KnoxIQ: The AI Agent That Triages Mobile App Vulnerabilities

KnoxIQ: The AI Agent That Triages Mobile App Vulnerabilities

KnoxIQ is the agentic triage layer in Appknox. It takes the findings from your SAST and DAST scans, filters out the ones that aren't real and ranks the rest by how exploitable they are in your build. For each one, it shows you how to reproduce it and writes a fix for your app, including a prompt for Claude Code, Cursor, Github Copilot or any AI coding agent.

Ask any Security expert, finding issues was never the hard part. The hard part starts when the report lands. Someone has to decide which findings are real, which ones an attacker could actually use and how a developer should fix them. On most teams, that someone is a senior security engineer, working through the list by hand.

But now, KnoxIQ does that triage, it validates every finding, scores its exploitability, writes steps to reproduce it and hands your developers a fix for your app. You still decide what ships. You just stop spending your week working out where to start.

Why mobile security teams can't keep up with their own findings

A scan produces findings. Turning them into fixes is manual work, and it breaks down in four places.

Noise. A single scan can return hundreds of findings. One vulnerability type can have many instances: every hardcoded string, every sensitive log statement, every unobfuscated class. Most AppSec teams cover web and API too, so the same five or ten people get a long list from every tool.

Manual triage doesn't scale. Confirming a finding means reproducing it: decompile the APK or IPA, find the class or manifest entry, check whether the pattern is reachable. Multiply that by every finding and every release, and your most expensive people spend their week on repetitive work.

Severity without exploitability. CVSS tells you how bad an issue could be. It doesn't tell you whether an attacker can exploit it in your build. So teams sort by severity, spend sprints on high-severity findings that carry little real risk and leave an exploitable medium waiting.

Low-context handoffs. Developers get a finding with a description, a CWE ID and a generic compliant code sample. They still have to work out where the issue lives in their app and what a safe change looks like. Fixes slow down, and the back-and-forth wears on both teams.

AI coding agents have widened the gap. Teams that shipped quarterly now ship weekly, and some ship daily. Ten releases a week can mean ten assessments and a thousand findings, all landing on the same security team. Code volume has scaled. Security headcount hasn't.

What is KnoxIQ and how does it triage mobile app vulnerabilities?

We built KnoxIQ to do the triage work security engineers do by hand today: decide what's real, what's exploitable and how to fix it.

KnoxIQ sits on top of the Appknox scanner, and detection doesn't change. Appknox still tests your binary with the same deterministic SAST and DAST engines, so the same build gives the same findings every time. When a scan finishes, KnoxIQ picks up its findings and runs them through a set of AI agents, each with one narrow job.

That's what we mean by agentic, it isn't a chatbot beside your results or a summary on top of a report. It does the triage.

Today, KnoxIQ covers SAST and DAST findings for Android and iOS apps. API findings are next.

How KnoxIQ validates, prioritises, replicates and fixes mobile app vulnerabilities

Every finding goes through four steps, each handled by its own agent.

1. Validate. The validation agent checks each finding against your app and decides whether it holds up. Findings it can't support are filtered out as likely false positives. Hardcoded secrets get an extra test: KnoxIQ calls the API with the key it found and keeps the finding only if the call succeeds.
2. Prioritize. The exploit agent predicts how likely each valid finding is to be exploited in your build. It scores the finding with the Appknox Exploit Intelligence Score (AEIS), writes an attack scenario and shows the evidence behind the score.
3. Replicate. The replication agent writes steps to reproduce: the file to open, the command to run and the output you should see if the issue is real. A security engineer can confirm a finding in minutes instead of rebuilding it from scratch.
4. Fix. The remediation agent writes a fix for your app, not a generic code sample. It names the file, the class or method, and the change to make. It also writes a developer prompt you can paste into Claude Code, Cursor, GitHub Copilot or ChatGPT. The prompt tells the coding agent to change only what the security fix needs, and to ask rather than guess. Teams that don't use AI coding tools get the same fix as step-by-step instructions.
   
   

If your developers work with an AI coding agent, Appknox MCP takes the last step further. The agent pulls the KnoxIQ fix plan straight into the editor, applies the change in your repo and verifies it with an Appknox re-scan.

How AEIS scores exploitability

AEIS sits beside CVSS v4 on every finding. It doesn't replace it. CVSS answers "how bad could this be?" AEIS answers "can an attacker actually use it here?"

