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EU AI Act Article 12 compliance.","maintainers":[{"name":"cloakllm","email":"cloakllm@gmail.com"}],"readme":"# CloakLLM\n\n**PII cloaking and tamper-evident audit logs for LLM API calls.**\n\nCloakLLM intercepts your LLM API calls, detects and cloaks PII before it reaches the provider, and logs every event to a tamper-evident audit chain designed for EU AI Act Article 12 compliance.\n\n> **Also available for Python:** `pip install cloakllm` — includes spaCy NER for name/org/location detection. See [CloakLLM Python](https://github.com/cloakllm/CloakLLM-PY).\n\n## Install\n\n```bash\nnpm install cloakllm\n```\n\n## Quick Start\n\n### With OpenAI SDK (one line)\n\n```javascript\nconst cloakllm = require('cloakllm');\nconst OpenAI = require('openai');\n\nconst client = new OpenAI();\ncloakllm.enable(client);  // That's it. All calls are now cloaked.\n\nconst response = await client.chat.completions.create({\n  model: 'gpt-4o-mini',\n  messages: [{\n    role: 'user',\n    content: 'Write a reminder for sarah.j@techcorp.io about the Q3 audit'\n  }]\n});\n// Provider never saw \"sarah.j@techcorp.io\"\n// Response has the real email restored automatically\n```\n\n### With Vercel AI SDK\n\n```javascript\nconst { createCloakLLMMiddleware } = require('cloakllm');\nconst { generateText, wrapLanguageModel } = require('ai');\nconst { openai } = require('@ai-sdk/openai');\n\nconst middleware = createCloakLLMMiddleware();\nconst model = wrapLanguageModel({ model: openai('gpt-4o'), middleware });\n\nconst { text } = await generateText({\n  model,\n  prompt: 'Write a reminder for sarah.j@techcorp.io about the Q3 audit'\n});\n// Provider never saw \"sarah.j@techcorp.io\"\n// Response has the real email restored automatically\n```\n\nWorks with any AI SDK provider (OpenAI, Anthropic, Google, Mistral, etc.) and supports both `generateText` and `streamText`.\n\n### Standalone\n\n```javascript\nconst { Shield } = require('cloakllm');\n\nconst shield = new Shield();\nconst [sanitized, tokenMap] = shield.sanitize(\n  'Send report to john@acme.com, SSN 123-45-6789'\n);\n// sanitized: \"Send report to [EMAIL_0], SSN [SSN_0]\"\n\n// ... send sanitized text to any LLM ...\n\nconst restored = shield.desanitize(llmResponse, tokenMap);\n// Original values restored\n```\n\n### Redaction Mode (irreversible)\n\n```javascript\nconst { Shield, ShieldConfig } = require('cloakllm');\n\nconst shield = new Shield(new ShieldConfig({ mode: 'redact' }));\nconst [redacted] = shield.sanitize('Email john@acme.com about Sarah Johnson');\n// redacted: \"Email [EMAIL_REDACTED] about [PERSON_REDACTED]\"\n// No token map stored — cannot be reversed\n```\n\n### Entity Details (compliance metadata)\n\n```javascript\nconst { Shield } = require('cloakllm');\n\nconst shield = new Shield();\nconst [sanitized, tokenMap] = shield.sanitize('Email john@acme.com, SSN 123-45-6789');\n\n// Per-entity metadata (no original text — PII-safe)\nconsole.log(tokenMap.entityDetails);\n// [\n//   { category: 'EMAIL', start: 6, end: 19, length: 13, confidence: 0.95, source: 'regex', token: '[EMAIL_0]' },\n//   { category: 'SSN', start: 25, end: 36, length: 11, confidence: 0.95, source: 'regex', token: '[SSN_0]' }\n// ]\n\n// Full report for dashboards\nconsole.log(tokenMap.toReport());\n```\n\n## What It Detects\n\n| Category | Examples | Method |\n|----------|----------|--------|\n| `EMAIL` | `john@acme.com` | Regex |\n| `SSN` | `123-45-6789` | Regex |\n| `CREDIT_CARD` | `4111111111111111` | Regex |\n| `PHONE` | `+1-555-0142` | Regex |\n| `IP_ADDRESS` | `192.168.1.1` | Regex |\n| `API_KEY` | `sk_live_abc123...` | Regex |\n| `AWS_KEY` | `AKIAIOSFODNN7EXAMPLE` | Regex |\n| `JWT` | `eyJhbG...` | Regex |\n| `IBAN` | `DE89370400440532013000` | Regex |\n| `PERSON` | John Smith | LLM (Local) |\n| `ORG` | Acme Corp, Google | LLM (Local) |\n| `GPE` | New York, Israel | LLM (Local) |\n| `ADDRESS` | 742 Evergreen Terrace | LLM (Local) |\n| `DATE_OF_BIRTH` | 1990-01-15 | LLM (Local) |\n| `MEDICAL` | diabetes mellitus | LLM (Local) |\n| `FINANCIAL` | account 4521-XXX | LLM (Local) |\n| `NATIONAL_ID` | TZ 12345678 | LLM (Local) |\n| `BIOMETRIC` | fingerprint hash | LLM (Local) |\n| `USERNAME` | @johndoe42 | LLM (Local) |\n| `PASSWORD` | P@ssw0rd123 | LLM (Local) |\n| `VEHICLE` | plate ABC-1234 | LLM (Local) |\n\n> **LLM categories** require opt-in (`llmDetection: true`) and a local [Ollama](https://ollama.com) instance. Data never leaves your machine.