Four scanners,
one report.
Static analysis, dependency audit, dynamic testing and an AI penetration tester — run against every release and deduped into a single severity-ranked list.
Everything an attacker can reach — the code, what it pulls in, and the app that is actually running.
An application’s attack surface is three things at once: every line your team writes, every package and image you pull in, and the live URL exactly as an attacker meets it. Testing one and calling it secure leaves the other two open.
So four scanners run against all three. Two of them read what you wrote — static analysis of the source, and an audit of every dependency. Two of them attack what you run — dynamic testing against the live application, and an AI penetration tester that chains flaws the way a person would.
Static scanners read what you wrote; the dynamic pair attacks what you run — the way a breach actually starts. Their output is deduplicated into one report, severity-ranked and ordered fix-first, so the list your engineers open is a queue rather than four inboxes.
Four scan classes, one findings report.
Static code analysis — SAST
Reads every line of source and flags exploitable patterns before they ship.
- Parses the code itself, tracing how untrusted input travels through it
- Rulepacks cover the OWASP Top 10 and CWE flaw patterns for each major language
- Findings point to the exact file and line, so the fix lands before release
- SQL injection — user input concatenated into a database query.
- Cross-site scripting — unescaped input rendered into a page.
- Command injection — request data reaching a shell command.
- Hard-coded secrets — keys and passwords committed to source.
- Weak cryptography — MD5, ECB mode, fixed salts.
- Path traversal — file paths built from user input.
Software composition analysis — SCA
Most of a modern app is open source you didn’t write. This audits all of it.
- Inventories every package, direct and transitive, plus container image layers
- Checks each version against public CVE databases refreshed daily
- Each hit names the fixed version to upgrade to — patching, not research
- Known-CVE packages — a pinned version with a published exploit.
- Transitive flaws — a vulnerability three dependencies deep.
- Vulnerable base images — container OS layers years out of date.
- Secrets in images — credentials baked into a container layer.
- Licence risk — GPL-family licences hiding deep in the tree.
- IaC misconfiguration — Kubernetes and Terraform granting root.
Dynamic application testing — DAST
Probes the live application exactly the way an attacker would — from outside.
- Crawls every page and API of the running app, then fires real attack traffic
- Runs the OWASP Top 10 as live attacks — injection, XSS, auth and session flaws
- A finding here was demonstrated against the app, not inferred from the code
- Injection, proven live — shown on the wire, not in theory.
- XSS that executes — payloads that actually fire in the browser.
- Broken authentication — sessions that survive logout.
- CSRF — state-changing requests accepted without proof of intent.
- Missing security headers — no CSP, HSTS or cookie flags.
- Information leakage — stack traces and debug endpoints exposed.
The AI penetration tester
Reasons like a human pentester: probes, adapts, chains flaws into an attack.
- An autonomous agent that explores the app, forms attack hypotheses, tests them
- Goes where rulebooks can’t — business logic, workflow abuse, multi-step chains
- Reports a replayable attack narrative, not a list of rule IDs
- Broken object access — change one ID, read another customer’s account.
- Privilege escalation — a normal user reaching admin functions.
- Business-logic abuse — negative quantities, replayed coupons.
- Chained attacks — three low findings combined into a takeover.
- Auth workflow flaws — reset links that leak tokens, OTPs that never expire.
- Mass data exposure — one authorised request, iterated over IDs.
Grey-box testing on every release, with a report your engineers can act on.
Testing runs against a staging URL with test credentials you issue and can revoke — so the application is examined both as an outsider meets it and as a logged-in user does, including authenticated flows, roles and object access.
Each finding carries a reproducible proof. Anything that could not be demonstrated is graded Tentative rather than presented as fact. Only hosts you name are probed; anything out of scope is noted and never attacked.
- Scope and in-scope hosts, as tested
- Endpoints mapped by reconnaissance
- Vulnerability classes hunted
- Severity summary and fix-first priority
- Per finding: description and impact
- Evidence: the raw request and response
- A benign, reproducible proof of concept
- Steps to reproduce, then remediation
- Confidence grade, CWE and OWASP references
Where an application breach costs the most.
Four domains where the app itself is the regulated surface.
Banking & FS
Customer-facing portals and APIs moving money and holding accounts.
Use case: Pre-release scan on every deploy D02Healthcare
Patient records reachable through the web tier and its integrations.
Use case: Object-access testing on record APIs D03Government
Citizen services exposed to the public internet by design.
Use case: Authenticated grey-box assessment D04Telecom
Self-care apps and provisioning APIs at subscriber scale.
Use case: Business-logic abuse testingThe same 5-stage system we run everywhere.
Discovery to scale, engineered for production from day one.
See how we deliver →Point it at one application.
We run the full stack against a staging URL — never production, so attack traffic never touches a customer. You get a severity-ranked findings report and a session walking your team through the fixes.