Mobile app pentesting, binary to backend.
AI penetration testing for iOS and Android mobile applications, covering binary analysis, runtime exploits, insecure storage, certificate pinning, inter-process communication, and the backend APIs mobile apps depend on.iOS and Android apps at equal depth. We reverse-engineer the binary, exploit the runtime, test insecure storage and IPC, and chain through to the backend APIs behind the app. A senior pentester reviews every finding.
Mobile is three attack surfaces in one.
A mobile app is a binary on a device, a runtime in hostile hands, and a client to a backend API. Each is its own attack surface. Most pentests only cover one or two.
Secrets that shouldn't have shipped
Hardcoded keys, endpoints, feature flags, and debug strings. We reverse-engineer IPA and APK files to find what you didn't mean to ship. The AI extracts and classifies; the human tells you which ones actually matter.
Your app runs on the attacker's device
Cert pinning bypass, root/jailbreak detection that doesn't detect anything, insecure keychain items, exported activities on Android. Frida and Objection are our baseline. If it runs on the phone, we can manipulate it.
Most mobile bugs live on the server
Your app is a client. The interesting flaws are in the APIs it talks to, often with weak auth because nobody's supposed to see them. We test those too, same engagement.
What we test on mobile apps.
iOS and Android. Binary, runtime, backend. Every engagement, both platforms.
What's in the app
- Hardcoded secrets / keys
- Sensitive strings & endpoints
- Insecure third-party SDKs
- Symbol / obfuscation review
- Debug flags in release builds
- Signing & entitlement issues
Live on device
- Certificate pinning bypass
- Jailbreak / root detection
- Frida / Objection attacks
- Anti-debug checks
- Method swizzling / hooking
- Screenshot / overlay attacks
Data on the device
- Insecure Keychain / Keystore
- Plaintext in SharedPreferences
- Exported Android activities
- Broadcast receiver abuse
- URL scheme hijacking
- iOS pasteboard leakage
What the app talks to
- Unauthenticated endpoints
- IDOR on user resources
- Mass assignment
- Replay & session attacks
- Push-notification abuse
- Token-binding flaws
Example findings from this surface.
Illustrative examples of real vulnerability classes on this attack surface. Anonymized, but every one based on patterns our pentesters encounter repeatedly.
A production API key was embedded in the iOS binary. Extracted via `strings` in under a minute. The key had full read/write access to the customer database.
Certificate pinning was implemented only for the main domain, not for the analytics subdomain which handled auth redirects. A proxy on analytics domain MITM'd the login flow and captured tokens.
A deep-link activity was exported without permission checks. A malicious app on the same device could launch it with a crafted intent and read the returned auth token from the result.
Auth tokens were stored in Keychain with kSecAttrAccessibleAlways, meaning they could be extracted from a physical device without a passcode. A lost phone leaks the user's session.
// illustrative examples · not real customer engagements
Ship faster than your pentesters? Let's fix that.
Tell us what you ship and we'll scope a pilot on this surface. The AI and the reviewer take it from there.
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