CVE-2017-18514

SQL Injection in The simple-login-log plugin before 1

Verified by Precogs Threat Research
Last Updated: Nov 21, 2024
Base Score
9.8CRITICAL

Executive Summary

CVE-2017-18514 is a critical severity vulnerability affecting appsec. It is classified as SQL 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)
Low (0.5%)
Public POC
Available
Exploit Probability
High (84%)
Public POC
Available
Affected Assets
appsecCWE-89

What is this vulnerability?

CVE-2017-18514 is categorized as a critical SQL Injection flaw with a CVSS base score of 9.8. Based on our vulnerability intelligence, this issue occurs when the application fails to securely handle untrusted data boundaries.

The simple-login-log plugin before 1.1.2 for WordPress has SQL injection.

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 Score9.8 (CRITICAL)
Vector StringCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
PublishedAugust 14, 2019
Last ModifiedNovember 21, 2024
Related CWEsCWE-89

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-2017-18514

  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
SourceUser-controlled HTTP request parameter
VectorString concatenation into SQL query string
SinkDatabase engine executes the malformed query
ImpactFull database compromise, unauthorized data modification or exfiltration

Vulnerable Code Pattern

# ❌ VULNERABLE: Direct string concatenation
def get_user(user_id):
    query = "SELECT * FROM users WHERE id = '" + user_id + "'"
    cursor.execute(query)  # Taint sink: unparameterized query
    return cursor.fetchone()

Secure Code Pattern

# ✅ SECURE: Parameterized query
def get_user(user_id):
    query = "SELECT * FROM users WHERE id = %s"
    cursor.execute(query, (user_id,))  # Sanitized binding
    return cursor.fetchone()

How Precogs Detects This

Precogs AI Analysis Engine traces data flow from HTTP request parameters through string concatenation directly into database execution sinks, identifying critical SQL injection vectors via Code Property Graph traversal.

Related Vulnerabilitiesvia CWE-89

Is your system affected?

Precogs AI detects CVE-2017-18514 in compiled binaries, LLMs, and application layers — even without source code access.