Aegis 365

Executive Overview

Aegis 365 is an intelligent, eight-layer AI Trust Mesh that intercepts all prompts flowing from enterprise users to external Large Language Model (LLM) services. It detects, filters, anonymises, and governs sensitive data — including PII, PHI, source code, and trade secrets — before it ever leaves the organisation. It then re-hydrates the AI's response locally, so the end user receives a seamless experience while the enterprise maintains zero-knowledge data sovereignty.

Mission Statement: Aegis 365 ensures that even if an AI agent goes rogue, an administrator turns traitor, or the cloud is compromised by a nation-state actor, the data remains a secret. Aegis 365 protects the Intelligence Layer. The customer protects the Physical Layer.

Product Positioning

Target Market

The Eight-Layer Trust Mesh

Aegis 365 is architected as an Active Privacy Orchestration platform. Unlike passive firewalls that inspect individual prompts, Aegis 365 maintains stateful context across agent sessions, semantically analyses intent, and enforces data sovereignty in real time.

Prompt → L0 → L1 → L2 → L3 → L4 → LLM → L4 → L5 → L6 → L7 → Response
         │     │     │     │     │            │     │     │     │
    Behaviour  Intent  PII/  Anon-  Re-        Geo-  Proof Cache
    Guardrail  Shield  PHI   ymiser hydration  route Notary Opt.

Layer 0 — Behavioural Guardrail (The Shield)

Layer 0 is the foundational enforcement point where an AI agent's intent becomes a real-world action. Unlike traditional firewalls that inspect text, L0 governs Agentic Intent and Operational Authority across all agent types — internal, third-party, and hybrid.

Key capabilities:

• Agent-agnostic interception — intercepts actions from any AI source: internal builds, OpenAI Assistants, Claude, or hybrid agents. Eliminates Shadow AI blind spots.
• Least-privilege enforcement — AI agents operate with minimum access required for a specific task. Minimises blast radius of a compromised agent.
• Action taxonomy — admins define and extend what constitutes a high-risk action. The taxonomy is dynamic and enterprise-extensible.

Stateful context engine:

• In-memory Redis-backed session state tracking parent-child agent relationships
• Sliding-window algorithm detects drip-feed sensitive data requests (Inference Attack / Mosaic Effect)
• Security-aware TTL: Low = 1 hour, Medium = 24 hours, High = 30 days, Critical = Indefinite freeze
• Background state-siphon process analyses Tier 1 cache for temporal aggregation patterns without introducing live response latency

Human-in-the-Loop (HITL) approval routing:

Fail-closed protocol: If L0 analysis exceeds 200ms, the action is blocked by default — preventing latency bypass attacks. If Tier 1 hot cache is unavailable, all active agent sessions are paused until state integrity is restored.

Layer 1 — Intent Shield (The Inspector)

Layer 1 governs what the user or agent is trying to make the AI think. It applies semantic analysis to every prompt regardless of source, using a local Small Language Model (SLM) to detect adversarial intent before any data is inspected.

Confidence-scored behavioural contract:

Role-based transparency model:

Source-agnostic semantic normalisation: L1 treats every prompt with equal scrutiny regardless of origin. The Semantic Normalisation Engine strips all formatting, encoding, and transport context before SLM analysis.

Aegis Collective Intelligence (ACI) — a continuously updated SLM model with:

• Global Threat Model — centrally maintained from anonymised attack signals across all deployments
• Local Enterprise Brain — per-deployment fine-tuning; enterprises flag false positives to build proprietary contextual model
• Shadow Update Protocol — only gradient signals or anonymised mathematical attack patterns transmitted; zero plaintext leaves enterprise
• Dark Mode — defence/government deployments receive global updates but contribute no signals back

Layer 2 — Inspector

Layer 2 answers the question: what is in this prompt? It identifies and classifies every piece of sensitive data using a three-engine consensus model, providing Static Context tiles that L0 uses for Mosaic Effect (temporal) detection.

Sensitivity taxonomy:

Industry extension modules:

Aegis Private Semantic Map: Enterprises upload internal project names, codenames, and proprietary terminology. The L2 SLM builds a client-specific sensitivity index — never shared with the global model. Terms are matched semantically, not literally. Each tenant's map is cryptographically isolated.

