CVE-2026-40524: FrontAccounting SQL Injection in General Ledger Analytics—HIGH Severity

Technical summary

CVE-2026-40524 is a SQL injection vulnerability in FrontAccounting's get_gl_transactions() function. The filter_type parameter is concatenated directly into a SQL IN() clause without prepared statement parameterization. An authenticated attacker with SA_GLANALYTIC permission can inject a closing parenthesis followed by arbitrary SQL conditions to manipulate query logic. The vulnerability enables boolean-based blind SQL injection with observable response size differentials, allowing systematic extraction of journal entry records from the General Ledger. The issue affects all versions before 2.4.20.

Business impact

Compromise of General Ledger data could expose financial transaction details, account balances, and audit trails to unauthorized parties. For organizations using FrontAccounting for accounting operations, this creates regulatory compliance risk (SOX, GAAP audit requirements), potential financial reporting inaccuracy if data is modified, and reputational damage if a breach becomes public. Insider threats leveraging this vulnerability could alter or exfiltrate sensitive financial records while maintaining plausible deniability through legitimate system access.

Affected systems

FrontAccounting deployments running version 2.4.19 and earlier are vulnerable. Any user or service account provisioned with SA_GLANALYTIC permission (General Ledger Analytics role) can exploit this issue. Organizations should inventory all FrontAccounting instances, identify which user accounts hold this permission, and prioritize patching or access control remediation accordingly.

Exploitability

Exploitation requires valid FrontAccounting credentials and the SA_GLANALYTIC role assignment. No zero-click attack vector exists; the attacker must have authenticated session access. Once a vulnerable account is identified or compromised, the boolean-based blind SQL injection is reliable and repeatable, with response size differentials providing a stable information channel. Tools for automated SQL injection testing would accelerate exploitation, though manual crafting is feasible for a skilled attacker. The barrier to exploitation is moderate authentication access, not technical complexity.

Remediation

Upgrade FrontAccounting to version 2.4.20 or later, which patches the SQL injection by parameterizing the filter_type parameter. Organizations unable to patch immediately should implement compensating controls: restrict SA_GLANALYTIC permission to essential users only, monitor General Ledger access logs for unusual query patterns, and segment database access with network policies if possible. After patching, verify the fix and review audit logs for signs of prior exploitation.

Patch guidance

Install FrontAccounting 2.4.20 or a later stable release. The patch introduces parameterized queries for the get_gl_transactions() function's filter_type parameter. Before patching, back up your database and test in a non-production environment to confirm compatibility with your deployment. After patching, restart the FrontAccounting application server and validate General Ledger reporting functionality with a test user. Verify against the FrontAccounting project advisory and release notes to confirm patch version availability and any migration steps.

Detection guidance

Monitor FrontAccounting application logs and database query logs for suspicious General Ledger access patterns, particularly queries with unusual filter syntax, parentheses, or conditional logic in the filter_type parameter. Search for SQL error messages in application logs that may indicate injection attempts. Review database activity logs for unusual SELECT statements targeting journal entry tables (gl_trans, chart_master) from authenticated users with SA_GLANALYTIC permission. Consider deploying a Web Application Firewall (WAF) rule to detect and block SQL injection payloads in General Ledger query parameters if FrontAccounting is internet-facing.

Why prioritize this

This vulnerability merits immediate attention due to its HIGH CVSS score (8.1), direct impact on financial data confidentiality and system availability, and the authenticated but low-barrier nature of exploitation. General Ledger data is security-critical in any accounting system; compromise affects financial reporting integrity, regulatory compliance, and stakeholder trust. The boolean-based blind SQL injection technique is reliable and difficult to detect without robust logging. Prioritize patching for any FrontAccounting deployment processing real financial data, especially those with multiple users holding analytics roles.

Risk score, explained

The CVSS 3.1 score of 8.1 (HIGH) reflects: (1) network-accessible attack vector with no special access requirements beyond authentication; (2) low attack complexity—standard SQL injection without race conditions or timing constraints; (3) privilege requirement of SA_GLANALYTIC role, preventing unauthenticated exploitation; (4) high confidentiality impact via reliable data exfiltration; (5) high availability impact if injected queries consume excessive resources; (6) no integrity impact under the documented attack surface, though SQL injection theoretically permits modification. The score appropriately elevates this above medium severity due to financial data sensitivity and reliable exploitation mechanics.

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