360 Secure SkillHub
360 安全技能中心

Agentpathfinder

这是一款为AI代理提供防篡改加密任务追踪的工具,核心功能含XOR密钥分片验证任务完成、HMAC-SHA256签名审计追踪,以绿红标识任务/步骤状态。支持CLI模拟及Python SDK绑定真实函数执行,适用于多步骤部署、自动化流程监控等场景。免费版提供无限任务追踪、审计验证等,升级可获仪表盘、多代理视图等。开源无网络访问,不收集数据。

certainlogicai
certainlogicai
热度 25.90
最近更新 2026-04-26 09:21:47
分类:自动化依赖:代码执行 / 读写文件应用场景:自动化脚本 / DevOps / 任务管理 / 工作流

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.