Consensus engine — dynamic escalation protocol:

Layer 3 — Anonymizer (The Mask)

Layer 3 replaces every sensitive element with a synthetic equivalent — without breaking the prompt's meaning or structure for the downstream LLM.

Anonymisation depth levels:

Secure State Map (shared L3/L4 architecture):

• Single interface layer controls read/write — L3 writes outbound mappings, L4 reads inbound mappings
• Once assigned, mapping is immutable for the duration of session TTL
• Same real-world entity receives same token across multiple prompts within TTL window
• Cryptographically isolated per tenant — no map bleed across enterprise boundaries

Triple-guard re-identification protection:

1. Pre-emptive collision risk — L3 evaluates every token combination for unique re-identification potential. High Re-ID Risk triggers automatic token generalisation.
2. Entity cluster SDG — when prompt contains multiple sensitive entities in relational context, Level 3 Synthetic Data Generation is mandatory.
3. Post-inference redaction — L4 scans all LLM responses for inference markers ("This seems to be...", "I assume...") and intercepts de-masking attempts.

Layer 4 — Hydration Brain

Layer 4 makes Aegis 365 invisible to the end user. It intercepts the LLM's response, re-hydrates synthetic tokens back to real values locally, and delivers a seamless answer — all before the user sees a single character. Re-hydrated values exist only in the ephemeral UI render layer and are never written to persistent storage.

Re-hydration decision hierarchy:

1. Hard Mask — never re-hydrate admin-defined categories (SSNs, PHI, Critical credentials)
2. Role Clearance Check — clearance-first gate; L4 queries L0 Auth to verify user's clearance
3. User-Origin Priority — tokens the user themselves introduced are always re-hydrated first
4. Policy Overlay — admin-configured department-level or role-level masks
5. Full Re-hydration — never the global default; explicit admin setting only

Mask-on-Hover UI:

• High-sensitivity tokens rendered as masked token [USER_88] in all UI contexts
• Real value displayed only on deliberate hover action — requires clearance validation at moment of hover
• Every successful hover-reveal logged in L6 as a discrete data access event
• Screen-share protection: mask-on-hover is default for all roles

Self-healing state-pulse check:

• Before every prompt leaves L3, L4 verifies all active token TTLs exceed expected LLM response latency plus safety buffer
• Tokens approaching TTL expiry receive automatic lease extension — logged in L6
• If state-pulse check fails, session is paused and user notified before prompt is dispatched to LLM

Layer 5 — Sovereignty Border (The Border)

Layer 5 ensures every prompt reaches only the LLM endpoints that are legally permitted to receive it — based on data classification, user location, enterprise jurisdiction, and applicable regulatory framework.

Sovereignty precedence framework:

Critical continuity modes:

Aegis Compliance Registry: Continuously maintained covering GDPR, HIPAA, CCPA, Swiss banking law, ITAR, UK GDPR, PDPA, and extensible for new jurisdictions. Registry updates are pushed automatically to all deployments. Enterprises may delay but not permanently block compliance updates.

Layer 6 — Proof Notary

Layer 6 transforms Aegis 365 from a security tool into a legally defensible compliance instrument. By default, L6 stores only cryptographic hashes and Zero-Knowledge Proofs — never plaintext.

Three-artifact tiered disclosure model:

Break Glass Protocol (eight-step sequence):

1. Legal officer submits formal access request with case reference
2. Dual key authorisation — Legal key holder and CISO key holder authenticate within 15-minute window
3. Scope definition — access scoped to specific session IDs or time range
4. Meta-Log generation — immutably records who requested, who authorised, what scope, what time
5. Meta-Log distribution — real-time notification to Board-designated compliance officer and external partner
6. Timed access window — configurable window (default 4 hours), then automatically re-sealed
7. Access audit — every action during window logged
8. Post-access report — automated report distributed to all key holders

Litigation Hold: Legal teams may flag specific sessions for indefinite hold, suspending TTL expiry on associated Vault entries until released by dual-key authorisation.

Layer 7 — Semantic Optimiser

Layer 7 makes Aegis 365 economically compelling. It recognises semantically equivalent prompts and serves cached, pre-filtered answers — reducing LLM costs by 30-40% and cutting response time to milliseconds.

