E-01 · BUILDING
An e-commerce security scanner shop owners can act on
Small online shops rarely know what an attacker can see from the outside. Existing scanners dump long technical lists. I'm building one with a graphical interface that ranks findings by real-world risk and tells the owner which rule they break and what to fix first.
Why it matters now
Since 2025, PCI DSS v4.0.1 requires shops to keep an inventory of every script on their payment page (requirement 6.4.3) and to detect when that page is tampered with (11.6.1). Most small merchants have never heard of either.
Card-skimming attacks exploit exactly those gaps, and one unlisted third-party script on checkout is enough.
How it works
- COLLECTPublic signalsDNS, certificates, headers, page scripts, software versions
- ENRICHThreat intelligencePublic reputation and vulnerability APIs
- SCOREReal-world riskCISA KEV, EPSS, CVSS
- MAPRules brokenPCI DSS, OWASP ASVS, ISO 27001
- SHOWGUI and reportsFindings in the interface, exports for developers and owners
Each stage is a separate module, so new checks or frameworks plug in without touching the rest. Shop owners work in the graphical interface; developers can export the technical report. An optional AI module turns findings into plain-language fixes for non-technical owners.
The interface
concept · example dataThe main screen as I'm designing it. Findings are sorted by real-world risk, and opening one shows the rule it breaks and the fix in plain language.
What the owner gets
There's no command line. In the interface, each finding looks like the example below.
example-shop.lv/checkout (example output) finding unlisted 3rd-party script on payment page severity HIGH · actively exploited pattern breaks PCI DSS 6.4.3, 11.6.1 fix approve or remove the script, enable tamper alerts
Built to be safe to run
- Passive by defaultOnly public data. Active probing stays off unless the user proves they own or are authorised to test the site.
- Bring your own keysNo API keys ship with the tool. Users supply their own and stay within each provider's terms.
- Secure by its own standardTimeouts and rate limits on every request, careful parsing of API responses, no secrets in logs, protection against server-side request forgery, and dependency and static analysis in CI.
- AI-assisted, human-ownedMuch of the code is written with AI help. The architecture, threat model, scoring decisions, reviews and tests are mine, recorded as decision records.
Where it stands
- DONETopic approved, October 2026
- NOWArchitecture and threat model
- NEXTBuild the modules and evaluate them on test shops
- 2027Thesis defence, then an open-source release under Apache-2.0