
Available
Exploit Probability
High (84%)
Public POC
Available
Affected Assets
appsecCWE-94

What is this vulnerability?

CVE-2015-8351 is categorized as a critical Code Injection flaw with a CVSS base score of 9. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

PHP remote file inclusion vulnerability in the Gwolle Guestbook plugin before 1.5.4 for WordPress, when allow_url_include is enabled, allows remote authenticated users to execute arbitrary PHP code via a URL in the abspath parameter to frontend/captcha/ajaxresponse.php. NOTE: this can also be leveraged to include and execute arbitrary local files via directory traversal sequences regardless of whether allow_url_include is enabled.

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

MetricValue
CVSS Base Score9 (CRITICAL)
Vector StringCVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
PublishedSeptember 11, 2017
Last ModifiedApril 20, 2025
Related CWEsCWE-94

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-2015-8351

  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

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.

Start scanning with Precogs →

Vulnerability Code Signature

Attack Data Flow

StageDetail
SourceUntrusted payload via API or file upload
VectorInput passed to a dynamic code evaluation function
Sinkeval(), exec(), or similar unsafe execution sink
ImpactRemote Code Execution (RCE), full system compromise

Vulnerable Code Pattern

# ❌ VULNERABLE: Dynamic code evaluation
def process_data(user_input):
    # Taint sink: arbitrary code execution
    result = eval(user_input)
    return result

Secure Code Pattern

# ✅ SECURE: Safe parsing
import ast
def process_data(user_input):
    # Sanitized parsing: only evaluates literal structures
    result = ast.literal_eval(user_input)
    return result

How Precogs Detects This

Precogs AI Analysis Engine identifies unsafe dynamic code evaluation paths by tracking untrusted data into sinks like eval() and exec().

Related Vulnerabilitiesvia CWE-94

Is your system affected?

Precogs AI detects CVE-2015-8351 in compiled binaries, LLMs, and application layers — even without source code access.