CVE-2023-4116
XSS in Phpjabbers Taxi Booking Script 2.0
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:NSummary
CVE-2023-4116 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Phpjabbers Taxi Booking Script. Its CVSS base score is 4.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 6% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2023-4116 is a cross-site scripting flaw in PHP Jabbers Taxi Booking 2.0. The issue resides in an unspecified function of the /index.php file, where unsanitized input supplied to the index parameter is reflected back to the browser, enabling injection of arbitrary script code.
An unauthenticated remote attacker can exploit the flaw by sending a crafted URL to a victim user. Successful execution allows the attacker to perform actions in the context of the victim's browser session, such as modifying page content, though the vulnerability does not permit direct data exfiltration or server-side compromise.
Public references, including Packet Storm and Vuldb entries, document the issue but contain no vendor-supplied patches or mitigation guidance; the product maintainer did not respond to early disclosure notification. The associated EPSS score has remained in a narrow band near 0.23 with only modest fluctuation and no pronounced post-disclosure rise.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-54002
Vulnerability Data
A vulnerability classified as problematic was found in PHP Jabbers Taxi Booking 2.0. Affected by this vulnerability is an unknown functionality of the file /index.php. The manipulation of the argument index leads to cross site scripting. The attack can be…
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launched remotely. The associated identifier of this vulnerability is VDB-235963. 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
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.