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CVE-2026-66453 – Authentication Bypass – Salon Booking System (WordPress Plugin) ≤ 10.30.26

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Summary

CVE-2026-66453 is a critical unauthenticated authentication bypass vulnerability affecting the Salon Booking System WordPress plugin, developed by Dimitri Grassi. The flaw allows a remote, unauthenticated attacker to bypass the plugin’s authentication mechanism using an alternate path or channel. It carries a CVSS v3.1 base score of 9.8 (Critical), reflecting network-exploitable, low-complexity access with high impact to confidentiality, integrity, and availability.

Technical details

  • Root cause: The plugin implements an authentication-related code path (e.g., password/session recovery or login handling) that can be reached through an alternate channel without validating the requester’s identity, classified as CWE-288 (Authentication Bypass Using an Alternate Path or Channel).
  • Trigger conditions: No authentication or user interaction is required to exploit the flaw; the vulnerable functionality is exposed to any remote requester.
  • Attack vector: Network — the vulnerability is exploitable remotely over HTTP/HTTPS against the WordPress site running the affected plugin.
  • Impact: Successful exploitation allows an unauthenticated attacker to bypass authentication controls, potentially gaining unauthorized access to accounts or protected plugin functionality, with high impact to confidentiality, integrity, and availability.

Affected software

  • Salon Booking System (WordPress Plugin) — all versions up to and including 10.30.26

Severity

  • CVSS v3.1 Base Score: 9.8 (Critical)
  • Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Mitigation and recommended actions

  • Immediate: Update the Salon Booking System plugin to version 10.30.27 or later, which resolves this vulnerability.
  • If immediate patching is not possible: Restrict or disable public access to the plugin’s booking/authentication endpoints until the update can be applied, and monitor site logs for unusual authentication or booking-related requests.

How IONIX identifies potentially affected assets

IONIX matches the following signals against data already collected when it crawled the asset; identifying the technology sends no request beyond that crawl.

  • Raw response body: salon-booking-system/js/

References

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How IONIX’s External Exposure Management Platform Detects and Validates
Zero-Days to Shrink MTTR

1

Map your entire attack surface (continously)

IONIX uses multi-factor discovery methods, including DNS analysis, certificate mapping, metadata inspection, and more, to automatically map every internet-facing asset across your environment. This includes cloud instances, third-party platforms, shadow IT, and even forgotten infrastructure that traditional tools miss.

2

Monitor for new CVEs

Dozens of threat intel feeds using agentic technology are continuously analyzed to detect the appearance of proof-of-concept code, exploit kits, and indicators of active targeting. IONIX goes further by applying AI to proactively evaluate whether emerging vulnerabilities are likely to be exploited, even before PoCs go public.

3

Identify Potential External Exposures

Not all CVEs matter. IONIX filters vulnerabilities by asking attacker-centric questions: Can it be reached from the internet? Does it require authentication? Is it being exploited in the wild? This dramatically reduces noise and focuses teams on threats that can actually be weaponized.

4

Create Safe, Scalable Exploit Validations

IONIX transforms real-world PoCs into safe, non-intrusive test payloads that can be run in production environments without disruption. These simulations are precisely targeted to the systems that are vulnerable, ensuring rapid validation without unnecessary load.

5

Execute Exploit Validations

By combining context about software stack, versioning, exposure status, and reachability, IONIX ensures that only the right payloads are executed against the right assets, maximizing efficiency and minimizing risk.

6

Drive Fast and Actionable Remediation

Results are routed through integrations with ticketing, SOAR, and SIEM tools. Issues are written in plain language, bundled into remediation clusters, and prioritized based on asset criticality, exploitability, and blast radius. This shortens mean time to remediation (MTTR) and empowers teams to act with confidence.

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  • Mapping of all Assets with this Technology
  • Identification of potentially exposed assets to this CVE
  • Confirmation of verified exploitable assets
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