Mobile App Penetration Testing
Identify exploitable vulnerabilities in your iOS and Android apps - and the APIs behind them - before attackers do.
Do you need a mobile app penetration test?
A quick self-check. If several of these sound like you, it is worth a short conversation.
You likely need this if
- You publish an iOS or Android app that handles accounts, payments or personal data
- The app stores data on the device or communicates with backend APIs
- You operate in finance, health or another regulated sector with mobile exposure
- You have never assessed the app for reverse engineering or insecure local storage
Not sure where you land? A short scoping call will tell you plainly, including if you do not need this yet.
Book a scoping callWhat is mobile penetration testing?
A controlled, adversarial assessment of your iOS and Android apps, their local data, and the backend APIs they depend on - finding the exploitable flaws that automated scanners miss.
It is aligned with the OWASP Mobile Application Security Verification Standard (MASVS) and Mobile Top 10, then tailored to your platforms, data flows, and regulatory obligations.
Validate login, tokens (JWT), session handling, and biometric flows against real attacker techniques.
Test local storage, key management, and TLS so sensitive data cannot be extracted from the device.
Probe the backend APIs and deep links your app exposes for authorization and abuse flaws.
Produce documented findings for DORA, GDPR, NIS2, PCI-DSS, and the EU AI Act.
The mobile threat landscape
Mobile apps fail in ways web tests do not cover. We target the abuse paths unique to iOS and Android.
JWT manipulation, insecure deep links, and client-side logic abuse unique to mobile apps.
Sensitive data in logs or local storage, and hardcoded secrets baked into app binaries.
Vulnerable third-party SDKs, outdated dependencies, and exposed API keys.
DORA, GDPR, and sector fines for unvalidated controls - plus customer-trust and licensing risk.
Testing of mobile applications
Scope & Recon
Define platforms, builds, accounts, and APIs; map the app's attack surface and data flows.
Static Analysis (SAST)
Reverse and inspect the app binary for secrets, insecure storage, and embedded dependencies.
Dynamic Analysis (DAST)
Intercept traffic and exercise the running app: auth, session, deep links, and API abuse.
Exploit & Report
Safely prove impact, then deliver developer-ready findings with reproduction steps and fixes.
Every finding comes validated, with reproduction steps, remediation guidance, and the compliance documentation boards and regulators expect.
Learn the best security flow for your mobile application
Testing types
We tailor the method and knowledge level to your platforms, risk profile, and objectives.
Dynamic & static testing (DAST + SAST)
Static analysis reverses the binary for secrets and insecure patterns; dynamic analysis exercises the running app and its API traffic.
Black-box, gray-box, or full knowledge
Choose the knowledge level: zero for realism, partial for balance, or full source and credentials for the deepest coverage.
Use cases
Mobile banking & fintech
Validate account, payment, and transaction flows against takeover and fraud.
Biometric & auth bypass
Test liveness detection and biometric flows against presentation and replay attacks.
Embedded AI / LLM features
Probe in-app AI for prompt injection and sensitive-data leakage to third-party models.
Pre-release assurance
Test before each major release so flaws never reach production.
Reporting structure and metrics
Management Report
An executive overview of mobile risk, business impact, compliance alignment, and remediation priorities.
Technical Report
Developer-ready findings with affected components, request/response samples, proof-of-concept, and CVSS severity.
Verified vulnerabilities by severity, affected screens and endpoints, remediation status, time-to-remediation, and retest pass rate.
Quantify your mobile risk before hackers do
Find the auth, data-storage, and API gaps in your iOS and Android apps before attackers or auditors find them. Get a tailored scoping proposal in less than 48 hours.
Securing the mobile frontier
Healthcare & mHealth: patient data privacy & device integrity
The Problem: mHealth apps handle sensitive patient data across devices and integrations, under strict privacy duties.
The Outcome: We validate encryption, storage, authentication, and API security to protect patient data and support GDPR (and HIPAA where applicable).
E-Commerce & Retail: fraud prevention & transaction trust
The Problem: Shopping and payment apps are targeted for account takeover, payment manipulation, and API abuse.
The Outcome: We test authentication, payment logic, and API security to protect revenue and customer trust, supporting PCI-DSS.
