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SOC 2 Type II Observation In Progress • PCI DSS v4.0 Ready • NAIC Cybersecurity Aligned

API Security for Insurance
Protect Policyholder Data

The AI Security Layer for insurance: SHA-256 hash-chain audit for state insurance recordkeeping, OS-level sandbox for AI underwriting agents, PII / SSN auto-redaction, and pre-mapped controls across 11 compliance frameworks. All 4 platforms from $399/mo.

Tamper-evident hash-chain audit
PCI DSS v4.0 Ready (300+ reqs)
NAIC Model Law #668 aligned
85,000+
threat patterns (24 categories)
11
compliance frameworks mapped
SHA-256
tamper-evident hash-chain audit
7-year
audit retention (84-month WORM)
4-dim
Zero Trust risk scoring (claims fraud)
PII / SSN
auto-redaction in security logs
Target: Sub-5ms
gateway proxy overhead (cached)
99.9%
Enterprise SLA · 1-hr P1 response

Insurance API Threats We Prevent

Proactive protection against threats targeting policyholder data and claims systems

Claims Fraud

Attackers submit fraudulent claims through APIs. Behavioral baselines + adaptive Z-score circuit breaker catch velocity anomalies and slow-and-low patterns over 24h sliding windows.

Prevention: Pattern analysis, velocity limiting, cross-claim correlation

Policy Data Exfiltration

Bulk scraping of policyholder PII, SSNs, and financial data via quote or lookup APIs. Sliding-window rate limits and response-size caps block enumeration attacks at the gateway.

Prevention: Rate limiting, anomaly detection, response filtering

Quote Manipulation

Attackers manipulate underwriting APIs to get fraudulent quotes. Schema validation, parameter pollution detection, and HMAC signature verification block tampered payloads before they reach the underwriting model.

Prevention: Schema validation, integrity checks, audit trails

Four Platforms for Insurance

API Security + MCP Security + AI Gateway + Verification Engine — unified under one correlation ID for insurance workloads

API Security

Claims Protection

Secure claims, policy, and quoting APIs. Pre-mapped to PCI DSS v4.0 across 300+ requirements, with cross-framework sync contributing evidence toward SOC 2 and GDPR.

  • Claims API fraud detection
  • Policy lookup rate limiting
  • PII/SSN data masking

MCP Security

AI Underwriting

Secure AI agents that assist with underwriting decisions. Every tools/call passes 7 sequential checks — permission, MFA, rate limit, rug-pull (SHA-256), threat detect, forwarding, response scan — before touching risk databases.

  • AI underwriting audit trails
  • Risk model access control
  • Decision explanation logging

AI Gateway

Risk Assessment

Route LLM calls for risk assessment and claims processing. PII / SSN scrubbing before LLM processing; adaptive Z-score circuit breaker for failover.

  • Multi-LLM routing with failover
  • PII scrubbing before LLM calls
  • Claims summarization security

Verification Engine

4 Validation Layers

Validate every AI-driven underwriting or claims decision before it approves a policy or denies a claim. Real-time enforcement with staged rollout; BLOCK-capable on selected critical paths.

  • PII / SSN masking + forbidden-phrase constraints
  • Source grounding (hallucination detection on AI rationales)
  • Structural validation (ACORD, JSON schema, regex)

Every Tool Call Passes 7 Sequential Checks

Zero code changes to your claims systems or AI underwriting stack. Target: Sub-5ms gateway proxy overhead on cached, single-region paths.

1
Permission check
RBAC: does this adjuster have access to this claim or policy?
2
MFA verification
TOTP required for high-value claims, underwriting overrides, and SIU operations
3
Rate limiting
Sliding-window check, Redis-backed with in-memory fallback
4
Rug-pull verification
SHA-256 of tool definition vs. registered hash — block on drift
5
Threat detection
Scan tool arguments for injection patterns + PII / SSN markers
6
Server forwarding
Execute via stdio subprocess, HTTP, or WebSocket transport
7
Response scanning
IndirectInjectionScanner blocks LLM-directed instructions in output
Audit log written
Hash-chain entry: arguments, response, decision, correlation ID
Fail-closed quota state on Redis error • Per-key asyncio lock prevents TOCTOU races • 10 dedicated Prometheus metrics

5 Capabilities You Won't Find Anywhere Else

Not in Anthropic's MCP spec. Not in API gateways. Not in WAFs. Platform-level additions built for insurance workloads.

