CVE-2026-105472 (GCVE-0-2026-105472)
Vulnerability from cvelistv5 – Published: 2026-10-06 00:30 – Updated: 2026-10-08 02:39
VLAI
EPSS
VEX
Title
girishsaraf Online-Appointment-Booking-System Booking book.php sql injection
Summary
A weakness has been identified in girishsaraf Online-Appointment-Booking-System up to f427b4757128ca253d33d0cc4e87bbb9c999a4d5. The affected element is an unknown function of the file book.php of the component Booking Handler. This manipulation of the argument Doctor/appointment causes sql injection. The attack is possible to be carried out remotely. The exploit has been made available to the public and could be used for attacks. This product adopts a rolling release strategy to maintain continuous delivery. Therefore, version details for affected or updated releases cannot be specified. The project was informed of the problem early through an issue report but has not responded yet.
Severity
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-08 02:39 UTC
Assigner
References
6 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/413618 | vdb-entrytechnical-description |
| https://vuldb.com/vuln/413618/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-105472 | third-party-advisory |
| https://vuldb.com/submit/984338 | third-party-advisory |
| https://github.com/girishsaraf/Online-Appointment… | exploitissue-tracking |
| https://github.com/girishsaraf/Online-Appointment… | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| girishsaraf | Online-Appointment-Booking-System |
Affected:
f427b4757128ca253d33d0cc4e87bbb9c999a4d5
cpe:2.3:a:girishsaraf:online-appointment-booking-system:*:*:*:*:*:*:*:* |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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