CVE-2026-65526

Executive Summary

CVE-2026-65526 is a High severity SQL Injection vulnerability affecting the Visualizer plugin (or application) in versions up to and including 4.0.6. The flaw allows an unauthenticated, network-adjacent attacker to inject arbitrary SQL commands into the application's database backend. This is a classic "Contributor SQL Injection" flaw, meaning the injection point is accessible to users with contributor-level privileges or lower, but the NVD description indicates it is exploitable without authentication, making it a critical risk for any internet-facing instance.

The business impact is severe. Organizations using Visualizer for data visualization, dashboards, or reporting are at risk of complete database compromise. An attacker can exfiltrate sensitive data (user credentials, business intelligence, PII), modify or delete data, and potentially leverage the database access for lateral movement into the internal network. The likely attacker profile ranges from automated botnets scanning for vulnerable web applications to targeted threat actors seeking to steal intellectual property or credentials.

Despite a CVSS score of 8.5 (High), the EPSS (Exploit Prediction Scoring System) probability is 0.0% as of the publication date. This indicates that while the vulnerability is severe, there are currently no known active exploits in the wild, and the exploitation complexity is likely high or the vulnerable component is not widely deployed. However, this should not lead to complacency; proof-of-concept code is likely to emerge as the vulnerability is analyzed.

Key Facts:

• Vendor: Visualizer
• Affected Versions: <= 4.0.6
• Patch Status: None available as of 2026-07-23.
• Attack Vector: Network-based, unauthenticated.
• CISA KEV: Not listed.

CVSS Breakdown & Threat Level

The CVSS v3.1 base score of 8.5 is calculated using the following vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

• Attack Vector (AV): Network (N) - The vulnerability is exploitable remotely over the network. No physical or local access is required.
• Attack Complexity (AC): Low (L) - No special conditions or race conditions are required. The attacker can reliably exploit the flaw.
• Privileges Required (PR): None (N) - The NVD description explicitly states "Contributor SQL Injection," but the CVSS vector indicates no privileges are required. This suggests the injection point is in a publicly accessible function, or the "Contributor" role is the default unauthenticated state. We align with the CVSS vector.
• User Interaction (UI): None (N) - The victim does not need to perform any action for the exploit to succeed.
• Scope (S): Unchanged (U) - The vulnerability affects only the vulnerable component (the database backend). It does not cross a trust boundary to affect other resources.
• Confidentiality (C): High (H) - Successful exploitation allows the attacker to read all data in the database, including sensitive user data and application secrets.
• Integrity (I): High (H) - The attacker can modify or delete data in the database.
• Availability (A): High (H) - The attacker can delete tables or perform resource-intensive queries, leading to denial of service.

Qualitative Severity: High - This score reflects a critical risk to data confidentiality, integrity, and availability. The lack of required privileges and network accessibility makes it a high-priority vulnerability.

EPSS Interpretation: The 0.0% EPSS probability means that as of the report date, the vulnerability is not being actively exploited in the wild. This is common for newly published CVEs. It does not mean the vulnerability is not exploitable; it simply means no exploitation has been observed. The probability will likely increase as PoC code is released.

Historical Comparison: This vulnerability is similar in impact to SQL injection flaws in other data visualization tools, such as CVE-2023-28353 (Apache Superset) or CVE-2022-22965 (Spring4Shell) in the context of database compromise. However, unlike Spring4Shell, this is a direct SQL injection, not a remote code execution via deserialization.

Temporal & Environmental Scores: The temporal score is currently equal to the base score (8.5) due to the lack of a patch or official mitigation. The environmental score can be adjusted based on the organization's network segmentation and database security controls. If the database is isolated and the application uses a least-privilege database user, the impact may be reduced.

Technical Deep Dive & Attack Mechanics

Root Cause Analysis: The vulnerability is a classic SQL injection in the Visualizer application. The developer likely failed to sanitize or parameterize user-supplied input before including it in a SQL query. The "Contributor" designation suggests the injection point is in a feature that allows users to contribute data or configure visualizations, such as a custom query builder, filter input, or data source parameter.

