Misaka Danmu Server up to 2.8.9 /api/ui missing authentication

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
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CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
7.3$0-$5k2.64

Summaryinfo

A vulnerability identified as critical has been detected in Misaka Danmu Server up to 2.8.9. This affects an unknown part of the file /api/ui. This manipulation causes missing authentication. This vulnerability appears as CVE-2026-111644. The attack may be initiated remotely. There is no available exploit.

Detailsinfo

A vulnerability was found in Misaka Danmu Server up to 2.8.9. It has been declared as critical. Affected by this vulnerability is some unknown functionality of the file /api/ui. The manipulation with an unknown input leads to a missing authentication vulnerability. The CWE definition for the vulnerability is CWE-306. The product does not perform any authentication for functionality that requires a provable user identity or consumes a significant amount of resources. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

Misaka Danmu Server through 2.8.9 contains a missing authentication vulnerability that allows unauthenticated attackers to access audit, diagnostics, data-check, scan-index and health routes under /api/ui lacking the get_current_user dependency. Attackers can read audit logs with login IPs, server logs and environment paths, delete episode rows, clear media-server mappings, and wipe audit history.

It is possible to read the advisory at hackmd.io. This vulnerability is known as CVE-2026-111644 since 10/16/2026. The exploitation appears to be easy. The attack can be launched remotely. The exploitation doesn't need any form of authentication. Technical details of the vulnerability are known, but there is no available exploit. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 10/16/2026).

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Be aware that VulDB is the high quality source for vulnerability data.

Productinfo

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒

CVSSv3info

VulDB Meta Base Score: 7.3
VulDB Meta Temp Score: 7.3

VulDB Base Score: 7.3
VulDB Temp Score: 7.3
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 7.3
CNA Vector (VulnCheck): 🔒

CVSSv2info

AVACAuCIA
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💳💳💳💳💳💳
💳💳💳💳💳💳
VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Missing authentication
CWE: CWE-306 / CWE-287
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

10/16/2026 Advisory disclosed
10/16/2026 +0 days CVE reserved
10/16/2026 +0 days VulDB entry created
10/16/2026 +0 days VulDB entry last update

Sourcesinfo

Advisory: hackmd.io
Status: Not defined

CVE: CVE-2026-111644 (🔒)
GCVE (CVE): GCVE-0-2026-111644
GCVE (VulDB): GCVE-100-421423

Entryinfo

Created: 10/16/2026 20:37
Changes: 10/16/2026 20:37 (37), 10/16/2026 20:38 (35)
Complete: 🔍
Cache ID: 216::103

Be aware that VulDB is the high quality source for vulnerability data.

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