MAST security testing is the practice of analyzing a mobile application for security flaws using a mix of static, dynamic, and interactive techniques, tailored to the specific risks of iOS and Android. MAST stands for Mobile Application Security Testing, and it exists because web-focused tools miss most of what makes a mobile app risky: on-device data storage, platform permission models, insecure interprocess communication, and binaries that ship straight to an attacker's own device. This guide explains how the pieces fit and how to run a testing program that produces findings you can act on.
Why mobile needs its own discipline
The defining fact of mobile security is that the attacker owns the runtime. Once an app is installed, the user, who may be hostile, controls the device, the OS, and the network path. They can jailbreak or root the device, attach a debugger, intercept traffic, and read the app's local storage. That changes the threat model completely compared to a server-side application where you control the environment.
MAST security testing responds to this by inspecting both what the app contains and how it behaves under adversarial conditions. The reference framework is the OWASP Mobile Application Security Verification Standard (MASVS), paired with the Mobile Application Security Testing Guide (MASTG), which together give you a checklist of what to verify and concrete procedures for verifying it.
The three core techniques
MAST is not one tool. It is a combination of analysis methods, each catching different classes of defect.
Static analysis (MAST-SAST) examines the app without running it. For a mobile app that means decompiling the APK or IPA and inspecting code, resources, and the manifest. Static analysis is good at finding hardcoded secrets, insecure cryptographic calls, exported components, and dangerous permission declarations. It is fast and runs early in the pipeline, but it produces false positives because it cannot see runtime context.
Dynamic analysis (MAST-DAST) runs the app on a device or emulator and observes it in motion. This is where you catch insecure network traffic, weak TLS validation, data written to unprotected storage, and authentication that can be bypassed. Dynamic testing needs instrumentation: a proxy such as mitmproxy or Burp for traffic, and often a rooted or jailbroken test device.
Interactive analysis (MAST-IAST) instruments the running app to trace data flow from inside, combining the code visibility of static analysis with the runtime accuracy of dynamic analysis. Frida is the workhorse here, letting you hook functions, bypass certificate pinning in a test build, and watch how sensitive data moves through the app.
A workflow that produces real findings
A repeatable MAST engagement usually runs in this order:
- Reconnaissance. Pull the app package and identify the frameworks, SDKs, and third-party libraries it bundles. This is also software composition analysis: a mobile app is a dependency tree like any other, and a vulnerable analytics or ad SDK is a common weak point. Our overview of software composition analysis applies directly to the libraries a mobile binary ships.
- Static pass. Decompile and scan for hardcoded keys, insecure storage APIs, exported activities and content providers, debuggable flags, and weak crypto.
- Traffic analysis. Proxy the app and confirm every sensitive endpoint uses TLS, validates certificates, and does not leak tokens in URLs or logs.
- Storage and platform checks. Inspect what the app writes to local databases, shared preferences, and the keychain or keystore, and whether that data is encrypted at rest.
- Runtime manipulation. Use interactive instrumentation to test authentication logic, jailbreak or root detection, and certificate pinning under active tampering.
The output should map back to MASVS control groups so a reader can see coverage, not just a pile of individual issues.
Common findings worth naming
Across mobile assessments, a handful of issues recur often enough to check for first:
- Secrets embedded in the binary. Decompilation is trivial, so an API key in the app is a public key. Look for
stringsoutput and hardcoded tokens in resource files. - Sensitive data in insecure storage. Tokens or PII written to a world-readable file or an unencrypted SQLite database.
- Weak or absent certificate validation, which turns any network into a man-in-the-middle opportunity.
- Over-broad permissions and exported components that expose functionality to other apps on the device.
- Insufficient jailbreak or root detection on apps that handle payments or regulated data.
Naming the class matters more than chasing every instance, because the fix for a class of defect is usually one code change applied consistently.
Fitting MAST into a pipeline
Manual assessments are thorough but slow, so mature teams automate the repeatable parts. Static analysis and dependency scanning run on every build in CI, gating merges when a critical issue appears. Dynamic and interactive testing run on a schedule or before a release, because they need instrumented devices and are harder to fully automate.
The goal is the same shift-left principle that governs web security: catch the cheap-to-fix issues early with automation, and reserve human testing for the logic flaws a scanner cannot reason about. If your web pipeline already runs dynamic application security testing, MAST is the mobile-specific extension of that same idea, adapted for a runtime you do not control.
Where MAST tools fall short
No scanner understands your app's business logic. A tool can tell you a token is stored insecurely; it cannot tell you that your password-reset flow lets one user reset another's account. It can confirm TLS is used; it cannot judge whether your session-expiry policy is sane. Treat automated MAST results as the floor, not the ceiling, and budget for manual review of authentication, authorization, and payment flows on any app that matters.
FAQ
What does MAST stand for?
MAST stands for Mobile Application Security Testing. It covers the static, dynamic, and interactive techniques used to find security flaws in iOS and Android applications.
How is MAST different from web application testing?
The key difference is that in mobile the attacker controls the device and runtime. That makes on-device storage, binary analysis, certificate pinning, and platform permission models central concerns that web testing largely ignores.
What standard should a MAST program follow?
The OWASP Mobile Application Security Verification Standard (MASVS) defines what to verify, and the companion MASTG provides the procedures. Mapping findings to MASVS control groups keeps coverage honest.
Can MAST be fully automated?
Static analysis and dependency scanning automate well and belong in CI. Dynamic and interactive testing need instrumented devices and still benefit from manual review, especially for authentication and business-logic flaws.