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CVE-2026-71518 – Authorization Bypass (Unauthenticated Media File Disclosure) – Typemill < 2.26.0

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Summary

CVE-2026-71518 is an authorization bypass vulnerability in Typemill, an open-source flat-file PHP CMS, affecting the media file download route. Unauthenticated attackers can submit path-equivalent URL variants to retrieve files that administrators have restricted to privileged roles. The flaw carries a CVSS v4.0 base score of 8.7 (High) / CVSS v3.1 base score of 7.5 (High), with confidentiality impact but no effect on integrity or availability.

Technical details

  • Root cause: Typemill’s media file download route makes its access-control decision against the raw, un-normalized request path, but retrieves the file from the filesystem-resolved path — the two representations can diverge.
  • Trigger conditions: an attacker requests a restricted media file using a path-equivalent variant (e.g. a dot-slash prefix, a doubled slash, or a percent-encoded path segment) instead of the canonical path.
  • Attack vector: network, no authentication and no user interaction required (AV:N/AC:L/PR:N/UI:N).
  • Impact: disclosure of media files that were explicitly restricted to specific roles, without valid credentials; integrity and availability are not affected.

Affected software

  • Typemill: all versions prior to 2.26.0

Severity

  • CVSS v3.1: 7.5 (High) — AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
  • CVSS v4.0: 8.7 (High) — AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N

Mitigation and recommended actions

  • Immediate: upgrade Typemill to version 2.26.0 or later, which normalizes the request path once and uses that canonical value for both the restriction check and the file read.
  • If no patch: restrict or disable public access to the media file download route at the web server or reverse proxy layer, and reject requests containing dot-slash, doubled-slash, or percent-encoded path segments before they reach the application.

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.

  • HTTP response header x-powered-by: Typemill
  • Meta tag generator content: TYPEMILL

References

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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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