Abstract
This disclosure introduces a Cognitive Integrity Firewall (CIF), a real-time monitoring and protection framework designed to detect and mitigate prompt-level manipulation and reasoning compromise in AI systems. Modern AI systems rely heavily on semantic interpretation of prompts and contextual inputs to generate decisions. Adversaries can exploit this dependency by manipulating prompt structure, context, or semantic framing without directly attacking system infrastructure. The Cognitive Integrity Firewall operates as a semantic security layer that monitors prompt lineage, reasoning stability, and output confidence alignment. It detects deviations in reasoning pathways, anomalous prompt injection patterns, and contextual manipulation attempts. By assigning dynamic trust scores to prompt inputs and reasoning states, the system enables early detection and mitigation of adversarial manipulation. This framework strengthens reliability, forensic traceability, and operational integrity in autonomous systems, enterprise AI deployments, and security-sensitive environments.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Bhatnagar, Pranav Mr, "Cognitive Integrity Firewall: Real-Time Detection of Prompt-Level Manipulation and Reasoning Compromise in AI Systems", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/9365