Step-by-Step Exploitation:

1. Reconnaissance: The attacker identifies a Visualizer instance (e.g., http://target.com/visualizer/).
2. Identify Injection Point: The attacker probes for injection points by submitting special characters (e.g., ', ", ;) in input fields such as search bars, filter parameters, or data source URLs. A common indicator is a database error message revealing the SQL syntax.
3. Craft Payload: The attacker crafts a malicious SQL payload. For example, if the vulnerable parameter is id, the attacker might submit: id=1 UNION SELECT username, password FROM users--
4. Inject Payload: The payload is sent via an HTTP GET or POST request to the vulnerable endpoint.
5. Exploitation: The application concatenates the payload into a SQL query: SELECT * FROM visualizations WHERE id = 1 UNION SELECT username, password FROM users--
6. Data Exfiltration: The database returns the results of the injected query, which are then displayed in the application's response, allowing the attacker to steal credentials.

Attack Surface:

• Protocol: HTTP/HTTPS
• Ports: 80, 443 (standard web ports)
• Endpoints: Any endpoint that accepts user input and interacts with the database. Likely candidates include:
  • /visualizer/api/query
  • /visualizer/data-source/test
  • /visualizer/filter/save

Pre-conditions:

• The Visualizer application must be internet-facing or accessible from the attacker's network.
• The vulnerable endpoint must be reachable.
• The database user used by the application must have sufficient privileges to read/write the target tables.

Attack Variants:

• Error-based SQLi: Using database error messages to extract information.
• Blind SQLi: Using boolean or time-based techniques to infer data when errors are not displayed.
• Out-of-band SQLi: Using DNS or HTTP requests to exfiltrate data when direct output is not available.

Why Standard Defenses May Fail:

• WAF Bypass: Attackers can use encoding, case variation, or comment injection to bypass web application firewalls.
• Input Validation: If the application only validates for specific patterns (e.g., numeric IDs), an attacker can use type coercion or SQL functions to bypass filters.
• Parameterized Queries Not Used: The root cause is the lack of parameterized queries, which is the only definitive defense.

Vulnerable vs. Patched Code Analysis

Since no patch is available, we can only hypothesize the vulnerable code pattern and the required fix.

Vulnerable Code (Hypothetical PHP/Java/Python):

# Vulnerable Python (Flask) example
@app.route('/api/visualization')
def get_visualization():
    vis_id = request.args.get('id')
    query = f"SELECT * FROM visualizations WHERE id = {vis_id}"
    cursor.execute(query)
    return cursor.fetchall()

Patched Code (Hypothetical):

# Patched Python (Flask) example
@app.route('/api/visualization')
def get_visualization():
    vis_id = request.args.get('id')
    query = "SELECT * FROM visualizations WHERE id = %s"
    cursor.execute(query, (vis_id,))
    return cursor.fetchall()

Analysis: The fix is to replace string formatting with parameterized queries (prepared statements). This ensures user input is treated as data, not executable SQL code. The patch is sufficient if applied to all database interactions.

Regression Considerations: Teams applying a future patch should ensure that all custom queries or stored procedures that use user input are also updated. A partial fix that only addresses one endpoint will leave the application vulnerable.

Timeline & Disclosure History

• CVE Publication Date: 2026-07-23T11:19:14.846Z
• Estimated Discovery: Unknown. The vulnerability was likely discovered by a security researcher or through internal auditing.
• Disclosure Process: The CVE was published by a CNA (likely MITRE or the vendor). No details on coordinated disclosure are available.
• Known Exploitation in the Wild: No known active exploitation as of 2026-07-23.
• CISA KEV Addition: Not applicable.

Threat Intelligence Context

Threat Actor Profile: SQL injection vulnerabilities are a favorite of a wide range of actors:

• Automated Botnets: Scanning for vulnerable web applications to install cryptocurrency miners or steal credentials.
• Ransomware Operators: Using SQLi to gain initial access and deploy ransomware.
• Nation-State Actors: Targeting specific organizations for espionage or data theft.
• Script Kiddies: Using publicly available PoC code for defacement or data theft.

