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Detecting Unauthorized Modification and Deletion of Sensitive PostgreSQL Database Records Through Database Activity Monitoring and Integrity Validation

Description

Organizations use PostgreSQL databases to store business-critical information such as customer records, employee information, financial data, application records, and operational data.

Unauthorized modification or deletion of database records can compromise data integrity and may result in incorrect business decisions, loss of important information, compliance issues, and operational disruption.

If a compromised or unauthorized database account has excessive privileges, an attacker may modify or delete sensitive records without authorization.

In this project, a real PostgreSQL application is deployed locally on Ubuntu Linux inside an isolated VirtualBox laboratory. Synthetic sensitive records are created and stored in the PostgreSQL database.

A controlled unauthorized database activity scenario is then simulated using a designated security-testing account. The account is intentionally provided with excessive database privileges for the purpose of the laboratory test.

The test account performs controlled modification and deletion of synthetic records. Wazuh is used to monitor relevant PostgreSQL and system activity, while OpenSearch is used for centralized security investigation.

Database integrity is validated by comparing the original database state with the modified state. After detection, the excessive privileges are removed and the affected records are restored from the controlled backup.

The same unauthorized activity is then retested to confirm that the account can no longer modify or delete protected records.

The complete workflow is: PostgreSQL → Synthetic Sensitive Records → Secure Baseline → Excessive Database Privileges → Controlled Unauthorized Modification/Deletion → Activity Monitoring → Wazuh Detection → OpenSearch Investigation → Integrity Assessment → Privilege Remediation → Data Restoration → Retesting → Integrity Validation

Existing Security Problem

Application: PostgreSQL

PostgreSQL is the real open-source database application used in this project. It is installed on Ubuntu Linux and configured as a local database server. The database contains synthetic records representing customer information, employee information, financial records, product information, and internal business records.

The security problem occurs when a database account has more privileges than required. An account with excessive privileges may be able to perform database operations that should be restricted, including modification and deletion of sensitive records.

Existing Problem:

The insecure situation occurs when excessive database privileges allow a database user to perform unauthorized UPDATE and DELETE operations against sensitive PostgreSQL tables, resulting in compromised data integrity.

The security problem is therefore:

Database User → Excessive Privileges → Sensitive PostgreSQL Tables → Unauthorized UPDATE / DELETE → Data Integrity Compromised

The proposed solution introduces database least privilege, database activity monitoring, audit logging, data-integrity validation, backup and recovery, security alerting, centralized investigation, privilege remediation, post-remediation validation, and continuous monitoring.

Attack

Specific Attack: Unauthorized Modification and Deletion of Sensitive PostgreSQL Records

The controlled attack scenario demonstrates how an account with excessive privileges could modify or delete sensitive database records. The activity is performed against the isolated laboratory using a designated test account and synthetic records only.

The assessment focuses on database-account privileges, unauthorized UPDATE operations, unauthorized DELETE operations, affected records, affected tables, database activity visibility, security-event monitoring, incident investigation, database-integrity impact, privilege remediation, data restoration, and post-remediation access restrictions.

Attack Behavior:
PostgreSQL Server
→
Synthetic Sensitive Records
→
Database Test Account
→
Excessive Privileges
→
Unauthorized UPDATE
→
Unauthorized DELETE
→
Database Integrity Impact
→
Wazuh Monitoring
→
OpenSearch Investigation
→
Privilege Removal
→
Data Restoration
→
Retesting
→
Unauthorized Modification Blocked

Security Concept

Database Integrity and Least-Privilege Access Control:

The primary security concepts are Data Integrity, Database Activity Monitoring, Least-Privilege Access Control, and Unauthorized Change Detection.

Sensitive database records should not be modified or deleted unless the operation is authorized. The security workflow combines database access control, database activity monitoring, unauthorized-change detection, security investigation, privilege remediation, data restoration, integrity validation, and continuous monitoring.

The secure processing flow is:

Sensitive Database
→
Database Access Control
→
Database Activity Monitoring
→
Unauthorized Change Detection
→
Security Investigation
→
Privilege Remediation
→
Data Restoration
→
Integrity Validation
→
Continuous Monitoring

Defensive Mechanism

Database Least Privilege

Database users receive only the permissions required for their legitimate tasks.

Purpose

Prevent unauthorized users from modifying or deleting sensitive records.

Database Activity Monitoring

PostgreSQL activity is monitored for suspicious database operations.

Purpose

Detect unexpected modification and deletion activity.

Audit Logging

Relevant database activity is recorded.

Purpose

Provide evidence for security investigation.

Data Integrity Validation

Database records are compared against the known-good baseline.

Purpose

Identify unauthorized changes.

Backup and Recovery

A controlled backup of the test database is maintained.

Purpose

Allow affected records to be restored after a simulated integrity incident.

Security Alerting

Suspicious database activity is monitored through Wazuh.

Purpose

Provide visibility into potentially unauthorized database operations.

Centralized Investigation

Security events are analyzed using OpenSearch.