It's built from factors AppSec teams already know. For each finding, the exploit agent sets every factor to true, false or unknown, using a mix of fixed rules and AI reasoning.

The score runs from 1 to 10 and maps to high, medium or low exploitability. When the evidence doesn't settle a factor, the agent marks it unknown. It doesn't guess.

What it looks like in practice

Two findings from our internal demo show how KnoxIQ changes the order of work.

A medium that jumped the queue. Appknox flagged a StrandHogg task-hijacking issue in a sample Android app. On severity alone, it's a medium. KnoxIQ rated it highly exploitable. The validated finding traced it to an exported main activity combined with a PendingIntent that launches an activity with FLAG_ACTIVITY_NEW_TASK. That combination lets a malicious app inject a fake screen into the legitimate app's task stack. The fix plan pointed to AndroidManifest.xml and the exact change needed to secure the exported MainActivity. Sorted by CVSS, it would have waited behind every high. Sorted by exploitability, it went first.

A finding the agent wouldn't guess on. Appknox flagged missing code obfuscation in an iOS app. CVSS v4 scored it 2.1, and AEIS scored it 1, the lowest exploitability. The validation agent also found that the app's main executable was encrypted with Apple's FairPlay DRM (LC_ENCRYPTION_INFO with cryptid=1). Static analysis can't reliably read symbol names in an encrypted binary, so the agent couldn't confirm whether obfuscation was actually missing. It said so, and showed its reasoning. It didn't dismiss the finding as a false positive or call it confirmed. It left it for a human to review.

In another scan, the original results listed two findings under one vulnerability. KnoxIQ kept one and filtered the other as a likely false positive. Both stayed visible under Original Analysis.

Built so you stay in control

Putting AI into security triage raises fair questions. Here's how KnoxIQ keeps it in control:

• Detection stays deterministic. AI never decides what the scanner finds. It only triages what the scanner has already found.
• Every verdict shows its work. Each validated finding comes with the evidence, the agent's reasoning and a confidence level. Each AEIS score comes with its factors and an attack scenario.
• No silent dismissals. If every instance of a vulnerability looks invalid, KnoxIQ doesn't mark it as passed. It sends it to a human to confirm.
• The original results stay. Your full SAST and DAST output is always available under Original Analysis, so you can check exactly what KnoxIQ filtered out.
• Unknown means unknown. When the evidence isn't there, the agent says so instead of guessing.
• Scoped to your app. The agents work only on your scan results and your app, and guardrails keep each agent to its one task.
• You choose when it runs. KnoxIQ runs automatically by default, and the scan completes when triage does. Need a quick scan before a release? Switch the project to manual mode and run KnoxIQ when you're ready.

• Every verdict shows its work. Each validated finding comes with the evidence, the agent's reasoning and a confidence level. Each AEIS score comes with its factors and an attack scenario.
• No silent dismissals. If every instance of a vulnerability looks invalid, KnoxIQ doesn't mark it as passed. It sends it to a human to confirm.
• The original results stay. Your full SAST and DAST output is always available under Original Analysis, so you can check exactly what KnoxIQ filtered out.
• Unknown means unknown. When the evidence isn't there, the agent says so instead of guessing.
• Scoped to your app. The agents work only on your scan results and your app. Guardrails keep each agent to its one task.
• You choose when it runs. KnoxIQ runs automatically by default, and the scan completes when triage does. Need a quick scan before a release? Switch the project to manual mode and run KnoxIQ when you're ready.

What changes for your team

Your scans, reports and dashboard stay the same. What changes is the work that lands on people after the scan.
 

Get started

KnoxIQ is an add-on to the Appknox platform. Once it's enabled for your organisation:

1. Scan as usual. Upload a build or start a scan the way you do today. Nothing changes in how you scan.
2. Let KnoxIQ run. In automatic mode, it starts as soon as the SAST or DAST scan finishes. In manual mode, open the scan and run KnoxIQ yourself.
3. Work the list. Sort findings by exploitability. Open any finding to see its evidence, AEIS factors, steps to reproduce and fix.
4. Hand off the fix. Paste the developer prompt into your AI coding agent, or install Appknox MCP and let the agent fetch it directly.

Your scanner already finds the issues. Now KnoxIQ tells you which ones matter and how to fix them.

Already on Appknox? Ask your account team to enable KnoxIQ for your organisation.

New to Appknox? Book a demo to see KnoxIQ triage findings on your own app.