Skip to main content

Verifiable task delegation between AI agents

Project description

OpenSSF Scorecard

PyPI version

Python versions

License

Supply Chain 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

  1. PLANNER NODE -> verification: True
  2. RESEARCHER NODE -> verification: True
  3. TAMPERED HANDOFF -> verification: False
  4. 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


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

trusthandoff-0.3.3.tar.gz (47.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

trusthandoff-0.3.3-py3-none-any.whl (50.9 kB view details)

Uploaded Python 3

File details

Details for the file trusthandoff-0.3.3.tar.gz.

File metadata

  • Download URL: trusthandoff-0.3.3.tar.gz
  • Upload date:
  • Size: 47.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for trusthandoff-0.3.3.tar.gz
Algorithm Hash digest
SHA256 1d6020945117a0613f1bbcd450021fcca1e2b88548fb804508a5544114a2c0a9
MD5 1e5b96c48882a85ce6ec5209215e0585
BLAKE2b-256 a6ac57cd569f74f4b4d458c59edcd77d19f773e625f7d32a031ad8b43bd0f658

See more details on using hashes here.

Provenance

The following attestation bundles were made for trusthandoff-0.3.3.tar.gz:

Publisher: publish.yml on trusthandoff/trusthandoff

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file trusthandoff-0.3.3-py3-none-any.whl.

File metadata

  • Download URL: trusthandoff-0.3.3-py3-none-any.whl
  • Upload date:
  • Size: 50.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for trusthandoff-0.3.3-py3-none-any.whl
Algorithm Hash digest
SHA256 5709b73ce0f67d074d544f08f46925ce73e69dfd5d3ab4c24733ff710ddac2c8
MD5 9e4d42d23cb66bdbffdb4137e87d4e14
BLAKE2b-256 e2c913a3faf8f4d616b721766617e5a0451083d62a2b1e9648f1ba8a31bdf76f

See more details on using hashes here.

Provenance

The following attestation bundles were made for trusthandoff-0.3.3-py3-none-any.whl:

Publisher: publish.yml on trusthandoff/trusthandoff

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page