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Provides layered, zero-trust context processing (CSL, ISL, AAL) and transversal integrity (CPE)","maintainers":[{"name":"masliahdev","email":"d3vTek-mv@outlook.com"}],"readme":"# @ai-pip/core\n\n[![npm version](https://img.shields.io/npm/v/@ai-pip/core)](https://www.npmjs.com/package/@ai-pip/core)\n[![npm downloads](https://img.shields.io/npm/dm/@ai-pip/core)](https://www.npmjs.com/package/@ai-pip/core)\n[![License](https://img.shields.io/badge/license-Apache--2.0-blue)](LICENSE)\n\n**Core implementation of the AI-PIP protocol.** Layered, zero-trust context processing and transversal integrity for AI systems.\n\n---\n\n## Why AI-PIP?\n\nAI-powered browsers and chat interfaces (e.g. **GPT Atlas**, embedded AI in web apps) create new attack surfaces: **prompt injection**, **hidden text**, **jailbreaking**, and **role hijacking**. The AI-PIP (AI Prompt Integrity Protocol) was designed to improve the security of these environments by providing **rules and tools** to detect, score, and respond to such threats before content reaches the model. This package is the **semantic core** of that protocol—pure functions, immutable value objects, and clear contracts between layers—so that SDKs and applications can build secure, auditable pipelines.\n\n---\n\n## Description\n\n**AI-PIP** is a multi-layer security protocol that protects AI systems from prompt injection and malicious context manipulation. This package contains the **core** implementation: it does not execute network calls or side effects; it provides the logic for segmentation, sanitization, risk scoring, policy decisions, and remediation plans. The **official AI-PIP SDK** (in development) will use this core to deliver production-ready features, including browser extensions and integrations for AI-powered applications.\n\n---\n\n## Architecture (summary)\n\n| Layer | Role |\n|-------|------|\n| **CSL** (Context Segmentation Layer) | Segments and classifies content by origin (UI, DOM, API, SYSTEM). |\n| **ISL** (Instruction Sanitization Layer) | Detects threats (~287 patterns), scores risk, sanitizes content, and emits a **signal** (risk score, detections) for other layers. From **v0.5.0**: produces **ThreatTag** metadata and exposes the **canonical tag serializer** for semantic isolation (encapsulation with `<aipip:threat-type>...</aipip>` is applied by the SDK at fragment level). |\n| **AAL** (Agent Action Lock) | Consumes the ISL signal and applies policy: **ALLOW**, **WARN**, or **BLOCK**. Produces a **remediation plan** (what to clean—target segments, goals, constraints); the SDK or an AI agent performs the actual cleanup. |\n| **CPE** (Cryptographic Prompt Envelope) | **Transversal**: ensures the **integrity of each layer**. Wraps pipeline output with a signed envelope (nonce, metadata, HMAC-SHA256) so that results can be verified. Implemented in `shared/envelope`; exported as `@ai-pip/core/cpe`. |\n\nThe processing pipeline is **CSL → ISL** (optionally **AAL** consumes the signal). **CPE** is not a step in that sequence—it is a transversal capability that can wrap the result at any point to guarantee integrity. Layers communicate via **signals**, not internal results, so that each layer stays independent and testable.\n\n**Trust and security (contract):**\n- **`source`** (UI, DOM, API, SYSTEM) determines trust level and sanitization. It **must be set only by trusted code** (backend/SDK), **never** derived from user input. Otherwise an attacker could send `source: 'SYSTEM'` and reduce sanitization.\n- **CPE secret key**: The key passed to `envelope(..., secretKey)` **must not be logged or serialized**. Key rotation and storage are the **SDK’s responsibility** (e.g. use a key id in metadata and multiple keys in the verifier).\n\n**Semantic isolation and canonical tags (v0.5.0):** The core does **not** modify segment text. It produces **ThreatTag** metadata (segmentId, offsets, type, confidence) and defines the **canonical AI-PIP tag format** via the serializer (`openTag`, `closeTag`, `wrapWithTag`). Encapsulation with tags like `<aipip:prompt-injection>...</aipip>` is applied by the **SDK** at fragment level. Benefits: no semantic corruption, auditable and reversible, deterministic; the SDK is responsible for applying offsets, insertions, and ordering (e.g. by descending offset when resolving multiple tags).\n\n---\n\n## Installation\n\n```bash\npnpm add @ai-pip/core\n# or\nnpm install @ai-pip/core\n# or\nyarn add @ai-pip/core\n```\n\n---\n\n## Usage example\n\nSegment user input, sanitize it, optionally get a risk decision and remediation plan, and wrap the result in a cryptographic envelope:\n\n```typescript\nimport { segment, sanitize, emitSignal, resolveAgentAction, buildRemediationPlan, envelope } from '@ai-pip/core'\nimport type { AgentPolicy } from '@ai-pip/core'\n\nconst cslResult = segment({ content: userInput, source: 'UI', metadata: {} })\nconst islResult = sanitize(cslResult)\nconst signal = emitSignal(islResult)\nconst policy: AgentPolicy = {\n  thresholds: { warn: 0.3, block: 0.7 },\n  remediation: { enabled: true }\n}\nconst action = resolveAgentAction(signal, policy)  // 'ALLOW' | 'WARN' | 'BLOCK'\nconst remediationPlan = buildRemediationPlan(islResult, policy)\nconst cpeResult = envelope(islResult, secretKey)   // integrity for the pipeline result\n\nif (action === 'BLOCK') {\n  // SDK: block the request, log, and optionally run cleanup using remediationPlan\n}\nif (remediationPlan.needsRemediation) {\n  // SDK or AI agent: clean targetSegments using goals and constraints\n}\n```\n\n---\n\n## Documentation\n\n- **Full README** (examples, use cases, audit, all layers): [docs/readme.md](./docs/readme.md)\n- **Protocol docs** (whitepaper, architecture, layers): [AI-PIP documentation repository](https://github.com/AI-PIP/ai-pip-docs)\n- **Package changelog**: [CHANGELOG.md](./CHANGELOG.md) — Latest: **0.5.0** (unreleased)  \n- **Features by version**: [FEATURE.md](./FEATURE.md)\n- **Roadmap** (path to 1.0.0): [roadmap.md](./roadmap.md)\n\n---\n\n## Requirements\n\n- **Node.js** ≥ 18\n- **TypeScript**: For correct imports and types, your `tsconfig.json` must use:\n  - `\"module\": \"NodeNext\"`\n  - `\"moduleResolution\": \"nodenext\"`\n  - `\"target\": \"ES2022\"` (or compatible)\n\nWithout this, you may see resolution errors for subpaths (`@ai-pip/core/csl`, etc.). See [docs/readme.md](./docs/readme.md) for a full configuration example.\n\n---\n\n## License\n\nApache-2.0. See [LICENSE](LICENSE).\n\n---\n\n**Repository**: [github.com/AI-PIP/ai-pip-core](https://github.com/AI-PIP/ai-pip-core) · **npm**: [@ai-pip/core](https://www.npmjs.com/package/@ai-pip/core)\n","readmeFilename":"README.md"}