How are you auditing what your AI agents do in production?

AgentGate, a new trust authorization layer for autonomous AI agents, intercepts every agent action before execution to verify identity, validate delegation chains, and detect behavioral drift in real time. The system blocked a simulated attack where an analyst agent performed 10 bulk reads in under five minutes followed by an export attempt, identifying the sequence as a "bulk read then exfiltration" kill chain and denying the request. As enterprises deploy AI agents at scale, existing security tools like OAuth cannot detect scope creep, invisible delegation chains, or behavioral drift, leaving organizations vulnerable to attacks that no single request triggers.

The trust layer for autonomous AI agents AgentGate intercepts every agent action before execution — verifying identity, validating delegation chains, and detecting behavioral drift in real time. bash $ 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. python 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 Request Early Access /early-access We'll review your request and get back to you within 48 hours.