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Agentpathfinder

AgentPathfinder 把任务拆成多个步骤,用 XOR 将 256 位主密钥分片到各步骤,全部成功后才允许重建;每步由签发层生成 HMAC 令牌并写入仅追加审计链,任何改动都会导致校验失败。提供 pf 命令行、Python SDK、本地 Flask 仪表盘与静态 HTML 报表,声明无网络访问与数据收集。作者自述防篡改但非免疫:具备文件系统权限的智能体仍可读取分片重建密钥。

certainlogicai
certainlogicai
热度 25.94
最近更新 2026-04-26 09:21:47
分类:安全依赖:代码执行 / 读写文件应用场景:任务管理 / 自动化脚本 / 工作流 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add agentpathfinder
Metadata
summary
Tamper-evident cryptographic tracking for AI agent siblings
read_when
["installing","configuring","troubleshooting"]
name
AgentPathfinder
description
Unlimited tamper-evident cryptographic task tracking for AI agents. Green = proven complete. Red = failed or incomplete. Free forever — upgrade for dashboard, multi-agent views, and full audit exports. Security: Open-source, no network access, no data collection. See SAFETY.md for full disclosure.
version
1.0.6
author
CertainLogic
license
MIT
platforms
["linux","macos"]

AgentPathfinder

Green = cryptographically proven complete. Red = not. Dead simple in every reply.

AgentPathfinder gives your AI agents cryptographic proof of task completion. Decompose any task into N steps, shard a master key across them via XOR, and only reconstruct the key when every step finishes successfully. Every event is HMAC-SHA256 signed and written to an append-only audit trail.

Free forever, unlimited tasks, no usage caps. Upgrade when you want a dashboard, multi-agent views, or exportable audit files.

What You Get

Free (Now) Pro (Coming Soon)
✅ Unlimited tamper-evident tracking via green/red in messages 🖥️ Beautiful dead-simple dashboard
✅ Cryptographic sharding (XOR-based, 256-bit) 📊 Multi-agent sibling tracking
✅ Audit trail with HMAC verification 📋 Full audit exports (CSV/JSON)
✅ Crash recovery + atomic writes 🔗 Webhook notifications
✅ CLI with visual confirmations 📧 Priority support

Enterprise: On-prem deployment, SSO/SAML, exportable tamper-proof audit files for compliance.

Install

clawhub install agentpathfinder

Then verify:

pf install

Quickstart

# Create a 4-step deployment task
pf create "deploy_api" "run_tests" "build_docker" "push_registry" "restart_service"
# → Task created: a7f3d2e1-...

# Run it (simulation mode — see what it looks like)
pf run a7f3d2e1-...
# → ⏳ SIMULATION MODE — No real code executed.
#    ✅ deploy_api is complete! Progress: 4/4
#    ✅ Step 1 complete: run_tests (token: tok_abc123…)
#    ✅ Step 2 complete: build_docker (token: tok_def456…)

# Check status — one glance says it all
pf status a7f3d2e1-...
# → ✅ task_complete 4/4 (all green)

# Verify audit integrity
pf audit a7f3d2e1-...
# → ✅ All 6 events verified

# Reconstruct the master key (only works when all steps pass)
pf reconstruct a7f3d2e1-...
# → ✅ Key reconstructed successfully

Real Execution (Python SDK)

The CLI marks steps complete for demo. For real automation, bind Python functions:

from pathfinder_client import PathfinderClient
from agentpathfinder import AgentRuntime

pf = PathfinderClient()
tid = pf.create("deploy", ["test", "build", "push"])

# Bind real functions
def run_tests():
    subprocess.run(["pytest", "-v"], check=True)
    return "passed"

def build_docker():
    subprocess.run(["docker", "build", "-t", "app", "."], check=True)
    return "app:latest"

# Execute
runtime = AgentRuntime(pf.engine, pf.issuing)
runtime.execute_task(tid, {
    "test": run_tests,
    "build": build_docker,
    "push": lambda: subprocess.run(["docker", "push", "app"], check=True),
})

# If any step fails → task pauses, audit trail shows exactly what happened
# Retry after fixing:
runtime.retry_step(tid, 2, build_docker)

Architecture

┌─────────────┐  create_task()   ┌──────────────┐
│   CLI/SDK   │ ───────────────▶ │  TaskEngine  │
│ (pf create) │                  │              │
└─────────────┘                  │ - Generate K │
                                 │ - Split(K,N) │
                                 │ - Write JSON │
                                 └──────────────┘
                                        │
                                 Vault: step shards
                                 Tasks: metadata only
                                        │
┌─────────────┐         ┌──────────────┘
│ AgentRuntime│◄────────│ IssuingLayer │
│(execute_step│  token  │              │
└─────────────┘         │ - HMAC sign  │
        │               │ - Audit log  │
        ▼               └──────────────┘
┌─────────────┐                ▲
│ AuditTrail  │◄───────────────┘
│(JSONL+HMAC) │
└─────────────┘

Security

Tamper-evident, not tamper-proof. Every event is HMAC-SHA256 signed with a derived audit key. If someone modifies the audit trail or task files, verification fails and you know immediately.

Current limitations: A malicious agent with filesystem access could read vault shards and reconstruct the key. For full isolation, upgrade to Pro (hosted vault) or Enterprise (TEE/remote attestation).

Feature How It Works
Cryptographic sharding 256-bit master key split into N+1 shards via XOR
Atomic persistence temp + fsync + rename — no partial writes
Crash recovery Steps in running state detected and reset
Concurrency control Advisory file locks per task
Audit integrity HMAC-SHA256 chain, any edit breaks verification
Agent authentication Shared-secret HMAC tokens per agent

CLI Reference

Command What It Does
pf install One-command setup, verify deps
pf create <name> [steps...] Create a new sharded task
pf run <task_id> Simulate running all steps
pf status <task_id> Visual status: ✅/❌/⏳ at a glance
pf audit <task_id> Show tamper-verified audit trail
pf reconstruct <task_id> Reconstruct master key (all steps required)
pf register-agent <id> Register an agent for authenticated execution
pf dashboard Start web dashboard (requires Flask)

Dashboard

# Generate a static HTML dashboard (no server needed)
python3 scripts/dashboard_static.py --output report.html
# Open report.html in your browser

# Or start live dashboard
pf dashboard --port 8080
# Open http://localhost:8080

The dashboard shows:

  • Tasks tab: Live status, progress bars, step icons, audit badges
  • Brain Stats tab: Token savings, cache hit rate, $ saved, hallucinations caught
  • CSV export: One-click report download

Troubleshooting

Problem Fix
"agentpathfinder not found" Run pf install to verify setup
"Task not found" Check task ID. Use pf status to list recent tasks
"Reconstruction failed" Not all steps complete. Run pf status to see which
"Step already running" Previous run crashed. Auto-reset or call reset_running_step()
"Agent auth failed" Re-run pf register-agent <id>
Dashboard won't start Install Flask: pip install flask
Audit reports tampered Files were modified outside the engine. Investigate immediately

License

MIT. Free forever. No usage caps. Pro dashboard coming soon.


Built by CertainLogic — deterministic AI, cryptographic proof.