Verifiable task delegation between AI agents
Project description
Releases are published from GitHub Actions using Trusted Publishing and include verifiable build provenance / attestations.
⚔️ Attack Demo
Legit output → accepted
Tampered output → rejected
Replay → rejected
Execution without proof is trust theater.
TrustHandoff
Most agent systems trust execution by convention.
TrustHandoff makes it provable.
What this is
TrustHandoff is a protocol layer for verifiable delegation and execution integrity in AI agent systems.
Think TLS for agents — but extended to execution.
TLS secures communication.
TrustHandoff secures execution.
The problem
In modern agent systems:
- intermediate outputs are trusted blindly
- permissions are long-lived and rarely enforced
- replay and tampering are not first-class concerns
- execution cannot be audited or proven
The weakest point is not the model.
It is the handoff.
What TrustHandoff does
TrustHandoff adds:
- signed, time-bounded task delegation
- replay protection via nonce tracking
- runtime revalidation of capabilities
- strict TTL enforcement (risk-based)
- human execution gates
- AI provenance tagging
- overlap window safety for token rotation
- event-based observability
- post-execution forensic analysis (Sentinel)
Core guarantees
Every execution becomes:
- tamper-evident
- replay-resistant
- runtime-verifiable
Example
- PLANNER NODE -> verification: True
- RESEARCHER NODE -> verification: True
- TAMPERED HANDOFF -> verification: False
- REPLAYED HANDOFF -> verification: False
What’s new in v0.3.3
This release closes the execution integrity loop.
Enforcement
- risk-based TTL (write=120s, read=900s)
- TTL bound to packet
- mismatch rejected at validation
- optional strict mode for production
Runtime integrity
- revalidation watcher detects drift mid-execution
- revoked or expired capabilities are rejected
- replay protection enforced
Execution control
- human review gates (blocking)
- capability constraints enforced at protocol level
Safety
- overlap window (30s) for token rotation
- prevents race conditions
Observability
- structured event system
- JSONL export for audit trails
- pluggable event sinks
Detection
- Sentinel detects:
- replay attempts
- stale capabilities
- overlap usage
- AI-generated payloads
Architecture
TrustHandoff plugs into existing stacks:
- MCP = tools
- A2A = communication
- LangGraph / CrewAI / AutoGen = orchestration
- TrustHandoff = delegation + execution integrity
Current scope
- local replay protection (Redis-ready)
- runtime revalidation
- TTL enforcement
- execution gating
- overlap safety
- event-driven observability
- forensic detection (Sentinel)
Direction
TrustHandoff is evolving into a distributed execution integrity layer for agent systems.
Planned:
- distributed nonce tracking
- shared revocation registries
- cross-agent invalidation
- network-aware trust boundaries
Philosophy
If you cannot prove execution, you cannot trust the system.
License
MIT
Project details
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Details for the file trusthandoff-0.3.3.tar.gz.
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- Upload date:
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- Tags: Source
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Provenance
The following attestation bundles were made for trusthandoff-0.3.3.tar.gz:
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Branch / Tag:
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Provenance
The following attestation bundles were made for trusthandoff-0.3.3-py3-none-any.whl:
Publisher:
publish.yml on trusthandoff/trusthandoff
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Statement:
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Statement type:
https://in-toto.io/Statement/v1 -
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Permalink:
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Branch / Tag:
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Access:
public
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Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@47fc5f4eaa8189388f19d6122f4678c9b26a8754 -
Trigger Event:
push
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Statement type: