Introduction
Mobile applications represent one of the most underestimated attack surfaces in corporate security programs. While AppSec teams focus on APIs and web applications, the mobile clients consuming those same services carry their own layer of logic, local storage, network communication, and protection mechanisms that rarely receive the same attention.
YAGA approaches this scenario as an autonomous agent that understands mobile not as an extension of web pentesting, but as a distinct surface — with its own methodology, specific exploitation chains, and an orchestration architecture designed to handle both ecosystems simultaneously.
Two platforms, one unified methodology
Android and iOS have fundamentally different architectures. The sandbox mechanisms, permission models, package formats, native protection layers, and exposure points of each platform follow distinct logic. An agent that treats both the same way misses critical nuances of each ecosystem.
YAGA operates with platform-specialized modules, but with a unified orchestration layer that coordinates testing, correlates findings across both surfaces, and builds a consolidated risk view.
This matters because many enterprise applications have Android and iOS versions developed by different teams, with distinct implementations of the same business logic. Vulnerabilities that exist in one version frequently do not exist in the other, and comparing the two behaviors is a valuable source of findings.
YAGA's orchestration architecture for mobile
YAGA does not execute mobile tests in a sequential, linear fashion. The orchestration works in parallel layers that feed into each other:
Acquisition and decomposition layer
The agent receives the application package and performs structural decomposition before any active testing. The goal is to build a complete surface map: what components exist, how they are organized, what dependencies are declared, what permissions are requested, what endpoints are referenced in the code, and what protection mechanisms are present.
Static analysis layer
In parallel with the preparation phase for dynamic testing, YAGA analyzes the application's code and resources without executing it. This layer feeds the hypotheses that will guide active testing. Hardcoded keys, referenced internal endpoints, client-side validation logic, certificate configurations, local storage patterns, and cryptographic implementations are all evaluated in this phase.
Instrumentation and dynamic execution layer
With the application running in a controlled environment, the agent instruments its behavior in real time. Network traffic, storage operations, inter-process communication, OS API calls, and authentication flows are observed, intercepted, and analyzed.
Correlation and chaining layer
Findings from the three previous layers are correlated by YAGA's reasoning engine. A secret identified in static analysis is actively tested. A route identified in code is verified in real traffic. A suspicious storage pattern is validated by attempting access outside the expected context. The layers communicate with each other continuously.
Prioritization and delivery layer
Consolidated findings are classified by impact, chained when related, and delivered with complete evidence for human specialist validation.
Static analysis as the foundation of testing
Before executing any active action against the application, YAGA builds its knowledge model from package analysis.
On Android, this involves APK decomposition for access to the permissions manifest, exported components, network configurations, and compiled resources. The agent identifies which Activities, Services, BroadcastReceivers, and ContentProviders are exposed without adequate permission protection, mapping the attack surface for subsequent dynamic testing.
On iOS, IPA analysis exposes the application's binary structure, Info.plist configurations, registered URL schemes, App Transport Security settings, and included frameworks. The agent identifies implementation patterns and configurations that will be actively validated.
On both platforms, YAGA applies code analysis to identify patterns of interest: sensitive data stored in inadequate locations, cryptographic implementations that deviate from best practices, validation logic that runs exclusively on the client, and references to endpoints that do not appear in official documentation.
These static findings are not reported in isolation. They feed directly into the dynamic phase, guiding the agent toward the highest-interest points in the application's real-time behavior.
Dynamic execution and real-time instrumentation
With the application running, YAGA takes on the role of active observer. Real-time instrumentation allows the agent to capture what static analysis cannot reveal: how the application actually behaves, what it does with user data, how it manages sessions, and how it communicates with the backend.
Network traffic interception
All communication between the application and external servers is captured and analyzed. YAGA evaluates TLS implementation, certificate validation, transmitted headers, authentication tokens present in requests, and response consistency. Endpoints that appear only at runtime and were not identified in static analysis are automatically added to the surface map.
Local storage analysis
The agent monitors what the application persists to disk during execution: local databases, shared preferences, cache files, application logs, and temporary files. Sensitive data stored without adequate protection is recorded with evidence of the content and creation context.
Inter-component communication monitoring
On Android, inter-component communication via Intents is monitored by YAGA. The agent evaluates whether exported components receive data from untrusted sources and whether there is adequate validation of that input before processing. On iOS, custom URL schemes and deep links are tested for origin validation and parameter handling.
Runtime behavior monitoring
The agent captures exceptions, unhandled errors, unexpected state changes, and behavioral variations that indicate edge conditions not anticipated by the developer. These moments are frequently the richest for vulnerability identification.
Attack chaining: how YAGA builds exploitation paths
The difference between an isolated test and a real pentest lies in chaining. YAGA was built to think in terms of progression, not individual data points.
From weak client-side validation to control bypass
YAGA identifies that a given validation happens exclusively in the client code, with no corresponding check on the backend. The agent intercepts the request, modifies the parameters that would have been rejected locally, and observes how the server responds. When the backend processes without complaint, the chain is established: client control bypass with real impact on the server.