Purpose

Establish the timeline and investigate affected systems and accounts.

Privilege Remediation

Excessive database permissions are removed.

Purpose

Prevent the test account from continuing unauthorized database operations.

Post-Remediation Validation

The same controlled activity is repeated after privilege remediation.

Purpose

Verify that unauthorized modification and deletion are prevented.

Continuous Monitoring

Database and system monitoring remains active.

Purpose

Detect future unauthorized database activity.

Security Tools

Target Application: PostgreSQL

PostgreSQL is the real open-source database application used in the project.

Purpose
  • Store synthetic sensitive records.
  • Provide database user accounts.
  • Configure database permissions.
  • Generate database activity.
  • Demonstrate unauthorized modification and deletion.

Security Monitoring Tool: Wazuh

Wazuh is used for centralized security monitoring.

Purpose
  • Monitor PostgreSQL-related logs.
  • Monitor system activity.
  • Detect relevant security events.
  • Generate alerts.
  • Provide security telemetry.

Investigation Platform: OpenSearch

OpenSearch is used to investigate the security events collected by Wazuh.

Purpose
  • Search security events.
  • Review timestamps.
  • Investigate database activity.
  • Identify affected systems.
  • Establish an incident timeline.

Security Testing Platform: Kali Linux

Kali Linux is used as the authorized security-testing system.

Purpose
  • Connect to the PostgreSQL laboratory.
  • Use the designated test account.
  • Perform controlled UPDATE and DELETE operations.
  • Validate database permissions.
  • Verify post-remediation restrictions.

Automation and Integrity Validation Tool: Python

Python is used for synthetic data generation and database-integrity validation.

Purpose
  • Generate synthetic database records.
  • Insert test data.
  • Record the baseline database state.
  • Compare records before and after testing.
  • Validate post-remediation integrity.

Target Platform: Ubuntu Linux

Ubuntu hosts PostgreSQL.

Purpose
  • Run PostgreSQL.
  • Store database configuration and logs.
  • Host monitoring components.
  • Provide the database server environment.

Virtualization Platform: VirtualBox

VirtualBox provides the isolated laboratory environment.

Purpose
  • Host Ubuntu.
  • Host Kali Linux.
  • Create an isolated network.
  • Prevent accidental interaction with production systems.

Process

STEP 01

Prepare the Isolated Laboratory

  • Install VirtualBox.
  • Create an Ubuntu virtual machine.
  • Create a Kali Linux virtual machine.
  • Configure an isolated virtual network.
  • Assign laboratory IP addresses.
  • Verify required connectivity.
  • Ensure the environment is isolated from production systems.
Tools: VirtualBox + Ubuntu + Kali Linux
STEP 02

Install PostgreSQL

  • Install PostgreSQL on Ubuntu.
  • Start the PostgreSQL service.
  • Verify that PostgreSQL is running.
  • Configure the laboratory database.
  • Create an administrator test account.
  • Verify database connectivity.
Tools: PostgreSQL
STEP 03

Create the Test Database

  • Create a dedicated laboratory database.
  • Create synthetic records representing organizational information.
  • Ensure all records are fictional.
Tools: PostgreSQL + Python
STEP 04

Establish the Secure Baseline

  • Create an authorized application/test user.
  • Assign only the permissions required for normal operations.
  • Verify authorized SELECT operations.
  • Verify that unauthorized modification is prevented.
  • Verify that unauthorized deletion is prevented.
  • Record the database privileges.
  • Record the initial database state.
Tools: PostgreSQL + Kali Linux
STEP 05

Create a Database Integrity Baseline

  • Export or back up the test database.
  • Record the number of records.
  • Record important test values.
  • Calculate integrity information for selected records where appropriate.
  • Store the baseline securely.
  • Use the baseline later to determine whether unauthorized modifications occurred.
Tools: PostgreSQL + Python
STEP 06

Configure Database Monitoring

  • Configure PostgreSQL logging for the required laboratory activity.
  • Identify relevant log locations.
  • Configure Wazuh to monitor the PostgreSQL-related logs.
  • Generate normal database activity.
  • Verify that Wazuh receives the relevant events.
Tools: PostgreSQL + Wazuh
STEP 07

Introduce the Controlled Excessive Privilege

  • Create a designated test account.
  • Provide the account with excessive permissions within the isolated laboratory.
  • Record the original privilege configuration.
  • Record the intentionally excessive privilege configuration.
  • Verify that the test account can perform the intended laboratory operations.
  • Ensure the account exists only for the controlled security scenario.
Tools: PostgreSQL
STEP 08

Perform Controlled Unauthorized Modification

  • Using the designated test account, select a synthetic record.
  • Perform a controlled UPDATE operation.
  • Change a predefined test value.
  • Record the affected record.
  • Record the timestamp.
  • Preserve the database activity evidence.
Tools: Kali Linux + PostgreSQL
STEP 09

