CVE-2026-112106 (GCVE-0-2026-112106)
Vulnerability from cvelistv5 – Published: 2026-10-19 10:45 – Updated: 2026-10-19 16:35 X_Open Source
VLAI
EPSS
VEX
Title
TufayelLUS TikTok-Video-Downloader-PHP TLS index.php certificate validation
Summary
A security vulnerability has been detected in TufayelLUS TikTok-Video-Downloader-PHP up to c4230497bb23dd9c1f81456fe8a982d951feac0d. Affected by this issue is some unknown functionality of the file index.php of the component TLS Handler. Such manipulation leads to improper certificate validation. It is possible to launch the attack remotely. The attack requires a high level of complexity. The exploitation is known to be difficult. This product takes the approach of rolling releases to provide continious delivery. Therefore, version details for affected and updated releases are not available. The name of the patch is 64c0155abb88e714198241d41b918cefc0d5a42a. It is advisable to implement a patch to correct this issue.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-19 15:35 UTC
Assigner
References
7 references
| URL | Tags |
|---|---|
| https://vuldb.com/vuln/422061 | vdb-entry |
| https://vuldb.com/vuln/422061/cti | signaturepermissions-required |
| https://vuldb.com/cve/CVE-2026-112106 | third-party-advisory |
| https://vuldb.com/submit/1013136 | third-party-advisory |
| https://github.com/TufayelLUS/TikTok-Video-Downlo… | issue-tracking |
| https://github.com/TufayelLUS/TikTok-Video-Downlo… | patch |
| https://github.com/TufayelLUS/TikTok-Video-Downlo… | product |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| TufayelLUS | TikTok-Video-Downloader-PHP |
Affected:
c4230497bb23dd9c1f81456fe8a982d951feac0d
cpe:2.3:a:tufayellus:tiktok-video-downloader-php:*:*:*:*:*:*:*:* |
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
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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.