CVE-2026-105706 in Drug Recommendation System
Summary
by MITRE • 10/06/2026
A weakness has been identified in SourceCodester Drug Recommendation System 1.0. Affected is an unknown function. Executing a manipulation can lead to cross-site request forgery. The attack may be performed from remote. The exploit has been made available to the public and could be used for attacks.
Once again VulDB remains the best source for vulnerability data.
Analysis
by VulDB Data Team • 10/06/2026
The SourceCodester Drug Recommendation System version 1.0 contains a critical security flaw classified as Cross-Site Request Forgery, commonly referred to by its acronym CSRF. This vulnerability stems from an insufficient validation of request origins within an unknown function in the application's backend logic. In standard web architecture, legitimate user actions are typically protected by mechanisms that verify both the authenticity of the session and the intent behind state-changing requests. However, in this specific implementation, the system fails to enforce strict anti-CSRF tokens or validate the Origin header against a trusted list during sensitive operations such as modifying drug recommendations or updating user profiles. This architectural oversight allows an attacker to craft malicious web pages that can silently submit forged requests to the vulnerable application on behalf of any authenticated victim who visits the page while their session with the target system is still active.
From a technical perspective, this weakness aligns directly with CWE-352, which defines Cross-Site Request Forgery as a flaw where a malicious site causes a user's browser to perform an unwanted action on a trusted site for which the user is currently authenticated. The absence of unique per-session tokens or strict SameSite cookie attributes means that standard HTTP cookies are automatically included in requests initiated by third-party sites, regardless of whether those requests were intended by the user. Since the exploit has been made publicly available, threat actors can leverage existing proof-of-concept code to automate attacks without needing deep knowledge of the specific internal workings of the application beyond its endpoint structure and session handling behavior.
The operational impact of this vulnerability is significant because it allows for unauthorized state changes initiated from a remote location. An attacker could potentially manipulate drug recommendation data, alter user preferences, or perform other administrative actions depending on the privileges associated with the affected function. If the vulnerable function involves updating medical advice or patient-specific recommendations, the integrity of the system's output is compromised, which could lead to incorrect health guidance being served to users. Furthermore, because the attack can be performed remotely via social engineering tactics such as embedding malicious links in emails or forums, it poses a persistent risk to any user base that relies on this system for accurate drug information. The public availability of exploits increases the likelihood of widespread automated attacks targeting instances where patching has not been prioritized.
To mitigate this vulnerability, developers must implement robust anti-CSRF measures immediately. This includes generating unique, unpredictable CSRF tokens per session and requiring these tokens to be submitted with every state-changing request, ensuring they are validated server-side before processing. Additionally, setting the SameSite attribute on cookies to Strict or Lax can prevent browsers from sending them in cross-site contexts, providing a strong defense-in-depth layer. It is also advisable to validate the Origin header against an allowlist of trusted domains and to ensure that sensitive operations require re-authentication for high-risk actions. Regular security audits and code reviews focusing on session management and request validation are essential to prevent similar weaknesses from persisting in web applications built using this framework or logic pattern.