B

Binary Audit Report

3.25

Derivation Chain

Step 1 AI+Ghidra binary backdoor detection technology
→
Step 2 Automated binary security auditing
→
Step 3 SI/outsourced software binary integrity verification Report service

Competitor references

No usable source links are available for this idea. Its signal notes and scores need independent verification.

Problem

Financial institutions and public agencies lack the internal capability to verify whether software delivered by SI vendors contains backdoors or malicious code. External security audits cost $7,500-$22,500 (10-30 million KRW) per engagement, and mid-sized financial firms receiving 10-30 deliveries annually cannot afford full inspections, resorting to sample-based checks only.

Solution

A SaaS that automatically detects backdoors and malicious patterns through AI-powered static analysis when delivered binaries are uploaded, generating compliance reports. (1) Automated reverse engineering using Ghidra/radare2 + AI anomaly pattern detection, (2) reports mapped to Financial Supervisory Service/ISMS-P audit criteria, (3) delivery history management + automated change comparison.

Target: IT security teams and information security officers at financial institutions and public agencies with 100-1,000 employees
Revenue Model: Per Transaction scan at $375/binary + Monthly Subscription at $1,493/month (includes 10 scans, additional scans at $225 each). Target ARR of ~$360,000 with 20 institutions onboarded
Ecosystem Role: Regulation
MVP Estimate: 1_month

NUMR-V Scores

N Novelty
4.0/5
U Urgency
4.0/5
M Market
3.0/5
R Realizability
2.0/5
V Validation
4.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (57%)

Tech Complexity
24.7/40
Data Availability
20.0/25
MVP Timeline
12.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (58/100)

Competition
8.0/20
Market Demand
9.4/20
Timing
16.0/20
Revenue Signals
12.0/15
Pick-Axe Fit
10.5/15
Solo Buildability
2.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Backend [high] AI/ML [medium] Frontend [low]
Dashboard