From undocumented endpoint to privileged access
During static analysis, YAGA identifies references to endpoints not listed on the initially mapped surface. In the dynamic phase, it confirms those endpoints respond in production. From there, the agent evaluates the authentication and authorization model for those endpoints and tests whether the absence of documentation corresponds to an absence of protection.
From exposed token to session hijacking
Authentication tokens identified in inadequate local storage or in application logs are actively tested by YAGA. The agent verifies the lifecycle of those tokens, their validity after logout, their sensitivity to reuse, and whether they can be used to access other users' resources.
From unvalidated deep link to unauthorized access
URL schemes and deep links that accept parameters without origin validation represent vectors for application flow manipulation. YAGA tests whether it is possible to induce the application to perform privileged actions or navigate to unintended states through crafted deep links.
From exported component to internal data access
On Android, exported components without permission protection are tested for their ability to receive commands from external applications and return data that should be private. YAGA simulates a malicious application interacting with those components and evaluates what can be accessed or executed.
Backend testing in the mobile context
One of the advantages of YAGA operating with visibility into the mobile client is that the agent can correlate the application's behavior with the APIs it consumes.
Endpoints that only appear in the mobile flow, specific parameters sent by the native client, device identification headers used for access control, and business logic implemented differently in the web client versus mobile are all points of interest that YAGA actively explores.
The agent simulates requests as if it were the legitimate mobile client, but with controlled variations: tokens from different sessions, out-of-range parameters, modified platform headers, and partially completed authentication flows. Each variation reveals information about how the backend validates the origin and context of requests.
This frequently exposes inconsistencies between what the mobile client assumes the server validates and what the server actually verifies. These inconsistencies are the fertile ground where access control flaws, IDOR, and business logic bypass tend to exist.
Black Box, Gray Box, or White Box: how YAGA adapts the methodology
The depth of a mobile pentest does not depend solely on the tools used. It depends on the level of access granted to the agent conducting the assessment. YAGA operates in all three modalities and adapts its orchestration methodology to the engagement context.
Black Box simulates the scenario of an external attacker with no prior knowledge of the application. YAGA operates exclusively on observable behavior: network traffic, public API surface, application responses, and OS interactions. It is the fastest modality to execute and the one that best replicates the perspective of a real adversary. Coverage of internal code and static analysis is naturally limited, but external behavior mapping and execution speed are its strengths.
Gray Box is the most common modality in enterprise engagements and represents the ideal balance between depth and operational viability. With access to credentials, API documentation, or the application binary without full source code, YAGA is able to deepen analysis into business logic, authentication flows, access control between profiles, and the behavior of specific endpoints. This is where the agent's chaining capability manifests most intensely.
White Box offers maximum coverage. With access to source code, application architecture, build environment, and full credentials, YAGA combines deep static analysis with instrumented dynamic execution. This modality is especially effective for identifying hardcoded secrets, validation logic implemented exclusively on the client, insecure configurations in the build pipeline, and dependencies with known vulnerabilities. The trade-off is longer execution time and the need for privileged access to the development environment.
Fig. 1 — Coverage by modality across 7 critical dimensions (mobile)
YAGA is designed to extract maximum coverage within the available access level. In Black Box, it leverages every external signal to build hypotheses. In Gray Box, it cross-references observed behavior with authentication context. In White Box, it combines what the code declares with what the application actually does at runtime. The methodology changes. The goal remains the same: map and exploit as much surface as possible before a real attacker does.
Cross-platform comparison as a discovery technique
YAGA runs parallel tests on Android and iOS when both versions are available, and the cross-platform comparison is itself a discovery technique.
Features implemented differently across the two versions reveal security inconsistencies. A validation present in iOS but absent in Android indicates that the protection is an implementation decision, not a backend guarantee. An endpoint accessible only through the Android version suggests that visibility control is handled on the client.
YAGA automatically cross-references findings from both platforms and identifies where behaviors diverge in ways that are security-relevant.
The human specialist in the mobile cycle
Mobile testing involves contexts that YAGA maps and prepares, but that require human judgment for full interpretation.
The real impact of an exported component depends on the ecosystem of applications installed on the target device. The criticality of locally stored data depends on the device's usage context. The exploitation of malicious deep links depends on distribution vectors that exist outside the agent's technical scope.
YAGA delivers the complete technical map, findings with evidence, and identified exploitation chains. The human specialist interprets the impact in the real business context, validates the most critical scenarios, and guides remediation recommendations.
Conclusion
Mobile applications are not smaller versions of web applications. They have their own attack surface, platform-specific behaviors, and exploitation chains that require dedicated methodology.
YAGA approaches this scenario with an orchestration architecture that combines static analysis, dynamic instrumentation, cross-platform correlation, and finding chaining in a continuous, autonomous cycle. The result is a mobile pentest program that keeps pace with development team delivery cadences, without sacrificing the technical depth the mobile ecosystem demands.
Talk to HackerSec and see how YAGA can cover your organization's mobile surface.