01

OS-Level MCP Sandbox

Subprocess MCP tools execute inside a hardened Linux sandbox. RLIMIT_CPU/AS/NOFILE/NPROC, setsid() process-group isolation, capability dropping, per-tool egress filtering, and shell binaries removed.

modules/mcp/sandbox/executor.py — 934 LOC
02

Tool Definition Hash Registry

SHA-256 hash of every underwriting tool definition pinned at tools/list. On every tools/call, the cached definition is re-hashed and compared. Drift raises MCPRugPullDetectedError, blocks execution, publishes a CRITICAL event.

modules/mcp/tool_registry.py • Redis-backed
03

Adaptive Z-Score Circuit Breaker

Statistical, not threshold-based. Z-score > 3.0 against per-hour time-of-day baselines (catastrophe surge vs steady-state). 4 overlapping sliding windows (1m/5m/15m/1h). Progressive recovery (10→25→50→100%).

gateway/ — 2,208 LOC combined
04

Cross-Pillar Correlation

Every event linked across all four pillars via shared correlation ID. One query: "Show me everything that happened from this claim — across MCP + API + Gateway + Verification." Architecturally impossible when layers are separate products.

mcp_contexts • parent-child causal chain
05

Tamper-Evident Audit System

SHA-256 genesis block, each entry signing the previous. Three verification levels (full / single / last-N). Tamper-evident evidence for SOC 2 CC7.2, NAIC Model #668 audit, and SIU fraud investigations.

7 modules • 3,866 LOC combined
+

MCP Correlation Analyzer

Cross-session attack detection: 6-dimension risk score (max 110) across tool sensitivity, data volume, burst, denials, prior detections, and tool diversity. Catches organized claim-fraud rings and 24h slow-and-low patterns.

MCPCorrelationAnalyzer — alert at score > 50

One Correlation ID. All Four Pillars.

A claim submission traces forward to the AI fraud-model tool call it triggered, the policy API response, and the verification check that caught any drift.

Policyholder
Claim Session
Prompt
Underwriting AI
Tool Call
Policy API
Response
Verification
Recorded in mcp_contexts for parent-child replay • Causal chain reconstruction in one query • Hash-chain entries are tamper-evident for SIU investigations

Insurance Use Cases

Built for every type of insurance organization

P&C Insurance

Secure property and casualty claims APIs. Detect fraud patterns and protect policyholder data from breaches.

APIs secured: /claims, /policies, /quotes

Life & Health

Protect life insurance and health plan APIs. Secure beneficiary data and underwriting decisions with tamper-evident audit trails.

APIs secured: /beneficiaries, /underwriting, /coverage

Reinsurance

Secure treaty and facultative reinsurance APIs. Protect large data transfers between carriers and reinsurers.

APIs secured: /treaties, /bordereaux, /settlements

Audit Evidence, Built In From Day One

Every claims event appended to a hash-chain audit log. Cross-framework sync means a SOC 2 control automatically contributes evidence toward PCI DSS and GDPR where they overlap.

PCI DSS v4.0
300+ requirements
SOC 2 Type II
observation in progress
GDPR-Ready
Articles 5 / 17 / 32
NAIC Model #668
cybersecurity aligned
HIPAA-Ready
BAA available (health)
NIST CSF 2.0
106 subcategories mapped

"-Ready" / "aligned" reflect capability posture. PCI-DSS certification requires a Qualified Security Assessor (QSA) engagement on the customer's side; SOC 2 Type II observation in progress with external audit H2 2026.

Secure Your Insurance APIs Today

Join insurance carriers and InsurTech companies using G8KEPR to prevent claims fraud, secure AI underwriting, and protect sensitive policyholder data with documented evidence.

30-day free trial
11 frameworks mapped
No credit card required