Vibe coding is fast.
Let's make it secure.
When you build software by prompting AI agents, deployment speed is a superpower. But AI-generated code is inherently untrusted, creating a critical need for KYE (Know Your Exhaust). Because models prioritize functionality (if it runs, they ship it), they frequently leak hardcoded keys, raw stack traces, and customer PII in plaintext telemetry. TN is the local guardrail that enforces KYE and secures prompt-driven applications at the source.
The "Path of Least Resistance" Telemetry Leak
In early 2025, the software community adopted the term vibe coding to describe software creation driven entirely by prompting LLM agents (such as Claude Code, Cursor, or Gemini CLI). While this democratizes development, AI models prioritize functionality over safety: if it runs, they ship it. Left to their own devices, coding assistants write logging and debugging calls that dump raw user objects, stack traces, and session tokens directly into plaintext logs, which are then ingested by third-party SaaS metrics tools, triggering immediate GDPR/PCI compliance failures.
def log_event(user):
logger.info(f"User state: {user.__dict__}")
{"level": "INFO", "msg": "User: {'email': '[email protected]', 'session': 'sk_live_9a2f...', 'ip': '75.163.131.58'}"}
The Vulnerability: The AI prints the raw object state to stdout. Plaintext credentials, tokens, and PII are uploaded to your cloud metrics aggregator, exposing private customer records to downstream SaaS systems.
def log_event(user):
tn.info("auth.user.login", email=user.email, ip=user.ip)
{"event_type": "auth.user.login", "pii": "btn_cipher_9fa1...", "geo_device": "btn_cipher_b412..."}
The Safeguard: Sensitive fields are sealed using local cryptographic keys you readily hold in your environment (keystores/DIDs). Encryption happens in-process before logs touch disk (requiring no third-party key custody).
Getting Started is Two Lines of Code
Securing AI-generated code does not require rewriting your telemetry architecture. You initialize the runtime at startup, and TN handles the rest using the keys in your local keystore:
pip install tn-proto
import tn # Reads local keys and governance briefs automatically tn.init() # Log safely: PII is sealed in memory before hitting disk tn.info("auth.user.login", email=user.email, ip=user.ip) # Read your own logs back (fields come back decrypted) for entry in tn.read(): print(entry.level, entry.event_type, entry.fields)
# Your first `tn init` prints a claim link: your encrypted keys + config # attach to your account. The vault stores ciphertext only, never your keys. tn init # Recover on any machine from your recovery phrase: tn wallet restore
By referencing the repository's data governance briefs, your AI coding assistants will naturally learn to write these structured log calls instead of raw print statements.
Enterprise Security & Compliance Capabilities
TN delivers comprehensive sensitive data protection by securing your runtime environment and integrating with existing enterprise security architectures:
Secure Audit Logs
Build immutable compliance trails locally with cryptographic Merkle chain verification for SOC 2 and ISO 27001 audits without cloud data leaks.
PCI Compliance Solutions
Seal cardholder data (PAN, CVV) and billing variables in-memory before serialization, removing target databases from scope without proxy relays.
Agentic Payments & LLM Privacy
Prevent LLM prompt telemetry leaks and secure transaction parameters in autonomous agent payment and API execution loops.
Data Governance for Agile, Agentic, Fast, AI-Driven Workflows
At machine speed, reviewing every line of AI-generated code is impossible. Instead, you need a system that structures, audits, and protects the telemetry emitted by AI-driven systems. TN implements this through two interlocking pillars:
Dynamic Telemetry Auditing: "Know Your Exhaust"
Vibe-coded apps throw off telemetry dynamically and unpredictably. Instead of manual inspection, TN runs a local scanner over your log streams to discover and classify what is actually being written:
Map the Telemetry
Enumerates every event type and variable in your logs to establish a coverage baseline.
Isolate Sensitive Fields
Flags PII, device identifiers, and credentials using value patterns and specs.
Detect Correlation Risks
Identifies behavior-linking keys (like session IDs) that thread user actions across rows, escalating them to protected groups.
The scanner automatically synthesizes these insights into your local configuration, creating a secure-by-default routing policy without manual guesswork.
Per-Message Compliance: Cryptographic Splicing
Once configured, TN enforces data governance parameters directly inside the runtime execution boundary. Every time your application emits a log, the SDK automatically splices policy metadata directly into the message.
This ensures that every log record carries its own self-governing rules, instructing downstream AI models and agents on how they are permitted to consume the data.
Declares what the event represents (e.g. an immutable fact record of a completed transaction).
Defines the allowed boundaries for data usage (e.g. aggregate reporting only).
Outlines prohibited actions for downstream models (e.g. forbidding re-identification or profiling).
Explains the structural partitions protecting the data (e.g. audience-partitioned decryption keys).
Because these parameters are bound inside the signed log envelope, they travel with the data. When downstream LLMs, vector search tools, or analytics agents consume these logs, they parse this metadata in their context windows, ensuring compliance is checked and respected on every single record.
- We Provide Telemetry Profiling: Our local scanner scans raw output streams automatically, listing and mapping variables without manual code auditing.
- We Provide Callsite Process Sealing: Our SDK encrypts sensitive fields directly in memory within your container, preventing cleartext leaks before logs are written to disk.
- We Provide Context Priming: We provide standardized repository governance briefs so coding assistants respect data guidelines during code generation.
- We Provide Pre-Commit Gateways: Our linter acts as a CI gate, scanning code changes pre-commit to block builds containing unmapped variables.
- We Provide Cryptographic Verification: We compile your logs into verified chains, letting you mathematically audit downstream data actions.
To learn how to configure secure vibe coding in your workspace, check out our Agent integration guide, read about our field-level encryption specifications, or browse the Reference documentation.
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