AgentGate intercepts every agent action before execution — verifying identity, validating delegation chains, and detecting behavioral drift in real time.
$ python demo.py AgentGate PDP — Trust Authorization Layer ─────────────────────────────────────────[REGISTER] agent_id=analyst_001 purpose="Summarize quarterly business reports"[TOKEN] issued: eyJhbGciOiJFZERTQSJ9... (Ed25519 JWT — scope embedded + signed)[REQUEST] action=read resource=/reports/q1.pdf → PERMIT (trust=0.91)[REQUEST] action=read resource=/reports/q2.pdf → PERMIT (trust=0.89)[REQUEST] action=read resource=/reports/q3.pdf → PERMIT (trust=0.87)[REQUEST] action=read resource=/reports/q4.pdf → PERMIT (trust=0.86)...6 more reads in under 5 minutes...[REQUEST] action=export resource=/reports/*[KILL CHAIN] *** BULK_READ_THEN_EXFIL detected *** 10 reads in 4m32s followed by export attempt Pattern: data enumeration → exfiltration[DECISION] *** DENY ***[REASON] Kill chain: bulk read then exfiltration sequence. No single request triggered this. The sequence did.[AUDIT] entry #4821 — HMAC-chained, tamper-evident[ALERT] security team notified instantly
Your agents have credentials. Do you know what they're doing with them? #
Enterprises are deploying autonomous AI agents at scale — but the security infrastructure hasn't kept up. Every agent is a potential attack surface.
OAuth can't detect scope creep
Traditional identity systems grant access once and assume good behavior. They cannot detect when an agent exceeds its delegated scope mid-task.
Delegation chains are invisible
When Agent A delegates to Agent B delegates to Agent C — who authorized the final action? No existing tool answers this.
Behavioral drift goes undetected
An agent's behavior shifts silently over time. By the time you notice, the damage is done.
AgentGate intercepts before execution #
Every agent action is scored across four dimensions before it's allowed to run. No agent bypasses the gate.
Identity Verification
25%Ed25519 JWT tokens with scope embedded in the signed credential — immutable after issuance, offline-verifiable with the public key. No database lookup required.
Delegation Chain Integrity
25%Full chain traversal at every authorization call: every ancestor's scope is verified. Atomic revoke_chain neutralizes an agent and all descendants in one call.
Purpose Alignment
30%Embedding-based semantic scoring: action + resource (85% weight) vs. declared purpose. Justification is capped at 15% — cannot be used to bypass a misaligned action.
Behavioral Anomaly Detection
20%Per-agent velocity baselines with trust decay over time. Dormancy followed by sudden high-volume activity is itself a risk signal — no static thresholds.
Kill Chain Detection
Beyond single-requestEach individual request may look clean. AgentGate examines the full 5-minute sequence. Bulk reads followed by an export. A read followed by a delete on the same resource. Progressive sensitivity escalation. Directory sweeps across 6+ prefixes. Patterns that only become visible across multiple calls — and that no rule-based system can catch.
Drop in your API key — one line of code
See every agent action in real time — attacks blocked live
Demo scenario — AgentGate intercepting a simulated multi-agent attack sequence in real time
See AgentGate in action #
Watch a live run — real agents, real attacks, real-time blocking.
The market context #
The regulatory and threat landscape is converging. Enterprises need answers now.
OWASP LLM06
Excessive Agency — agents granted permissions beyond their declared scope, acting outside their intended purpose. Listed as a critical risk in OWASP Top 10 for LLM Applications.
OWASP Top 10 for LLM Applications, 2025
MITRE ATLAS
Adversarial ML tactics against AI systems now formally catalogued — reconnaissance, privilege escalation, and data exfiltration all apply to autonomous agents.
MITRE ATLAS, 2024
August 2026
EU AI Act high-risk obligations take effect — enterprises have months, not years, to implement governance controls for high-risk AI systems.
EU AI Act (Regulation 2024/1689)
Regulatory pressure and adversarial sophistication are converging. Teams without agent governance controls today face compliance exposure by Q4 2026.
Works with your existing stack #
Drop-in integration. No framework changes. No rewrites.
from agentgate import AgentGate gate = AgentGate("http://localhost:8000", api_key="your-key")gate.register( "my_bot", "ReportBot", "Summarize quarterly business reports", authorized_resources=["/reports/*"], authorized_actions=["read"],) # Authorize before each action — PERMIT | ESCALATE | DENYresult = gate.authorize("read", "/reports/q3.pdf") # Or use the decorator — enforcement is automatic@gate.guard("read", resource_arg="path")def read_document(path: str) -> str: return open(path).read()
Request Early Access #
We're onboarding select enterprise pilot teams with limited availability.
Priority given to teams running LangGraph, LangChain, or custom agent frameworks in production with real compliance requirements.
Dedicated onboarding
1:1 setup with the founding team
Pilot pricing
Flexible pricing for early adopters
Direct influence
Shape the roadmap with your use case
We'll review your request and get back to you within 48 hours.