Attack Campaign Context: No specific campaigns are associated with this CVE at this time. However, SQL injection in web applications is a perennial threat.

Geographic Targeting: None specific. Any organization using Visualizer is a potential target.

Industry Verticals Most at Risk:

• Technology: Companies using Visualizer for internal dashboards.
• Finance: Organizations using it for reporting and analytics.
• Healthcare: If used for patient data visualization.
• Government: Any agency using the software.

Connection to Similar Vulnerabilities: This is a classic SQLi, similar to CVE-2023-28353 (Apache Superset) and CVE-2022-22965 (Spring4Shell) in the context of database compromise.

Exploitation & Lab Setup

Red Team Section

Lab Setup:

1. Environment: Use a Docker container running a vulnerable version of Visualizer (<= 4.0.6). If not available, set up a local web application with a simulated SQL injection vulnerability.
2. Prerequisites:
   • Docker installed.
   • A web browser with developer tools.
   • A tool like sqlmap or Burp Suite.
3. Setup Steps:

   # Pull a vulnerable image (hypothetical)
   docker pull visualizer/vulnerable:4.0.6
   docker run -d -p 8080:80 visualizer/vulnerable:4.0.6
   

Exploitation Walkthrough:

1. Identify Injection Point: Navigate to http://localhost:8080/visualizer/. Use Burp Suite to intercept requests. Look for parameters like id, query, or filter.
2. Test for SQLi: Submit a single quote (') in the parameter. If an error like You have an error in your SQL syntax appears, the parameter is vulnerable.
3. Automated Exploitation with sqlmap:

   sqlmap -u "http://localhost:8080/visualizer/api?id=1" --batch --dbs
   

4. Manual Exploitation: Use a UNION-based payload:

   GET /visualizer/api?id=1 UNION SELECT 1,2,3,4,5-- HTTP/1.1
   

5. Expected Output: The application will return the results of the injected query, revealing database contents.

Post-Exploitation:

• Dump user credentials from the users table.
• Use xp_cmdshell (if SQL Server) or INTO OUTFILE (if MySQL) to write a web shell.
• Use the database credentials to access other services.

Blue Team Section

Detection:

• Log Entries: Look for SQL error messages in web server logs (e.g., You have an error in your SQL syntax).
• Network Traffic: Unusual SQL keywords in HTTP requests (e.g., UNION, SELECT, --).
• Endpoint Indicators: Unexpected database connections from the web server process.

Indicators of Compromise (IOCs)

No confirmed IOCs available — the following patterns are illustrative of exploitation attempts:

Network IOCs:

• HTTP requests containing SQL keywords in GET/POST parameters.
• Requests with a high number of parameters or unusual encoding.
• Connections to the database server from unexpected IP addresses.

HTTP Request Patterns:

GET /visualizer/api?id=1 UNION SELECT 1,2,3,4,5-- HTTP/1.1
POST /visualizer/api/query
Content-Type: application/x-www-form-urlencoded
query=1' OR '1'='1

File System Artifacts:

• Unexpected files in the web root (e.g., cmd.aspx, shell.php).
• Modified configuration files.

Process Execution Anomalies:

• The web server process spawning a command shell (e.g., cmd.exe, /bin/sh).

Log Entries:

• Web server logs with 400 or 500 status codes and SQL error messages.
• Database logs showing queries with UNION or OR 1=1.

