Cyber Resilience

CVE-2026-56287

SQLi in Apache Fineract ≤ 1.15.0

Published
15 July 2026
Modified
15 July 2026
Patch / advisory
CVSS Score v3.1 8.1
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N
EPSS Score 0.0065 50th percentile
Risk Priority 61 floored blend · peak EPSS

CVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.

Summary

CVE-2026-56287 is a high-severity SQL Injection (CWE-89) vulnerability in Apache Fineract. Its CVSS base score is 8.1 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 50th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

A boolean-based SQL Injection vulnerability exists in Apache Fineract's Client Search API (GET /api/v1/clients) in versions up to and including 1.14.0. The orderBy and sortOrder request parameters are concatenated into a SQL query without sufficient validation, allowing an authenticated user…

more

with permission to view clients to inject arbitrary SQL via a crafted orderBy value. This can be leveraged to perform blind boolean-based data extraction and, on MySQL/MariaDB, to disclose arbitrary files readable by the database process via the LOAD_FILE() function. Users are recommended to upgrade to a version containing the fix

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-25196Same product: Apache Fineract
CVE-2024-23539Same product: Apache Fineract
CVE-2024-23538Same product: Apache Fineract
CVE-2023-25197Same product: Apache Fineract
CVE-2023-49736Same vendor: Apache
CVE-2024-36263Same vendor: Apache
CVE-2023-37924Same vendor: Apache
CVE-2023-30867Same vendor: Apache
CVE-2023-31038Same vendor: Apache
CVE-2023-30465Same vendor: Apache

Affected Assets

apache
fineract
≤ 1.15.0

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V6.2.5

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.

Input validation directly stops untrusted data from reaching SQL query construction without neutralization.

Secure engineering principles require parameterized queries and input sanitization that structurally eliminate SQLi.

System monitoring can identify attempted SQLi exploitation via anomalous queries after the weakness exists.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly target injection flaws during coding and review so largely prevent CWE-89 introduction, yet the single broad outcome leaves residual risk from incomplete neutralization techniques or missed edge cases.

PR.AT-02 partial match
prevents

Training raises developer awareness of SQLi risks and can reduce introduction likelihood (partial) but removes none of the actual coding flaw's risk by itself since technical neutralization is still required.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

prevents

Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.

prevents

Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.

prevents

Secure-coding rules and security testing phases mandate the use of parameterized queries or equivalent escaping, preventing the construction of dynamic SQL statements from untrusted input.

prevents

Language-specific secure coding rules, peer review and SAST together prevent the construction of SQL statements from untrusted data without proper parameterization or escaping.

finds

The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.

References