Security Testing for Mobile Apps: From Vulnerability Scanning to Penetration Testing

In 2025, mobile security testing isn’t optional — it’s essential. Apps are evolving fast, but so are the threats. From handling sensitive user data to enabling real-time commerce, mobile apps have become high-value targets for attackers.

In this blog, we’ll break down the layers of mobile app security testing, real-world challenges unique to mobile environments, and where tools like Frida and MobSF fit into modern workflows. While Quash doesn’t focus on security testing, our mission to help teams shift left means we care deeply about integrating secure practices early in your dev cycle.

What Makes Mobile Security Testing So Challenging?

Device Fragmentation

• Android has thousands of device combinations, chipsets, GPUs, and OS skins.

• iOS is more consistent but still deals with legacy devices and inconsistent updates.

An app might be safe on Pixel 8 but vulnerable on a low-end Samsung or jailbroken iPhone.

Unreliable Network Conditions

• Users switch between Wi-Fi and 4G/5G frequently, often mid-session.

• This opens up attack vectors like man-in-the-middle attacks on public Wi-Fi.

• Weak encryption or insecure APIs can be exposed during these transitions.

Client-Side Data Exposure

• Mobile apps store data in SQLite, shared preferences, or local caches.

• Improper encryption allows direct access via rooted or jailbroken devices.

• As highlighted by the OWASP Mobile Top 10, insecure data storage remains a critical risk.

Inconsistent Update Policies

• Android users might run OS versions from three or more years ago.

• Even if your app is secure, it might sit on top of a vulnerable OS.

The Five Layers of Mobile Security Testing

Security isn’t a single scanner — it’s a layered defense. Here's how the most effective security testing for mobile apps is structured:

Vulnerability Scanning

Tools like MobSF scan your APK/IPA for:

• Outdated libraries with known CVEs

• Exposed components like WebViews or debug logs

It’s the easiest way to catch low-hanging fruit early.

Static Code Analysis

Think of this as a security-aware code review:

• Finds hardcoded API keys, insecure API calls, and cryptographic flaws.

• SonarQube and Checkmarx integrate well into CI/CD workflows.

• Helps enforce security policies with every pull request, part of shifting security left.

Dynamic Analysis: Behavior in the Wild

Dynamic App Security Testing (DAST) observes real behavior:

• Burp Suite intercepts live API traffic to find data leakage.

• Frida allows runtime hooking to inspect encryption, authentication, or session flows.

Example: Runtime Hooking with Frida

import frida

def on_message(message, data):
    print("[+] Message:", message)

session = frida.get_usb_device().attach("com.example.myapp")
script = session.create_script("""
    Java.perform(function() {
        var Cipher = Java.use('javax.crypto.Cipher');
        Cipher.doFinal.overload('[B').implementation = function(data) {
            console.log("Intercepted doFinal call");
            return this.doFinal(data);
        };
    });
""")
script.on('message', on_message)
script.load()

Here, we’re hooking into Cipher.doFinal() – a cryptographic method to see if sensitive data is securely encrypted. This same approach can be used by attackers, so understanding how tools like Frida mobile testing work is critical for developers.

Penetration Testing for Mobile Apps

Pen testing goes deeper than automated scans. It's about thinking like a real attacker:

• Reverse engineering APKs to extract secrets or logic.

• Tampering with API payloads to bypass authentication (e.g., changing user_id=1 to user_id=2).

• Launching man-in-the-middle attacks to test for proper HTTPS enforcement.

• Using Frida or runtime exploits to bypass client-side checks.

These are time-consuming but essential, especially for fintech, health, and public-facing apps.

How AI Supports (But Doesn’t Replace) Mobile Security Testing

AI is changing the game, especially for repetitive or pattern-based tasks:

• Pattern recognition: Catch common flaws using trained models.

• Behavior analysis: Detect anomalies in automated test sessions.

• Contextual fixes: Suggest improvements based on surrounding code.

• CI/CD integration: Re-run known exploit patterns to validate security in pipelines.

However:

• AI cannot think like an attacker.

• AI cannot replace manual penetration testing, especially for business logic vulnerabilities.

Best Practices for Mobile App Security Testing

• Shift left testing: Integrate security checks from the start of development.

• Automate vulnerability scanning and static analysis in CI/CD.

• Run penetration tests regularly, particularly before major releases.

• Train developers to identify and prevent security flaws.

• Avoid relying solely on obfuscation, secure the data and logic end-to-end.

Final Takeaways

Security testing for mobile apps is a multi-layered strategy, not a single step. From vulnerability scanning to pen testing, every layer contributes to a robust defense. Tools like Frida, MobSF, and RASP platforms provide the visibility and control modern teams need.

At Quash, while we specialize in functional and regression testing, we actively support teams in shifting left and embedding security as a core part of the testing process. When security becomes part of your workflow, it becomes a strength, not an afterthought.

Further Reading & Resources

• A Complete Guide to Types of System Testing

• Mobile App Testing in the Age of AI

Want to integrate security best practices into your mobile testing pipeline? Let’s talk!