Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A06:2025 - Insecure Design
ASVS 5.0
V4 - API and Web Service Server-side security enforcement
|
| Impact | Without a CVSS score or EPSS probability, risk assessment relies on attack vector and exploitation signals. The attack requires prior authentication as an administrator role, which limits the threat surface to trusted or compromised administrative accounts. However, the availability of publicly available exploit code confirms the technical feasibility of the attack. The primary risk is financial: an authenticated attacker with administrative privileges can manipulate loan penalty structures to extract value from the lending institution, making this a high-impact vulnerability despite the authentication requirement. The lack of formal severity metrics suggests either the CVE was assigned after initial disclosure or the vendor has not formally scored the vulnerability. Real-world risk is substantial for organizations using this system in production for actual loan management, as financial fraud via negative penalties directly affects revenue and borrower accountability. This is not a false-positive high-CVSS issue; it is a genuine business logic vulnerability with clear financial impact, though limited by authentication requirements. |
| Exploit ScenarioDerived | An administrator account (or an attacker who has compromised an administrator account) accesses the loan plan creation interface and enters a legitimate penalty rate such as 5% in the frontend form. Before the request is submitted, the attacker uses a proxy tool (such as Burp Suite) to intercept the outgoing HTTP POST request and modifies the penalty_rate parameter to a negative value, such as -5%. The server accepts the request without validation and stores the negative penalty rate in the database. Subsequently, when borrowers incur overdue payments, the loan management system applies the negative penalty, effectively crediting the borrower or reducing their owed amount instead of charging them additional fees. Publicly available exploit code demonstrates this technique; see GitHub reference for detailed steps. |
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Alert meAnalysisAIv1 – Apr 01, 2026
SourceCodester Loan Management System v1.0 allows authenticated administrators to submit negative penalty rates for loan overdue payments by bypassing client-side validation through direct HTTP POST manipulation, enabling financial fraud through reversed penalty calculations that benefit borrowers instead of lenders. The vulnerability requires authenticated access but no CVSS score, EPSS probability, or formal patch status is available; however, publicly available exploit code confirms the vulnerability's technical feasibility.
RemediationAI
The primary remediation is to implement server-side validation of the penalty_rate parameter that rejects any negative or zero values before the loan plan is created or updated. This validation must occur on the backend, independent of frontend constraints. Verify that all financial input fields (penalty rates, interest rates, fees) are validated to ensure they fall within acceptable positive ranges before being persisted to the database. Additionally, implement role-based access controls to restrict loan plan creation to only authorized administrators, and audit existing loan plans in the database to identify any with negative penalty rates that may indicate prior exploitation. Contact SourceCodester directly at the vendor's official security contact for availability of a patched version; consult the GitHub PoC at https://github.com/meifukun/Web-Security-PoCs/blob/main/Loan-Management-System/BusinessLogic-LoanPlan-NegativePenalty.md for technical details of the bypass mechanism. No vendor-released patch is independently confirmed from available data.
Affected VersionsENISA
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Technical ContextAI · show details
The vulnerability stems from inadequate server-side input validation in the loan plan creation functionality. The application implements frontend JavaScript constraints that reject negative values in the 'Monthly Overdue Penalty' field, but these client-side controls are not mirrored by corresponding backend validation logic. An authenticated attacker can intercept the HTTP POST request containing the penalty_rate parameter and modify it to contain a negative number before it reaches the server. The server accepts this negative value and stores it in the database, causing the loan penalty calculation logic to invert the intended behavior-instead of charging borrowers additional fees for overdue payments, the system credits borrowers or reduces their principal, depending on how the penalty is applied in downstream calculations. This is a business logic flaw rather than a memory corruption or authentication bypass vulnerability, though it may be tagged as such due to the nature of its impact on authorization controls over financial transactions.
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Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:N
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
Lifecycle Timeline
2DescriptionCVE.org
A Business Logic vulnerability exists in SourceCodester Loan Management System v1.0 due to improper server-side validation. The application allows administrators to create "Loan Plans" with specific penalty rates for overdue payments. While the frontend interface prevents users from entering negative numbers in the "Monthly Overdue Penalty" field, this constraint is not enforced on the backend. An authenticated attacker can bypass the client-side restriction by manipulating the HTTP POST request to submit a negative value for the penalty_rate.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Authentication bypass attacks exploit flaws in the verification mechanisms that control access to systems and applications.
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EUVD-2026-17895
NVD
CVE.org
EPSS
Vulnrichment
GitHub
Exploit-DB