Regulatory & compliance deep dive
Mobile testing produces the independent, documented evidence these frameworks expect for apps handling sensitive data and payments.
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DORA: Annual resilience testing and threat-led penetration testing (TLPT) for mobile banking and fintech apps.
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GDPR (Art. 32): Validates encryption, access control, and secure data handling as technical and organizational measures.
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NIS2: Regular, repeatable testing of mobile apps supporting essential and important services.
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PCI-DSS 4.0: Penetration testing and secure handling for apps that touch cardholder data.
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EU AI Act: Cybersecurity and robustness evidence for high-risk AI features embedded in mobile apps.
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HIPAA & HITECH: For apps serving US healthcare, we map controls to the required technical safeguards.
Mobile app penetration testing FAQ
NIS2 requires regular security assessments - a minimum of annual testing, plus additional evaluations after:
- Major infrastructure changes (app version updates, backend or cloud migrations).
- High-risk deployments (new features, payment integrations, biometric additions).
- Security incidents or detected breaches.
- Regulatory requirement changes.
- Third-party component updates (SDK replacements, library upgrades).
Apps in critical sectors (financial, healthcare, energy) should add quarterly vulnerability scanning and TLPT for critical entities. Post-deployment testing is mandatory before releasing major updates.
It validates encryption, access controls, and secure data handling - the technical evidence needed under GDPR Article 32 (security of processing). Testing specifically covers:
- Data encryption: TLS 1.2/1.3 for API communications, AES-256 for local storage.
- Access controls: OAuth 2.0/OIDC, session management, role-based permissions.
- Secure data handling: no sensitive data in logs, secure key storage (Android Keystore, iOS Secure Enclave), proper certificate validation.
- Privacy by design: data minimization, consent, and access/delete functionality.
Reports serve as technical and organizational measures (TOMs) documentation for audits.
Mobile pentesting identifies supply-chain weaknesses that could compromise the whole app stack:
- Malicious or vulnerable third-party SDKs (advertising, analytics, payment processors).
- Insecure dependencies - outdated libraries with known CVEs.
- API integration risks - weak backend authentication and API keys exposed in app binaries.
- Cloud service issues - misconfigured storage and over-broad IAM permissions.
- Certificate and key management - hardcoded secrets and weak validation.
Testing combines static analysis of app binaries to enumerate embedded dependencies with dynamic testing of third-party API integrations.
Yes. Advanced mobile pentesting simulates real-world threat-actor tactics against mobile banking and fintech apps, satisfying the intelligence-driven TLPT framework for critical financial entities. TLPT involves:
- Adversary simulation: realistic scenarios mimicking organized cybercrime or state-sponsored attackers.
- Intelligence-driven testing: threat intelligence informing the attack vectors used.
- Full-scope coverage: external, internal, and social-engineering paths.
- Business-impact validation: demonstrating real damage from successful exploits.
Mobile TLPT specifically exercises banking-fraud, account-takeover, payment-manipulation, and data-exfiltration scenarios.
We assess AI-integrated apps for emerging vulnerabilities:
- Prompt injection: malicious input manipulating AI behavior or extracting sensitive data.
- Data leakage to third-party LLM APIs: unencrypted transmission of personal or financial data to external AI services.
- Model manipulation: poisoning inputs that cause incorrect or biased outcomes.
- AI authentication bypass: weaknesses in voice or facial recognition.
- LLM API security: weak authentication, missing rate limiting, inadequate input validation.
This aligns embedded-AI security with EU AI Act expectations for high-risk systems.
We evaluate biometric authentication against AI-generated deepfakes and presentation attacks:
- Liveness detection: verifying input comes from a real person, not photos, videos, or 3D masks.
- Secure hardware integration: proper use of Android BiometricPrompt, iOS LocalAuthentication, and secure enclaves.
- Facial and voice bypass: testing against replays, synthetic voice, and deepfake video.
- Multi-factor and fallback: ensuring biometrics combine with other factors and that fallback paths are not weak password-only alternatives.
Testing includes presentation-attack simulations, replay demonstrations, and sensor-spoofing attempts to validate liveness and secure-hardware integration.