NowSecure Agentic AI
Your mobile security data has answers. Just Ask.
NowSecure Agentic AI connects to your mobile risk data. It answers portfolio-level questions, takes scoped actions on your behalf, and returns proof, not just findings.
Mobile vs. Web
The attacker already has your binary.
No perimeter. No firewall. Mobile apps are publicly downloadable, decompilable, and analyzable
before you fix a single line of code.
of breaches start with vulnerability exploitation, overtaking credential theft for the first time.
Verizon DBIR 2026
from vulnerability disclosure to weaponized exploit. Down from 771 days in 2018.
CSA / Synack 2026
Ask a question. Get proof. Take action.
Ask about a finding, search your portfolio, or push a fix. Every answer is
grounded in evidence.
AI Chat features
00 Foundation
NowSecure is the AI harness for mobile security.
Your AI IDE wraps the model in your codebase. NowSecure does the same for mobile security: your data, your evidence, your tools as the harness. The model is the engine.
- MCP connects NowSecure AI tools to your mobile security data
- AI reasons over your verified findings, not training data. Answers reflect what's actually in your apps.
- Every answer is auditable. Every action is traceable.
01 AI Chat
Mobile security expertise, on demand.
Ask about any finding in plain language. AI Chat answers from binary evidence, not a CVE database lookup.
- Interprets binary evidence, runtime traces, and SDK risk. No mobile specialization required.
- Every answer links to its source artifact. One-click verification.
- Download any conversation as markdown, ready for a leadership update or incident response.
02 SDK and Component Exposure
Know which apps bundle a vulnerable SDK before your engineering team asks.
When a CVE drops, you need exposure data fast: which apps, which versions, how severe. AI Chat queries your portfolio and returns the answer, backed by binary evidence and not an external database.When a CVE drops, you need exposure data fast: which apps, which versions, how severe. AI Chat queries your portfolio and returns the answer, backed by binary evidence and not an external database.
- Search any SDK, library, or package version across your portfolio.
- Results include version, severity, and a direct link to the assessment
evidence. - Stale data is flagged. The AI offers a fresh assessment before you act.
03 MCP Rule Creation
Set the rule in plain language. It applies to every future assessment.
Tell your AI tool what the rule should be. NowSecure MCP translates it to a configuration change, shows scope and impact before applying, and updates every affected app automatically.
- State the rule in plain language: suppress a finding type, flag a behavior, or adjust severity thresholds.
- MCP translates it to a NowSecure configuration change. Scope and impact shown before you confirm.
- Future assessments across every affected app reflect the updated rule automatically.
AI Chat features
04 AI Navigator
Full-surface testing that reaches the flows scripted automation skips.
AI Navigator handles login flows, multi-step transactions, and
conditional screens, the surfaces most scanners skip. Runs on real
devices.
- Navigates authenticated flows, multi-step transactions, and dynamic UI states. No scripting required.
- Exposes sensitive data handling issues in payment flows and conditional screens that scripted tools never reach.
- All findings are backed by real-device runtime evidence, not emulated or synthetic behavior.
Verify. Fix. Ship
05 MCP Integration
NowSecure evidence and context inside the AI tools your team already uses.
NowSecure MCP connects binary analysis, runtime evidence, and your finding history to any AI tool: Claude, Copilot, ChatGPT, or your own pipelines. Bring your AI. NowSecure provides the depth.
- Deep mobile evidence structured for AI reasoning. Not surface-level summaries.
- Works with any AI tool. No forced platform migration.
- All queries and actions log to the NowSecure audit trail. Your evidence stays in your environment.
06 MCP Verification Testing
Verify the finding before your team spends a sprint on it.
Before escalating to engineering, trigger a targeted verification test
via MCP. NowSecure runs it on a real device and returns a confirmed
result: exploitable, mitigated, or false positive.
- Trigger a targeted test on any finding from your AI tool, via MCP.
- Test runs on a real device and returns a confirmed exploitability result with runtime evidence.
- Escalate with evidence. Or close the finding as a false positive before it wastes a sprint.
07 MCP Auto-Remediation
From binary finding to a code fix. Without leaving your IDE.