\n\n## How It Works\n\n```\nYour app:      \"Email sarah.j@techcorp.io about Project Falcon\"\nProvider sees: \"Email [EMAIL_0] about Project Falcon\"\nYou receive:   Original email restored in the response\n```\n\n1. **Detect** — Regex patterns find structured PII (emails, SSNs, credit cards, etc.)\n2. **Cloak** — Replace with deterministic tokens: `[EMAIL_0]`, `[SSN_0]`\n3. **Log** — Write to hash-chained audit trail (each entry includes previous entry's SHA-256 hash)\n4. **Uncloak** — Restore original values in the LLM response\n\n## Tamper-Evident Audit Chain\n\nEvery event is logged to JSONL files with hash chaining:\n\n```json\n{\n  \"seq\": 42,\n  \"event_type\": \"sanitize\",\n  \"entity_count\": 3,\n  \"categories\": {\"EMAIL\": 1, \"SSN\": 1, \"PHONE\": 1},\n  \"prompt_hash\": \"sha256:9f86d0...\",\n  \"entity_details\": [\n    {\"category\": \"EMAIL\", \"start\": 0, \"end\": 13, \"length\": 13, \"confidence\": 0.95, \"source\": \"regex\", \"token\": \"[EMAIL_0]\"},\n    {\"category\": \"SSN\", \"start\": 15, \"end\": 26, \"length\": 11, \"confidence\": 0.95, \"source\": \"regex\", \"token\": \"[SSN_0]\"},\n    {\"category\": \"PHONE\", \"start\": 28, \"end\": 40, \"length\": 12, \"confidence\": 0.95, \"source\": \"regex\", \"token\": \"[PHONE_0]\"}\n  ],\n  \"prev_hash\": \"sha256:7c4d2e...\",\n  \"entry_hash\": \"sha256:b5e8f3...\"\n}\n```\n\nModify any entry and every subsequent hash breaks. Verify with:\n\n```bash\nnpx cloakllm verify ./cloakllm_audit/\n```\n\n## CLI\n\n```bash\n# Scan text for PII\nnpx cloakllm scan \"Email john@test.com, SSN 123-45-6789\"\n\n# Verify audit chain integrity\nnpx cloakllm verify ./cloakllm_audit/\n\n# Show audit statistics\nnpx cloakllm stats ./cloakllm_audit/\n```\n\n## Configuration\n\n```javascript\nconst { Shield, ShieldConfig } = require('cloakllm');\n\nconst shield = new Shield(new ShieldConfig({\n  detectEmails: true,        // default: true\n  detectPhones: true,\n  detectSsns: true,\n  detectCreditCards: true,\n  detectApiKeys: true,\n  detectIpAddresses: true,\n  detectIban: true,\n  logDir: './my-audit-logs', // default: ./cloakllm_audit\n  auditEnabled: true,        // default: true\n  skipModels: ['ollama/'],   // skip local models\n  customPatterns: [\n    { name: 'EMPLOYEE_ID', pattern: 'EMP-\\\\d{6}' }\n  ],\n\n  // LLM Detection (opt-in, requires Ollama)\n  llmDetection: true,                         // Enable LLM-based detection\n  llmModel: 'llama3.2',                       // Ollama model\n  llmOllamaUrl: 'http://localhost:11434',      // Ollama endpoint\n  llmTimeout: 10000,                           // Timeout in ms\n  llmConfidence: 0.85,                         // Confidence score\n}));\n```\n\n## EU AI Act Compliance\n\nArticle 12 of the EU AI Act requires tamper-evident audit logs for AI systems. Enforcement begins **August 2, 2026**. CloakLLM provides:\n\n- **Hash-chained logs** — cryptographically linked, any modification breaks the chain\n- **O(n) verification** — `cloakllm verify` audits the entire chain\n- **No PII in logs** — only hashes and token counts are logged (original values never stored)\n- **Event-level detail** — every sanitize/desanitize event is recorded\n\n## Roadmap\n\n- [x] NER-based detection (names, orgs, locations) via local LLM\n- [x] Local LLM detection (opt-in, via Ollama)\n- [x] Streaming response support\n- [x] Vercel AI SDK middleware\n- [x] Redaction / scrubbing mode\n- [x] Field-level PII metadata (entityDetails)\n- [ ] LangChain.js integration\n- [ ] OpenTelemetry span emission\n- [ ] RFC 3161 trusted timestamping\n\n## License\n\nMIT — See [LICENSE](LICENSE).\n\n## See Also\n\n- **[CloakLLM Python](https://github.com/cloakllm/CloakLLM-PY)** — Python version with spaCy NER + LiteLLM integration\n","readmeFilename":"README.md"}