CVE-2024-2997
XSS in Bdtask Multi Store Inventory Management System ≤ 20240320
Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:N/I:L/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-2997 is a low-severity Cross-site Scripting (CWE-79) vulnerability in Bdtask Multi Store Inventory Management System. Its CVSS base score is 2.4 (Low).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 34% 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.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
The vulnerability CVE-2024-2997 is a cross-site scripting flaw (CWE-79) in Bdtask Multi-Store Inventory Management System versions up to 20240320. It resides in an unspecified component where user-supplied values for arguments such as Category Name, Model Name, Brand Name, and Unit Name are not properly sanitized before being rendered.
An authenticated attacker with administrative privileges can supply crafted payloads remotely over the network. When another user views the affected pages, the injected script executes in the victim's browser, allowing limited tampering with page content or behavior while requiring user interaction to trigger.
Public references on VulDB include a proof-of-concept disclosure and note that the vendor was contacted before publication but did not respond; no official patches or mitigation steps are documented in the available advisories.
The associated EPSS score has remained low and essentially flat since disclosure, with a current value of 0.0579 and a peak of 0.0594.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-27937
Vulnerability Data
A vulnerability was found in Bdtask Multi-Store Inventory Management System up to 20240320. It has been declared as problematic. Affected by this vulnerability is an unknown functionality. The manipulation of the argument Category Name/Model Name/Brand Name/Unit Name leads to cross…
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site scripting. The attack can be launched remotely. The exploit has been disclosed to the public and may be used. The associated identifier of this vulnerability is VDB-258199. NOTE: The vendor was contacted early about this disclosure but did not respond in any way.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
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.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
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.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.