NowSecure MCP sends the finding, evidence, and code path to your AI coding assistant. Claude or Copilot generates the patch from actual binary analysis. No ticket. Your developer reviews and commits from the IDE.
- Finding, evidence, and code path fed to your coding AI via MCP.
- Patch generated from binary analysis, not a generic remediation template.
- Developer reviews and commits to branch from the IDE. Audit trail maintained in NowSecure.
08 Portfolio Progress Reporting
Show whether your program is getting better. With numbers, not anecdotes.
Ask AI Chat directly. Get trend data, TTR, and recurrence rates, pulled directly from your live mobile risk data, on demand.
- Track findings by severity across any window: 30, 60, or 90 days.
- TTR, recurrence rates, mean time between new vulnerabilities. The KPIs your CISO actually asks about.
- Per-app drill-down to identify which apps drive the trend.
NowSecure Agentic AI
Detection is table stakes. Proof is
what your team actually needs.
NowSecure captures the binary artifact, code path, and runtime behavior behind every finding. That evidence forms a knowledge graph AI Chat reasons over, so answers come with proof, not just a finding ID.
Binary-level proof, not inference
Every finding links to decompiled code, data flow traces, and SDK call chains. When AI Chat calls a finding critical, the answer traces back to the artifact, not a CVSS score.
Runtime artifacts from real devices
Network traffic, storage reads, and SDK behaviors captured during live testing on real hardware. Actionable for your team; verifiable for auditors.
A knowledge graph your AI reasons over
AI Chat queries the full evidence corpus. Ask about an SDK and get every app, version, and associated runtime behaviors.
Evidence chain: from test to queryable knowledge
Binary Analysis
Runtime Testing
Finding + Evidence Artifact
Audit-Ready Record
Knowledge Graph
AI Chat + Agentic AI
Third-Party App Risk
Engineers need it to prioritize remediation. Auditors need it for compliance.
The NowSecure evidence layer is why AI Chat returns proof, not summaries.
Advantages
The model is table stakes. The harness is the advantage.
Not all mobile app assessment produces the same quality of truth. Traditional tools each observe a slice of the app. AI-only assessments predict behavior without observing it at all. Correlated, real-device testing is the only approach that produces evidence of what a shipped app actually does.
| Without NowSecure Agentic AI | With NowSecure Agentic AI |
|---|---|
|
No. SDK exposure: 1 to 2 days
Manual app-by-app checks, or enrichment tools that lack mobile binary accuracy. |
Yes. SDK exposure: minutes
Affected apps, versions, and severity, confirmed by binary evidence. |
|
No. Progress reporting: spreadsheet required
API exports, manual formatting, anecdotal summaries. No native trend view. |
Yes. Progress reporting: on demand
Trend data, TTR, and recurrence rates. Paste-ready for a QBR or leadership email. |
|
No. Suppression: too blunt or too slow
Per-app dismissal doesn't scale. Portfolio-level rules mask real risk. |
Yes. Suppression: portfolio-wide, evidence-scoped
One confirmed action. Scoped to the exact evidence pattern, never masking first-party code. |
|
No. Evidence: PDF attachments and manual review
Proof lives in reports, not queryable data. Auditors get a document, not a verifiable record. |
Yes. Evidence: structured, queryable, audit-ready
Every finding links to its evidence artifact. Auditors get a verifiable record, not a PDF. |
|
No. Authenticated flows: mostly untested
Scripted automation stops at login. |
Yes. Authenticated flows: covered
AI Navigator handles login, transactions, and dynamic UI states. |
|
No. Mobile security questions: plausible, unverifiable
Generic AI answers from training data. No basis for finding-specific answers. |
Yes. Mobile security questions: evidence-backed, specific
Answers pull from your binary analysis, runtime artifacts, and program history. Verifiable in one click. |
The difference: NowSecure AI reasons over binary analysis, real-device runtime evidence, and your finding history. Not CVE databases or SAST
heuristics. That's why answers are verifiable.
Benefits
What changes when your program is
built for the speed of modern attacks.
Attackers generate working exploits in hours. Your program needs complete
coverage and fast answers: binary analysis for what the app reveals, AI-
driven testing for what it hides.
