# Privent Privent — это уровень защиты во время выполнения для агентного ИИ, особенно для рабочих процессов n8n. Он маскирует конфиденциальные данные до их передачи внешним моделям, ведёт аудит решений по рискам и отслеживает использование ChatGPT, Claude и Gemini во всей организации. - Findings24: - Сайт: - Цены: Freemium - Категории: AI Ассистент Кода, AI Инструменты Разработчика, Наблюдаемость ИИ ## Что такое Privent? Privent is a runtime security layer for agentic AI, with a particular focus on n8n workflows. It embeds as a native node in the workflow so sensitive data can be detected, masked, and restored at trusted destinations before it reaches external models. The product is built around two related workflows: Agent Security for protecting data moving through n8n agent flows, and AI Monitoring for observing AI usage across an organization. The site says Privent can run in Privent Cloud, a dedicated environment, or fully on-prem/private cloud, including deployments where the full stack and ML inference stay inside the customer network. ## Что умеет Privent? ### Native n8n workflow node Privent runs as a native n8n node inside the workflow canvas, so security checks happen between steps rather than around the agent. The product is positioned as a drop-in addition with no proxy or rewrites. ### Session-aware risk scoring The ACARS engine scores data in the context of the whole agent session, using signals such as entity sensitivity, semantic risk, contextual amplification, destination risk, behavioral velocity, and policy overrides. ### Adaptive data protection The APE engine can mask, swap, or route sensitive data based on risk level. Supported responses include tokenization and re-injection, semantic substitution, noise injection, org identity decoupling, structural decomposition, and risk-conditioned routing. ### Workflow nodes for tokenization and audit Privent’s n8n package includes Session, Tokenize, Detokenize, Handoff, and Audit Event nodes, along with a credential type. The docs say tokenization handles kinds such as EMAIL, SSN, CREDIT\_CARD, IBAN, AWS\_KEY, JWT, and API\_KEY. ### Flexible deployment options The product supports multiple deployment modes, including Privent Cloud, a dedicated environment, and fully on-prem / private cloud deployment. The docs also describe a self-hosted n8n setup and cloud-based monitoring extension deployment. ### AI monitoring and dashboard visibility The monitoring docs say Privent can be rolled out to browser environments via MDM and can surface detection events in the dashboard in real time. The site also mentions AI Monitoring for organization-wide usage with ChatGPT, Claude, and Gemini. ## Варианты использования ### Protect n8n agent workflows Teams using n8n to build intake, triage, scheduling, or similar agent flows can mask sensitive fields before prompts reach an external LLM. The workflow keeps running while the model receives a tokenized or substituted version of the data. ### Monitor organization-wide AI usage Organizations that want to track how employees use ChatGPT, Claude, or Gemini can roll out the monitoring extension and feed detection events into the dashboard. The docs say deployment can be managed through MDM tools such as Google Workspace or Intune. ### Support audits and policy review Security and compliance teams can use the audit trail to review detections, decisions, timestamps, risk categories, and policy snapshots. The source says raw prompt text is not stored, while audit evidence can be exported for review. ### Handle regulated data in AI workflows Teams handling patient or other regulated data can use masking and trusted-destination controls to reduce exposure before AI calls and restore values only at approved sinks. The site specifically references PHI and HIPAA-oriented workflows. ### Inspect agent handoffs and trust changes Teams coordinating multiple agents can track handoffs and see when data moves between agents or sinks. The integration notes that handoff events and trust-score changes are surfaced in the Trust Map. ## Часто задаваемые вопросы ### How do you set up Privent in n8n? Privent is installed as a native n8n community node. The docs describe installing the package, adding a Privent API credential, and placing Session, Tokenize, and Detokenize nodes into the workflow so data can be transformed before it reaches external models. ### Does Privent block or interrupt running workflows? No. The n8n integration page says Privent is audit-only for the workflow: it does not proxy traffic, use a sidecar, or require orchestration changes, and the workflow keeps running while Privent watches and transforms sensitive data. ### Does Privent store raw prompt content? Privent’s documentation says raw prompt or agent payload text is processed only in-memory during scoring and is never written to disk or used for model training. The stored data is limited to audit and policy metadata such as scores, decisions, timestamps, and workflow identifiers. ### Which agent frameworks does Privent support? The product site says Privent supports n8n today, with LangGraph, CrewAI, MCP, and SDK integrations listed as coming soon in the docs. ### Can Privent be deployed on-prem? Yes. The site states that Privent can be deployed in the cloud, in a dedicated environment, or fully on-prem / private cloud, including a fully on-prem stack with ML inference inside your network. ## Краткие сведения - **Category**: Runtime security / AI security - **Primary platform**: n8n - **Other AI monitoring targets**: ChatGPT, Claude, Gemini - **Deployment options**: Cloud, dedicated environment, on-prem / private cloud - **Pricing model**: Free, Pro, and Teams plans listed; Enterprise is scoped with sales