This paper introduces Semantic Security as a FEIK Protocol extension for evaluating meaning-level risk in public language, AI systems, institutional documents, strategies, reports, and organizational self-descriptions. Traditional cybersecurity focuses on unauthorized access, data leakage, signal interception, and system compromise. Semantic Security expands the threat model to the level of meaning: how language frames risk, distributes responsibility, conceals uncertainty, launders authority, and alters the observer’s ability to detect what is happening. The central claim is that in AI-mediated societies, language itself becomes part of the attack surface. A system can remain technically secure while becoming semantically unsafe if its language causes users, citizens, workers, or decision-makers to misread power, uncertainty, harm, responsibility, or legitimacy. FEIK v4.2 therefore defines the Epistemic Shitfilter as a form of semantic cryptanalysis: a method for detecting when a claim has been encrypted into acceptable, neutral, safe, responsible, strategic, or humane language while its underlying structure remains unexamined. The paper defines semantic security, semantic breach, semantic encryption, plaintext/ciphertext/key analysis, semantic attack surfaces, failure modes, a semantic Phi-gate, contamination scoring adaptations, and a semantic cryptanalysis procedure. It positions Semantic Security not as a replacement for technical cybersecurity, but as an extension of security thinking into language, interpretation, institutional communication, and AI-mediated epistemology.