Coverage no single method can match: Binary analysis catches vulnerabilities before the app runs. AI Navigator reaches the authenticated surface static tools miss. Together they satisfy NIST SP 800-163 as two separate required methodologies.
Exploit timelines are hours. Your response should be too: CVE surfaces Friday morning. By end of day: a ranked exposure list: apps, SDK versions, confirmed by binary evidence. Not a weekend of manual API queries.
Answers your compliance team can actually verify: Every answer links to its source artifact. Every action logs to the audit trail. SOC 2, PCI DSS, and FedRAMP require reproducible evidence, not AI summaries that vary between runs.
Analysts focused on risk that is real, not noise that is loud: Third-party SDK findings suppressed portfolio-wide in one action. Findings ranked by binary impact, not CVSS defaults. Your team works the vulnerabilities attackers would actually reach.
IT knows what apps do, not just what's installed: MDM tracks what's installed. NowSecure shows what each app does: what it sends, which permissions it claims, and what SDKs it bundles, for every app your workforce uses, including ones you didn't build.
Metrics that prove the program is working: TTR, recurrence rates, and severity trends pulled from your risk data. Ready for a QBR or leadership brief, with no manual exports required.
A realistic scenario
Critical CVE disclosed Friday. Exposure
ranked and triaged by end of day.
Every question fetches live data from the evidence corpus. Every answer links to the finding or
artifact it came from.
A high-severity SDK vulnerability drops.
Exploit tools can weaponize a public binary in under four hours.
Your team needs affected apps, SDK versions, and severity.
In minutes: a ranked exposure list, SDK versions confirmed by binary evidence, severity by platform and data sensitivity, and a suppression preview for already-mitigated findings.
How It Works
Live data. Evidence-linked answers.
Auditable actions.
Every question fetches live data from the evidence corpus. Every answer
links to the finding or artifact it came from.
Live data, always
Answers come from your current assessments with reach across your entire app portfolio putting the latest information at your fingertips.
Evidence-linked, one-click verification
Every answer links to its source artifact.
One-click verification, no manual report
navigation.
Write actions require confirmation
Explicit confirmation required before any
change is applied. All actions log to the
audit trail with evidence scope,
respecting your role and permission
structure.
Advantages
What would you need to trust AI in
your security program?
We put the hard questions on the table ourselves. Here's how NowSecure Agentic AI would run full page.
Accuracy over speed
Every answer traces back to the binary evidence and runtime artifact it came from. No claim reaches your team without a traceable evidence chain.
Agents assist. Humans decide.
Every write action requires explicit confirmation. Human oversight
isn't a checkbox. It's a design constraint on every capability we ship.
Binary-level proof, not inference
Every finding links to decompiled code, data flow traces, and SDK call chains. When AI Chat calls a finding critical, the answer traces back to the artifact, not a CVSS score.
Full auditability, built in
Every agent action is logged with evidence scope. The audit trail is
native to the workflow, not reconstructed after the fact.
Who It’s for
AI-era mobile risk isn’t owned by one team.
NowSecure Agentic AI gives every function accountable for mobile security the evidence and tooling to act.
Security Analysts and AppSec Teams
Answer complex portfolio questions in seconds. Clear third-party noise without masking real findings.
CISOs and Security Leaders
Stop relying on anecdotal updates. Get TTR, severity trends, and recurrence rates from your risk data, ready for board presentations and QBRs.
DevSecOps and Mobile Engineering
Catch vulnerable SDK dependencies before they ship. Engineers get the code path and evidence they need to act, not just a severity rating to argue over.
AI Governance and Compliance
Map AI components and data flows inside mobile apps. Audit-ready records built into the workflow.
IT and End User Computing
Risk intelligence on every app your workforce uses: permissions, SDK composition, data flows, and flagged findings. Visibility into the apps you use, not just the ones you build.
See and govern the AI inside your mobile apps
Get a clear view of the AI, SDKs, generated code, and data flows inside your apps, plus prioritized guidance your teams can use to reduce risk and move faster.
Resources
Mobile Application Risk Management Resources