Perform Controlled Unauthorized Deletion

  • Using the same designated test account, select another synthetic test record.
  • Perform a controlled DELETE operation.
  • Record the affected record.
  • Record the timestamp.
  • Preserve the test evidence.
  • Ensure that only synthetic test data is deleted.
Tools: Kali Linux + PostgreSQL
STEP 10

Detect the Database Activity

  • Allow Wazuh to collect the relevant PostgreSQL/system events.
  • Review the generated security events.
  • Identify the database account involved.
  • Identify the affected system.
  • Identify the activity timestamp.
  • Identify the relevant database activity where available.
Tools: Wazuh
STEP 11

Investigate Through OpenSearch

  • Open the relevant Wazuh events.
  • Search for PostgreSQL-related activity.
  • Review the test account activity.
  • Correlate timestamps.
  • Identify modification and deletion activity.
  • Establish the incident timeline.
  • Document the security finding.
Tools: Wazuh + OpenSearch
STEP 12

Validate Data Integrity Impact

  • Compare the current database state with the original baseline.
  • Identify modified records.
  • Identify deleted records.
  • Compare original and current values.
  • Determine the number of affected records.
  • Identify the affected tables.
  • Document the integrity impact.
Tools: Python + PostgreSQL
STEP 13

Assess the Security Risk

  • Evaluate excessive database privileges.
  • Evaluate unauthorized modification.
  • Evaluate unauthorized deletion.
  • Evaluate the number of affected records.
  • Evaluate the type of affected information.
  • Evaluate potential business impact.
  • Evaluate potential privacy impact.
  • Evaluate monitoring visibility.
  • Evaluate recovery capability.
  • Assign an appropriate risk level to the finding.
Tools: PostgreSQL + Wazuh + OpenSearch
STEP 14

Remove Excessive Privileges

  • Revoke unnecessary permissions from the test account.
  • Apply least-privilege access.
  • Restrict modification permissions.
  • Restrict deletion permissions.
  • Verify the final privilege configuration.
  • Record the remediation.
Tools: PostgreSQL
STEP 15

Restore the Affected Records

  • Restore the deleted test record from the controlled backup or recreate the original synthetic record.
  • Restore the modified record to its original state.
  • Verify the values.
  • Compare the database with the original baseline.
  • Confirm that the expected records have been restored.
Tools: PostgreSQL + Python
STEP 16

Retest Unauthorized Modification

  • Using the same test account, attempt the previously performed UPDATE operation.
  • Verify that the operation is denied or restricted according to the corrected permissions.
  • Record the result.
  • Compare with the pre-remediation result.
Tools: Kali Linux + PostgreSQL
STEP 17

Retest Unauthorized Deletion

  • Attempt the previously performed DELETE operation.
  • Verify that deletion is denied.
  • Record the result.
  • Confirm that the protected record remains unchanged.
  • Preserve the evidence.
Tools: Kali Linux + PostgreSQL
STEP 18

Perform Final Data Integrity Validation

  • Compare the database with the original baseline.
  • Verify record counts.
  • Verify selected record values.
  • Verify the previously affected records.
  • Confirm unauthorized changes are no longer possible.
  • Review Wazuh events.
  • Review OpenSearch investigation results.
  • Confirm monitoring remains operational.
  • Document the final security status.
Tools: PostgreSQL + Python + Wazuh + OpenSearch

Outcome

  1. A real PostgreSQL application is successfully deployed on Ubuntu, providing a practical database-security environment without requiring AWS, Windows, or an existing production application.
  2. Synthetic sensitive records are created and stored in PostgreSQL, allowing the entire security scenario to be performed safely without using real organizational information.
  3. A secure database-access baseline is established, documenting legitimate user permissions and the initial integrity state of the test database.
  4. A controlled excessive-privilege scenario is successfully reproduced, demonstrating how excessive database permissions can enable unauthorized modification and deletion of sensitive records.
  5. Controlled unauthorized UPDATE and DELETE operations are performed against synthetic records, demonstrating the potential impact on database integrity.
  6. Wazuh monitors relevant PostgreSQL and system activity, providing security telemetry for the simulated incident.
  7. OpenSearch enables centralized investigation, allowing the security analyst to review database-related activity, timestamps, affected systems, and the test account involved.
  8. Database-integrity validation identifies the affected records, demonstrating the difference between the original known-good state and the modified database state.
  9. Excessive database privileges are removed and least-privilege access is applied, reducing the ability of the test account to perform unauthorized database operations.
  10. Affected synthetic records are restored, demonstrating the recovery capability following a controlled data-integrity incident.
  11. Post-remediation testing confirms that unauthorized modification and deletion are restricted, validating the effectiveness of the corrected database permissions.
  12. The complete real PostgreSQL deployment, synthetic sensitive-data creation, secure access baseline, database privilege configuration, controlled unauthorized modification and deletion, Wazuh monitoring, OpenSearch investigation, data-integrity assessment, privilege remediation, record restoration, post-remediation testing, and continuous monitoring workflow is successfully demonstrated.
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