Platform

A release workbench for mobile app defense.

RiskFront Lab organizes app package intake, policy selection, protection review, release evidence, and runtime routing in one operating model for mobile engineering and AppSec teams.

Release workspace reviewing

01 Build upload

Android or iOS package, release channel, app version, signing status, and reviewer owner.

02 Policy selection

Anti-tamper, anti-hooking, device-risk, network, screen, and response rules grouped by workflow.

03 AI-assisted review queue

Runtime signals are summarized into reviewer notes, severity hints, and suggested evidence paths.

04 Certified Secure release record

Protected build output, policy snapshot, reviewer signoff, certificate evidence, and event routing settings.

Operating flow

Protection work that stays close to the release.

The platform is structured around the steps teams already follow before a mobile release goes live. Each decision is tied to an app version, policy set, and review owner so security work does not become a side spreadsheet.

View report outputs Connect release tools

AI analysis layer

How AI participates in the workflow.

RiskFront Lab uses AI as an analysis layer across the mobile protection lifecycle. It reviews build metadata, selected policies, runtime threat events, device-risk signals, and release history to help security teams cluster related findings, draft reviewer-ready evidence, suggest severity and routing, and highlight policy gaps before a protected Android or iOS build moves forward. The customer team stays in control of enforcement decisions, while AI reduces manual triage, improves review consistency, and turns raw mobile security signals into release, audit, and response context.

Signal clustering

triage

Related runtime events can be grouped by app version, device-risk pattern, protected workflow, and policy action so reviewers see a focused case instead of isolated alerts.

Evidence drafting

review

Technical event details are shaped into reviewer-ready notes that explain what happened, which protection responded, and what evidence should be inspected.

Policy gap hints

rules

Release history and policy selections can surface missing coverage for sensitive flows such as payments, identity, account recovery, health data, and paid access.

Human approval

control

AI suggestions remain attached to customer-approved rules, reviewer owners, and release records so enforcement decisions stay visible and reversible.

Platform modules

Separate workspaces for build, policy, evidence, and response.

Build intake

package

Capture app version, platform, release channel, package owner, build source, and required protection profile before shielding begins.

Policy builder

rules

Group runtime controls by user flow so payment, identity, account recovery, and paid access screens can have different response behavior.

Release record

audit

Keep policy snapshots, protected package history, Certified Secure evidence, reviewer notes, and handoff status attached to the release that used them.

Event routing

signal

Send severe runtime events to security review, risk operations, support queues, or downstream monitoring tools based on policy outcome.