WordPress Mang Board Plugin Authentication Cookie Forgery

The Mang Board WP plugin for WordPress is vulnerable to Missing Authorization via Authentication Cookie Forgery in all versions up to, and including, 2.3.7. This is due to flawed HMAC generation in the mbw_get_hash_key() function that uses the current user's identity instead of the cookie username parameter when a WordPress user is logged in, combined with insufficient validation in mbw_validate_auth_cookie(). This makes it possible for authenticated attackers, with subscriber-level access and above, to forge administrator authentication cookies and change administrator passwords to achieve complete site takeover.

Casky was already ahead

This CVE exploits attack patterns that Casky's 224matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

The Mang Board WP plugin for WordPress contains a critical authentication bypass vulnerability stemming from flawed HMAC generation in the mbw_get_hash_key() function. When a WordPress user is logged in, the function incorrectly uses the current user's identity instead of the cookie username parameter during hash generation, combined with insufficient validation in mbw_validate_auth_cookie(). This allows authenticated attackers with subscriber-level privileges to forge authentication cookies and escalate their permissions within the application. With a CVSS score of 8.8, this vulnerability poses a significant risk to WordPress installations using Mang Board versions up to 2.3.7, potentially enabling privilege escalation and unauthorized access to sensitive functionality that should be restricted to administrators.

Casky's 224 mapped security skills, powered by Claude AI's extended reasoning capabilities, would identify this vulnerability through detection patterns aligned with MITRE ATT&CK technique TA0004 (Privilege Escalation). Practitioners using Casky would observe findings revealing flawed cryptographic validation in authentication mechanisms—specifically the HMAC generation logic that fails to properly segregate user context during cookie validation. The platform's skills would flag suspicious patterns such as inconsistent parameter usage in hash functions, insufficient input validation in authentication validation routines, and the ability to manipulate cookie-based authentication chains. Security teams would see detailed analysis of how an attacker chain begins with subscriber-level access, exploits the cookie forgery weakness, and escalates to higher privilege levels, enabling them to implement compensating controls, patch prioritization, and enhanced authentication monitoring before active exploitation occurs.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

224 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-75977.

abusing-dpapi-for-credential-access

red teaming · high

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abusing-shadow-credentials-for-privesc

red teaming · high

Run

Access with Stolen Session Cookie

identity access management · low

Run

MITRE ATT&CK Techniques

TA0004

Investigate the attack patterns behind CVE-2026-75977

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