Skip to main content
CVE Vulnerability Database
Vulnerability Database/CVE-2018-25379

CVE-2018-25379: Collectric CMU 1.0 SQLi Vulnerability

CVE-2018-25379 is a boolean-based blind SQL injection flaw in Collectric CMU 1.0 affecting the lang parameter. Unauthenticated attackers can manipulate queries to extract database information. This article covers technical details, impact, and mitigation.

Published:

CVE-2018-25379 Overview

CVE-2018-25379 is a boolean-based blind SQL injection vulnerability in Collectric CMU 1.0. The flaw resides in the lang parameter processed during login authentication. Unauthenticated remote attackers can inject SQL syntax through this parameter to manipulate backend database queries. Successful exploitation enables data extraction using time-based and boolean-based blind techniques. The vulnerability maps to [CWE-89] Improper Neutralization of Special Elements used in an SQL Command.

Critical Impact

Unauthenticated attackers can extract sensitive database contents over the network with low attack complexity and no user interaction.

Affected Products

  • Collectric CMU 1.0
  • Vendor: Our Energy (ourenergy.se)
  • Component: Login authentication handler processing the lang parameter

Discovery Timeline

  • 2026-05-25 - CVE-2018-25379 published to NVD
  • 2026-05-26 - Last updated in NVD database

Technical Details for CVE-2018-25379

Vulnerability Analysis

The vulnerability stems from unsanitized handling of the lang HTTP parameter inside the login workflow of Collectric CMU 1.0. Attacker-supplied input is concatenated directly into a backend SQL statement. Because the application does not use parameterized queries or input validation, SQL syntax injected into lang alters query logic.

The injection is blind, meaning the application does not return query results directly in HTTP responses. Attackers instead infer data by observing boolean-state differences or response delays from time-based payloads such as SLEEP() functions. Iterating one bit at a time, an attacker can enumerate database schemas, extract credential hashes, and read arbitrary table contents.

Exploitation requires only network access to the login endpoint and no prior authentication. According to the EPSS data dated 2026-05-28, the probability of exploitation in the next 30 days is 0.123 percent.

Root Cause

The root cause is direct string concatenation of the lang request parameter into a SQL query executed during the authentication routine. The codebase lacks prepared statements, allow-list validation, and contextual output encoding, which permits arbitrary SQL clauses to be appended to the original query.

Attack Vector

An attacker sends a crafted HTTP request to the Collectric CMU 1.0 login endpoint with malicious SQL syntax in the lang parameter. By comparing application behavior between truthy and falsy conditional payloads, the attacker reconstructs database content character by character. Refer to Exploit-DB #45446 and the VulnCheck Advisory on Collectric CMU SQL Injection for technical details on the request structure and payload format.

Detection Methods for CVE-2018-25379

Indicators of Compromise

  • HTTP POST or GET requests to the Collectric CMU login endpoint containing SQL keywords such as SLEEP, BENCHMARK, UNION, SELECT, AND 1=1, or OR 1=2 inside the lang parameter.
  • Repeated authentication attempts from a single source with sequentially varying lang values, indicating automated blind injection tooling.
  • Anomalous database response latency correlated with login requests containing time-delay functions.

Detection Strategies

  • Deploy web application firewall rules that flag SQL metacharacters and known blind-injection signatures in the lang parameter.
  • Enable SQL query logging on the backend database and alert on statements containing concatenated language values mixed with SQL control syntax.
  • Correlate HTTP access logs with database slow-query logs to surface time-based blind injection attempts.

Monitoring Recommendations

  • Baseline normal login request volume and alert on bursts of failed authentications originating from a single IP address.
  • Monitor outbound network connections from the CMU host that deviate from expected operational patterns, which may indicate post-exploitation data staging.
  • Forward web server and database logs to a centralized analytics platform for retrospective hunting of injection payloads in the lang parameter.

How to Mitigate CVE-2018-25379

Immediate Actions Required

  • Restrict network access to the Collectric CMU 1.0 login interface using firewall allow-lists or VPN-only access.
  • Place a web application firewall in front of the application with rules blocking SQL injection patterns in the lang parameter.
  • Review authentication and database logs for prior exploitation indicators and rotate any credentials that may have been exposed.

Patch Information

No vendor patch is referenced in the public CVE record. Operators should contact the vendor through the Our Energy Homepage to confirm whether a fixed release of Collectric CMU is available. If no patch is available, isolate the application until a remediation can be applied.

Workarounds

  • Implement an upstream reverse proxy that strictly validates the lang parameter against an allow-list of expected language codes such as en or sv.
  • Disable or remove the login workflow accepting the lang parameter if it is not required for production use.
  • Apply database least-privilege principles so the account used by the application cannot read sensitive tables or execute administrative statements.
bash
# Example WAF rule (ModSecurity) to block SQLi patterns in the lang parameter
SecRule ARGS:lang "@rx (?i)(union|select|sleep\s*\(|benchmark\s*\(|or\s+1=1|and\s+1=1|--|;)" \
    "id:1002018,phase:2,deny,status:403,log,msg:'Possible SQLi in lang parameter (CVE-2018-25379)'"

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

Default Legacy - Prefooter | Experience the World’s Most Advanced Cybersecurity Platform

Experience the Most Advanced Cybersecurity Platform

See how the world’s most intelligent, autonomous cybersecurity platform can protect your organization today and into the future.