plyra-id 0.1.1

Cryptographic identity and audit trails for autonomous AI agents

plyra-id

Cryptographic identity and audit trails for autonomous AI agents.

When your agents go into production, compliance teams ask: "Who did this? Who authorized it? Can you prove it?"

You have logs. You don't have proof.

plyra-id gives you cryptographically signed, tamper-evident receipts proving who did what and who authorized it.

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The Problem

Autonomous agents are moving into production across enterprises—in financial services, healthcare, insurance, and legal. But there's a compliance wall:

• Who authorized this action? Logs don't prove authorization.
• Who is responsible if something goes wrong? You can't trace accountability.
• Can you prove this in an audit? Logs can be tampered with. Receipts can't.

plyra-id solves this with one decorator.

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The Solution

from plyra_id import AgentID, sign_action

# Create agent identity (once)
agent = AgentID.create(owner="[e-mail]", name="document-analyzer")

# Sign every action (automatic with frameworks)
signature = sign_action("analyzed_document_123", agent.private_key_pem)

# Verify in audit (tamper-evident)
is_valid = verify_signature("analyzed_document_123", signature, agent.public_key_pem)
# True ✓ (can be proven in court)

One decorator. Framework-agnostic. Compliance-ready.

---

Framework Support

plyra-id integrates seamlessly with the frameworks you're already using:

LangGraph

from langgraph.graph import StateGraph
from plyra_id.frameworks.langgraph import PlyraCheckpointSaver, sign_node

@sign_node(name="research", agent_id=agent.id, authorizer="[e-mail]")
def research_node(state):
    return {"result": web_search(state.query)}

# Every checkpoint is now a signed receipt
checkpointer = PlyraCheckpointSaver()
compiled = graph.compile(checkpointer=checkpointer)

# Export compliance report
audit_trail = checkpointer.export_audit_trail(format="json")

AutoGen

from autogen import AssistantAgent
from plyra_id.frameworks.autogen import PlyraAgentWrapper

assistant = AssistantAgent(...)
wrapped = PlyraAgentWrapper(
    agent=assistant,
    agent_id=agent.id,
    authorizer="[e-mail]"
)

reply = wrapped.generate_reply(messages)
# Returns both: {"reply": ..., "audit_entry": {...}}

CrewAI

from crewai import Task
from plyra_id.frameworks.crewai import PlyraTaskWrapper

task = Task(description="Analyze financial report")
wrapped = PlyraTaskWrapper(task, agent_id=agent.id, authorizer="[e-mail]")

result = wrapped.execute()
# Returns both: {"result": ..., "audit_entry": {...}}

Plain Python

from plyra_id.frameworks.python import sign_action

with sign_action(agent_id, "fetch_data", authorizer) as log:
    data = fetch_from_api()
    # log now contains signed audit entry

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Export & Compliance

Export signed audit trails in any format:

# JSON (for APIs, pipelines)
json_trail = audit_log.to_json(pretty=True)

# CSV (for Excel, compliance reports)
csv_trail = audit_log.to_csv()

# SIEM integration (Datadog, Splunk, Sumo Logic)
exporter = DatadogExporter(api_key="...")
for entry in audit_log.entries:
    exporter.export(entry)

Every entry includes:

• Agent ID
• Action taken
• Timestamp (ISO8601)
• Signature (Ed25519, tamper-proof)
• Authorization (who approved)
• Policy constraints (what was forbidden)
• Success/failure status

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Use Cases

Financial Services

• KYC/AML agents: Prove who performed customer verification
• Trade execution: Audit trail for every agent-initiated trade
• Compliance: Meet GLBA, SOX, OCC requirements

Healthcare

• Prior authorization: Signed receipts for agent approvals
• Patient data access: Who accessed what, when, why
• HIPAA audits: Tamper-evident proof of compliance

Insurance

• Claims processing: Agent decisions with authorization proof
• Underwriting: Signed audit trail for every agent assessment
• State compliance: Meet state-by-state AI regulations

Legal

• Contract review: Agent analysis with attorney sign-off
• Due diligence: Verified agent findings for M&A
• Legal research: Traceable agent citations

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Installation

# Core library only
pip install plyra-id

# With LangGraph support
pip install plyra-id[langgraph]

# With all frameworks
pip install plyra-id[langgraph,autogen,crewai]

# With SIEM exporters
pip install plyra-id[otel,datadog]

# With PostgreSQL backend
pip install plyra-id[postgres]

---

Quick Start (5 minutes)

1. Create an agent identity:

from plyra_id import AgentID

agent = AgentID.create(
    owner="[e-mail]",
    name="document-analyzer"
)
print(f"Agent ID: {agent.id}")