Cache architecture principle: Intelligence is cached. Visibility is computed in real time. The cache never stores clearance-specific or re-hydrated responses — only anonymised LLM output in token form.

Tiered cache ownership:

Performance contract:

Inference attack detection: When vector distance is close but semantic intent has shifted toward data aggregation, cache hit is intentionally suppressed. Mosaic tile detection cross-references new prompt against L0 Stateful Context Store.

System-Wide Architecture

Performance: The 450ms Sprint

Research shows 500ms is the perceptual threshold where users feel delay is system-induced. Aegis 365 targets 450ms total overhead — protection feels like a natural pause.

Latency Profiles

Scalability

Graceful Security Degradation

Security & Threat Model

Responsibility Boundary

Distributed Trust Architecture — Rogue Admin Controls

Deployment Models

Hybrid Sidecar layer split (Data Gravity Rule): Sensitive data must never leave the enterprise perimeter in plaintext.

Integrations

LLM Connector Architecture

Drop-In Deployment: Aegis 365 exposes an OpenAI-compatible endpoint. The enterprise changes their BASE_URL environment variable and their entire AI stack is instantly secured — zero code modifications required.

Enterprise Identity Integration

SIEM Integration and SOAR Orchestration

Aegis 365 receives inbound commands from SOAR platforms (Microsoft Sentinel, Splunk SOAR, Palo Alto XSOAR). Example: Sentinel detects compromised user externally → sends freeze command → all active AI agent sessions for that user are hard-frozen within 500ms.

Compliance & Certification Roadmap

Admin Role Hierarchy

Use Cases

Enterprise AI Governance

A global financial institution deploys Aegis 365 across 20,000 employees using LLMs for customer support, compliance analysis, and code generation. Every prompt is inspected by all eight layers. Customer PII is anonymised before reaching OpenAI via Level 3 synthetic generation. Source code from the engineering team is redacted via Level 1. Non-compliant geo-routing requests are blocked at Layer 5. The CISO has full audit trail via Layer 6 compliance certificates.

Rogue Agent Containment

An AI agent compromised through indirect prompt injection attempts to exfiltrate internal pricing data by drip-feeding queries across multiple sessions. Layer 0's temporal mosaic detection identifies the pattern, Layer 1's Intent Shield flags the adversarial behaviour, and the session is frozen. The SOC receives a real-time alert via SIEM integration.

Multi-National Compliance

A pharmaceutical company operates across EU, US, and APAC regions. Aegis 365's Sovereignty Border (Layer 5) ensures patient data from EU clinical trials is routed only to GDPR-compliant endpoints within the EU. US operational data routes to US regions. Any cross-border data movement is logged immutably in Layer 6.

FAQ

Q: Does Aegis 365 require modifying application code?
A: No. Aegis 365 exposes an OpenAI-compatible endpoint. Change your BASE_URL and the entire AI stack is instantly secured — zero code modifications required.

Q: What latency does Aegis 365 add?
A: The total target overhead is 450ms — designed to feel like a natural pause in the AI's thought process. Cache hits return in under 100ms (20x faster than a fresh LLM call).

Q: Can an admin bypass Aegis 365?
A: No single admin can. The Distributed Trust Architecture uses MPC key splitting (Shamir's Secret Sharing) requiring two of three key holders (CISO, Legal Counsel, third-party HSM). Policy changes require dual hardware token approval.

Q: How is the ACI SLM updated without leaking data?
A: The Shadow Update Protocol transmits only gradient signals or anonymised mathematical attack patterns — zero plaintext leaves the enterprise. Dark Mode deployments receive updates but contribute no signals.

Q: What happens if Aegis 365 fails?
A: Fail-closed by design. If L0 analysis exceeds 200ms, the action is blocked. If the hot cache is unavailable, sessions are paused. If sovereignty endpoints are unreachable, traffic is severed at the gateway. Better zero AI productivity than AI agents running blind without the Trust Mesh.

Q: What is the difference between Aegis 365 and a traditional AI firewall?
A: Traditional firewalls use pattern matching (RegEx) and simple redaction. Aegis 365 uses semantic understanding, format-preserving encryption, stateful agentic governance, temporal mosaic detection, geo-sovereignty routing, zero-knowledge proofs, and a collective intelligence SLM continuously updated across all deployments.