cat agentsec_identity.dbRUNTIME SECURITY GATEWAY

AGENTSEC.app

Before your autonomous AI agent deploys, exports, or executes high-risk tool calls (such as destructive shell commands or credential lookups), AgentSec intercepts the action, inspects the payload via PreToolUse hooks, scores the risk, and routes it to an active human gatekeeper.

PreToolUse_runtime_pipeline.sh
[01]Agent Action
[02]Runtime Inspect
[03]Risk Score
[04]Policy Check
[05]Allow / Block / Review
[06]Audit Trail
ls -la /modules/4 active subnets
promptshield.agentsec.app

PromptShield

Real-time classification checking for malicious prompt injections, jailbreaks, system role extraction, and data leaks.

mcpguard.agentsec.app

MCP Guard Lite

Secure stdio-based and network-based Model Context Protocol tool pipelines with strict allowedRoots parameters and credential redaction.

agentmap.agentsec.app

AgentMap

Trace agent dependencies, monitor active telemetry grids, and map out the dynamic network topology of active LLM agent processes.

approveops.agentsec.app

ApproveOps

Human-in-the-loop audit log console where reviewers inspect gated shell commands and sign off on executions in real-time.

cat evidence_generator.shRECRUITER AUDIT REPORT

Compile a consolidated system audit and compliance report demonstrating your sandbox and gating capabilities:

// INSTALL DIRECTLY VIA BASH

Install AgentSec as a lightweight hook package inside any repository. Configure safe commands to bypass network hops, and set enforce mode to block dangerous operations (like force pushes or production migrations) without manual approval keys.

[view integrations]

// RUN INTERACTIVE SANITY CHECK

Test AgentSec immediately in observe and enforce modes. Trigger a mock command payload (such as reading user keychain secrets) to see the PreToolUse interceptor block the action and spin up an active approval gate link.