2. Sign an action:

from plyra_id import sign_action, verify_signature

action = "analyzed_report_2024_q1"
signature = sign_action(action, agent.private_key_pem)
print(f"Signature: {signature}")

# Verify
is_valid = verify_signature(action, signature, agent.public_key_pem)
print(f"Valid: {is_valid}")  # True ✓

3. Create an audit log entry:

from plyra_id.core.audit_log import AuditLogEntry, ActionStatus
from datetime import datetime, timezone

entry = AuditLogEntry(
    agent_id=agent.id,
    action="analyzed_report_2024_q1",
    input_hash="sha256:abc123...",
    authorized_by="[e-mail]",
    timestamp=datetime.now(timezone.utc).isoformat(),
    signature=signature,
    policy_constraints=["no_external_payments", "max_token_usage:10000"],
    status=ActionStatus.SUCCESS,
)

print(entry.to_json(pretty=True))

4. Export for compliance:

from plyra_id.core.audit_log import AuditLog

audit_log = AuditLog()
audit_log.add_entry(entry)

# JSON for your API
json_output = audit_log.to_json(pretty=True)

# CSV for audit committee
csv_output = audit_log.to_csv()

---

Command-Line Interface

# Export audit trail from a database
plyra-audit export --from langgraph --format json --output audit.json

# Verify a signature
plyra-audit verify \
  --signature "ed25519:abc123..." \
  --public-key pubkey.pem \
  --message "analyzed_report_2024_q1"

# Start audit dashboard
plyra-audit serve --port 8765 --db ~/.plyra/checkpoints.db

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Documentation

• Getting Started — 10-minute tutorial
• API Reference — Complete API docs
• Framework Guides — LangGraph, AutoGen, CrewAI
• Examples — Working code samples
• Exporters — Datadog, OpenTelemetry, etc.
• FAQ — Common questions

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Architecture

plyra-id is built in layers:

1. Core Identity (plyra_id.core)

   • Ed25519 keypair generation
   • Cryptographic signing & verification
   • Audit log schema & serialization
   • Policy constraint enforcement

2. Framework Integrations (plyra_id.frameworks)

   • LangGraph checkpoint saver
   • AutoGen agent wrapper
   • CrewAI task wrapper
   • Plain Python context manager

3. Exporters (plyra_id.exporters)

   • StdoutExporter (logging)
   • OpenTelemetryExporter (OTel)
   • DatadogExporter (Datadog)
   • SidecarExporter (webhooks)

4. Storage (plyra_id.storage)

   • SQLiteStorage (local)
   • PostgresStorage (cloud)

5. CLI (plyra_id.cli)

   • plyra-audit export
   • plyra-audit verify
   • plyra-audit serve

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Security

plyra-id uses Ed25519 (NIST-standard public-key cryptography) for all signatures.

• Private keys are never logged; export only with explicit flag
• Signatures are tamper-evident (any modification invalidates)
• Audit trails are immutable by design
• Policy constraints are enforced before action execution

For security issues, please email: [e-mail]

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Open Source

plyra-id is licensed under Apache 2.0. Build on it, extend it, integrate it. No proprietary lockdown.

• GitHub: https://github.com/plyraAI/plyra-id
• PyPI: https://pypi.org/project/plyra-id
• License: https://github.com/plyraAI/plyra-id/blob/main/LICENSE

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Contributing

We welcome contributions. See CONTRIBUTING.md for guidelines.

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Support

• Issues: https://github.com/plyraAI/plyra-id/issues
• Discussions: https://github.com/plyraAI/plyra-id/discussions
• Email: [e-mail]

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Roadmap

v0.1.0 (now)

• Core signing & verification
• Framework integrations (LangGraph, AutoGen, CrewAI)
• Exporters & storage backends
• CLI tool

v0.2.0 (Month 2)

• Enterprise dashboard (SaaS)
• SIEM integration (Datadog, Splunk, Sumo Logic)
• Advanced policy engine
• Compliance report generation

v0.3.0+ (Months 3+)

• Agent reputation scoring (plyra-cred)
• Payment integration (plyra-pay)
• Agent marketplace (plyra-marketplace)

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Citation

If you use plyra-id in your research or product, please cite:

@software{plyra_id,
  title={plyra-id: Cryptographic identity and audit trails for autonomous AI agents},
  author={Plyra AI},
  url={https://github.com/plyraAI/plyra-id},
  year={2026},
}

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Built with precision. Deployed with confidence. Scaled globally.

plyra-id: Identity infrastructure for the autonomous agent economy.