Agent Sandbox Audit Log

4.20

Derivation Chain

Step 1 Proliferation of AI agent sandbox isolation technology

→

Step 2 AI agent sandbox infrastructure provisioning services

→

Step 3 In-sandbox agent behavior audit log SaaS

Problem

An increasing number of companies (IT agencies, AI Startups) are running AI agents in sandboxes, but they cannot produce structured audit logs of what files the agent read, what APIs it called, and what commands it executed inside the sandbox, spending an average of 4-8 hours tracing the root cause when security incidents occur. In multi-agent environments, tracking inter-agent interactions is impossible, making it difficult to even reproduce failures.

Solution

A lightweight sidecar agent is injected into sandbox runtimes (Docker/VM/WASM) to capture filesystem access, network calls, and process execution in real time, providing per-agent timeline views and anomaly alerts. Core features: (1) Automatic syscall-level behavior log collection, (2) Per-agent behavior timeline visualization, (3) Real-time alerts for policy violations (file access outside allowed scope, external API calls).

Target: DevOps/security leads at AI Startups and IT agencies with 5-30 employees

Revenue Model: SaaS monthly subscription. Free tier (3 agents, 7-day log retention), Pro $35/month per workspace (~49,000 KRW; 20 agents, 90-day retention), Enterprise $140/month (~190,000 KRW; unlimited, custom policies)

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

4.0/5

U Urgency

5.0/5

M Market

4.0/5

R Realizability

4.0/5

V Validation

4.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (74%)

Tech Complexity

29.3/40

Data Availability

25.0/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (60/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

16.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

12.0/15

Solo Buildability

7.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Frontend [medium] Infrastructure [low]

Dashboard