DataProxy: B2B Data Exfiltration & Poisoning Guard

Data leakage through third-party AI integrations is a critical enterprise risk. As businesses synchronize internal CRM or database telemetry with external RAG pipelines and automated contractors, they become vulnerable to indirect prompt injection and vector exfiltration attacks. This skill provides a non-bypassable outbound serialization guardrail that sits between your internal loops and third-party vendors to ensure proprietary assets are never extracted by compromised counterparties.

What it does

• Intercepts payloads by scanning outbound business data before it reaches third-party API endpoints or shared vectors.
• Strips injection tokens by programmatically removing context-hijacking markers and system-override directives hidden in text fields.
• Enforces payload anchoring using cryptographic techniques to prevent data from being utilized in unauthorized downstream KNN queries.
• Detects semantic drift by evaluating structural patterns against zero-trust templates to identify potential extraction vectors.
• Generates audit trails by producing machine-readable JSON validation matrices with block hashes and timestamps for compliance teams.

How it works

1. Identify destination context to establish semantic baseline constraints based on the target vendor tier and data residency needs.
2. Execute protection modules including instruction boundary isolation, hidden token scanning, and entropy evaluation.
3. Normalize risk scores to produce a CLEAR, WARNING, or BREACH status based on structural integrity metrics.
4. Log immutable artifacts that capture the scan verdict, SHA-256 block hash, and weighted risk score for your audit store.

Frameworks & tools

This skill is framework-agnostic and optimized for orchestrators like LangChain, LangGraph, and n8n. It integrates with Python and TypeScript API routers and supports auditing data destined for models like Claude, GPT-4o, and DeepSeek.

Why this beats prompting it yourself

Manual prompting lacks the structural anchoring and cryptographic hashing required for enterprise compliance audits. This skill enforces a systematic serialization layer that is non-bypassable, whereas simple system prompts can be subverted by the very injection attacks this tool is designed to block.

Use cases

• Secure vendor syncing when sending CRM telemetry to external AI optimization scripts.
• RAG risk mitigation for data pipelines connected to third-party or open-source vector indexes.
• Compliance automation to satisfy enterprise security baselines regarding third-party AI data-breach risks.
• Automated pipeline gating in CI/CD environments to block payloads that trigger high-risk security signals.

Known limitations

This skill only sanitizes outbound payloads and does not scan inbound traffic. It requires read access to serialization middleware and does not provide legal advice.