Security Resilience

CVE-2024-0459

SQLi in Phpgurukul Blood Bank \& Donor Management System

Public PoCSQLi
Published
12 January 2024
Modified
21 November 2024
CVSS Score v3.1 4.7
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L
EPSS Score 0.0067 51th percentile
Risk Priority 39 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-2024-0459 is a medium-severity SQL Injection (CWE-89) vulnerability in Phpgurukul Blood Bank \& Donor Management System. Its CVSS base score is 4.7 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Protocol or Service Impersonation (T1001.003); ranked in the top 49% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

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 vulnerability has been found in Blood Bank & Donor Management 5.6 and classified as critical. This vulnerability affects unknown code of the file /admin/request-received-bydonar.php. The manipulation leads to sql injection. The attack can be initiated remotely. The exploit has…

more

been disclosed to the public and may be used. The identifier of this vulnerability is VDB-250564.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1001.003 Protocol or Service Impersonation Command And Control
Adversaries may impersonate legitimate protocols or web service traffic to disguise command and control activity and thwart analysis efforts.
T1003 OS Credential Dumping Credential Access
Adversaries may attempt to dump credentials to obtain account login and credential material, normally in the form of a hash or a clear text password.
T1003.001 LSASS Memory Credential Access
Adversaries may attempt to access credential material stored in the process memory of the Local Security Authority Subsystem Service (LSASS).
T1003.002 Security Account Manager Credential Access
Adversaries may attempt to extract credential material from the Security Account Manager (SAM) database either through in-memory techniques or through the Windows Registry where the SAM database is stored.
T1003.003 NTDS Credential Access
Adversaries may attempt to access or create a copy of the Active Directory domain database in order to steal credential information, as well as obtain other information about domain members such as devices, users, and access rights.
T1005 Data from Local System Collection
Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2024-51063Same vendor: Phpgurukul
CVE-2023-6402Same vendor: Phpgurukul
CVE-2023-48718Same vendor: Phpgurukul
CVE-2024-51065Same vendor: Phpgurukul
CVE-2024-0360Same vendor: Phpgurukul
CVE-2023-23162Same vendor: Phpgurukul
CVE-2024-5066Same vendor: Phpgurukul
CVE-2023-39551Same vendor: Phpgurukul
CVE-2024-34987Same vendor: Phpgurukul
CVE-2024-3691Same vendor: Phpgurukul

Affected Assets

phpgurukul
blood bank \& donor management system
all versions

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
blocks

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
blocks

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.

removes
removes
removes
removes
blocks

A.5.6 only improves knowledge flow, awareness of threats/patches and access to specialist advice; it does not stop SQL injection from being exploitable in code that still contains the flaw.

References