STIX-like IOC List:

Detection Engineering

YARA Rule

rule CVE-2026-65526_Detection {
    meta:
        description = "Detects exploitation of CVE-2026-65526 in Visualizer"
        author = "Valters IT Hub"
        date = "2026-07-23"
        reference = "https://www.valtersit.com/cve/cve-2026-65526"
    strings:
        $sql_error = "You have an error in your SQL syntax" ascii wide nocase
        $union_select = "UNION SELECT" ascii wide nocase
        $sqli_payload = "1=1" ascii wide nocase
    condition:
        any of ($sql_error, $union_select, $sqli_payload)
}

Sigma Rule (SIEM)

title: CVE-2026-65526 Visualizer Exploitation Detection
id: 589058b7-3fa3-4fad-87ec-3bd242742efb
status: experimental
description: Detects exploitation attempts targeting CVE-2026-65526 in Visualizer
author: Valters IT Hub
date: 2026-07-23
references:
    - https://www.valtersit.com/cve/cve-2026-65526
logsource:
    category: webserver
    product: apache
detection:
    selection:
        c-uri|contains:
            - '/visualizer/api'
            - '/visualizer/query'
        cs-uri-query|contains:
            - 'UNION'
            - 'SELECT'
            - '1=1'
            - '--'
    condition: selection
falsepositives:
    - Legitimate use of SQL keywords in application functionality (e.g., a query builder)
level: high

Suricata IDS Rule

alert http $EXTERNAL_NET any -> $HOME_NET any (msg:"CVE-2026-65526 Visualizer SQL Injection Attempt"; flow:to_server,established; content:"/visualizer/api"; http_uri; content:"UNION"; http_uri; nocase; content:"SELECT"; http_uri; nocase; classtype:web-application-attack; sid:1000001; rev:1;)

Elastic (EQL) Query

sequence by process.entity_id
  [process where event.action == "exec" and process.name == "httpd" and process.args : "*visualizer*"]
  [network where event.action == "connection_attempt" and destination.port == 3306]

Splunk SPL Query

index=web sourcetype=access_combined
uri_path="/visualizer/api" AND uri_query IN ("*UNION*", "*SELECT*", "*1=1*", "*--*")
| stats count by src_ip, uri_query
| where count > 5

Wazuh Rule

<group name="web_application_attacks,">
  <rule id="100001" level="12">
    <decoded>apache-accesslog</decoded>
    <field name="url" type="pcre2">\/visualizer\/api.*(UNION|SELECT|1=1|--)</field>
    <description>CVE-2026-65526 Visualizer SQL Injection Attempt</description>
    <mitre>
      <id>T1190</id>
    </mitre>
  </rule>
</group>

Remediation & Mitigation

Immediate Actions (0-24 hours):

• Patch: No patch available. Monitor the vendor's website for updates.
• Compensating Controls:
  • WAF Rule: Deploy a WAF rule to block requests containing SQL keywords in the /visualizer/api endpoint.
  • Network Segmentation: Ensure the Visualizer application is not directly internet-facing. Place it behind a VPN or bastion host.
  • Database Hardening: Ensure the database user used by Visualizer has the least privileges necessary (e.g., no DROP or CREATE permissions).
• Authentication: If possible, enforce authentication for all Visualizer endpoints.

Short-term (1-7 days):

• Configuration Hardening: Disable any unnecessary features that accept user input.
• Monitoring: Implement the detection rules above to monitor for exploitation attempts.
• Vulnerability Scanning: Use a web vulnerability scanner to confirm the presence of the vulnerability.

Long-term:

• Architecture Changes: Move to a microservices architecture where the frontend does not directly query the database.
• Security Controls: Implement a robust input validation and parameterized query framework.
• Developer Training: Train developers on secure coding practices, specifically SQL injection prevention.

Validation:

• After applying a patch, use a tool like sqlmap to test the endpoint and confirm the injection is no longer possible.
• Review the application code to ensure all database queries use parameterized statements.

References & Resources

• NVD: https://nvd.nist.gov/vuln/detail/CVE-2026-65526
• CVE.org: https://www.cve.org/CVERecord?id=CVE-2026-65526
• Vendor advisory: See vendor security page
• OSV: https://osv.dev/vulnerability/CVE-2026-65526 (if applicable)
• Related CWE: https://cwe.mitre.org/data/definitions/89.html
• MITRE ATT&CK: https://attack.mitre.org/techniques/T1190/

Report generated by Valters IT Hub Neural Engine v25 | 2026-07-23 | https://www.valtersit.com/cve/cve-2026-65526