This vulnerability in SourceCodester CET Automated Grading System with AI Predictive Analytics 1.0 involves session fixation, where an attacker can manipulate session identifiers to fixate a session for a victim user. The attack can be performed remotely but requires a high complexity level, making exploitation difficult. The vulnerability is publicly known but no known exploits are reported in the wild. No vendor advisory or patch information is available, and the remediation level is not specified.

Successful exploitation could allow an attacker to hijack a user's session by forcing a known session ID, potentially leading to unauthorized access within the application context. However, the attack complexity is high and no privilege or user interaction is required. The impact is limited to session fixation with low confidentiality, integrity, and availability impact vectors.

Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until an official fix is released, users should consider implementing additional session management controls such as regenerating session IDs after login and validating session tokens to mitigate session fixation risks.