QuantumShield Core
Governed AI Security Operations
A 4,251-line Python security operations platform where AI detects threats and humans approve actions. Every decision traces to a named human with documented reasoning — audit-ready by design, not by accident.
The Problem
Most AI security tools promise autonomy. When a regulator asks "who approved this?" the answer is often "the model decided" — the wrong answer for regulated industries.
- Alert fatigue overwhelms security teams
- Audit trails are optional, not enforced
- AI decisions lack human accountability
- Configuration can bypass oversight gates
The Solution
QuantumShield Core implements governed AI architecture: AI recommends, humans decide, and every decision is recorded in an append-only audit trail.
- Hard-gate human approval enforced in code, not policy
- Every finding requires human sign-off before delivery
- Named operator, timestamp, and reasoning on every approval
- Full decision chain replay from event logs
Key Capabilities
Human-in-the-Loop
Approval gates that cannot be bypassed by configuration. No gate, no action. Every finding requires human sign-off before delivery.
Replay-Capable Audit Trail
Append-only event log with immutable records. Any decision chain can be replayed from the event log with operator identity and reasoning.
37 Governance Controls
Documented safety and boundary controls across security, permissions, human review, governance, data handling, and operational boundaries.
Zero-Trust Model
All inputs treated as untrusted. No automatic execution of external code. 3-tier permission system with 6 categorically blocked actions.
Learning Engine
Governance feedback loop where approvals feed into confidence scoring. Learning rules are transparent and auditable, not a black box.
Synthetic Lab Environment
5 training scenarios with governance arc objectives and readiness checklists. Risk-based scoring with severity classification from INFO to HIGH.
Architecture & Controls
Permission Tiers
| Tier | Actions |
|---|---|
| Auto-Allowed | Fast scans, format reports, detect changes |
| Approval Required | Deep scans, add targets, send alerts, create issues |
| Blocked | Delete files, modify firewall, run exploits, shell commands, access secrets, push to main |
Trust Boundaries
11 defined trust boundaries ensure safe operation:
- Customer network isolation
- Observer mode (read-only, no credentials)
- Permission tier enforcement
- Approval gate (hard gate, no bypass)
- Constitutional role separation
- Automation boundaries
- Suppression and policy override controls
Safe Engagement Model
Read-only observation. No authentication attempts. No software installation. No data transmission to third parties. Customer controls redaction. Data deleted after engagement.
Screenshots
Security operations timeline with events, lineage links, and validation status.
Review queue showing findings with risk scores, approval states, and AI agents.
Human approval record showing operator identity, reasoning, and timestamp.
Security training scenario with governance arc objectives and readiness checklist.
Engagement Model
Pricing tiers for security posture assessments with human-in-the-loop governance:
Starter
$5,000
Up to 10 targets
2 weeks
- External posture assessment
- Human review of every finding
- Governance audit trail
Standard
$15,000
Up to 50 targets
4 weeks
- Everything in Starter
- Replay export bundle
- Debrief session
Comprehensive
$25,000
Up to 200 targets
6 weeks
- Everything in Standard
- Full PQC posture summary
- Prioritized remediation roadmap
Ready for Governed AI Security?
Let's discuss how human-in-the-loop security assessments can provide defensible audit trails for your organization.