Mobile Malware Static Analysis — Module ConclusionThis episode serves as a knowledge check and consolidation of the basic static-analysis methodology covered across both iOS and Android. The emphasis is not on learning one particular tool, but on developing a repeatable investigation process.1. iOS Static AnalysisSeveral important tools and artifacts are reinforced.class-dumpUsed primarily to extract and inspect Objective-C class information from compiled iOS binaries.It can help reveal:
Classes
Methods
Interfaces
Application structure
This gives the analyst an initial picture of how an application is organized.otoolA versatile Mach-O inspection utility.For example:otool -L application can display the application's linked dynamic libraries.Other otool options can provide additional information about the Mach-O binary, making it an important first-stage reverse-engineering tool.2. Finding the iOS ExecutableThe Info.plist contains important application metadata.One useful investigation task is determining the executable associated with the application.Conceptually:IPA ↓ Payload/ ↓ Application.app/ ↓ Info.plist ↓ CFBundleExecutable ↓ Executable Name The CFBundleExecutable value identifies the main executable associated with the application bundle.3. Android Static AnalysisOn Android, the equivalent early-stage artifact is the AndroidManifest.xml.apktool is commonly used to decode an APK so that its manifest and resources can be examined.For example:apktool d application.apk -o decoded_app The resulting manifest can reveal:
Activities
Services
Broadcast receivers
Content providers
Permissions
Intent filters
4. Intent FiltersA particularly important Android concept is the intent-filter.Intent filters describe the types of intents that an Android component can respond to.For example, a receiver may declare an intent associated with a particular system event.This makes intent filters useful during malware analysis because they help answer:What events is this application designed to react to?For example:Intent ↓ Matching Intent Filter ↓ Android Component ↓ Application Logic This is especially important when investigating applications that react automatically to events such as incoming messages, boot events, connectivity changes, or other system broadcasts.5. The Structured Malware-Analysis MethodologyOne of the most important lessons from the entire module is that malware analysis should follow a structured methodology rather than randomly examining files and tools.A strong workflow is:1. Define the objective ↓ 2. Preserve the sample ↓ 3. Calculate hashes ↓ 4. Search online intelligence resources ↓ 5. Identify platform and file type ↓ 6. Examine metadata ↓ 7. Analyze permissions / capabilities ↓ 8. Inspect code and binaries ↓ 9. Identify suspicious artifacts ↓ 10. Build a behavioral hypothesis ↓ 11. Validate through deeper analysis Why define the objective first?Without a specific objective, malware analysis can become extremely inefficient.For example, different questions require different investigations:
What does this application do?
Does it communicate with a C2 server?
Does it steal SMS messages?
What persistence mechanism does it use?
What information does it collect?
The objective determines which artifacts deserve priority.6. Hashing as an Early Triage TechniqueHashing provides a convenient way to identify a malware sample.Common hashes include:md5sum sample.apk sha256sum sample.apk The hash can then be searched in authorized threat-intelligence databases.This can potentially reveal:
Previous detections
Malware family classifications
Existing research
Known indicators
Previous submissions
However:No detection does not equal no malware.A previously unseen sample may have no reputation whatsoever.7. Using Online ResourcesOnline intelligence sources can significantly accelerate analysis.Instead of spending hours investigating an artifact that has already been studied, researchers can search existing intelligence for:
File hashes
Domains
IP addresses
URLs
Malware families
Known samples
Decompiled artifacts
The important skill is knowing when to leverage existing intelligence and when to perform your own analysis.8. iOS vs. Android — Quick ComparisonAreaiOSAndroidApplication packageIPAAPKMain metadataInfo.plistAndroidManifest.xmlExecutableMach-ODEX/native librariesKey toolotoolapktoolClass inspectionclass-dumpDEX decompilersComponent analysisApp metadata/runtimeActivities, Services, Receivers, ProvidersEvent handlingiOS frameworksIntent / Intent FilterPrimary static-analysis goalUnderstand binary structureUnderstand package structure and application logic9. The Bigger PictureThe module has essentially established a complete basic static-analysis foundation for both mobile platforms.iOSIPA ↓ Info.plist ↓ Executable ↓ Mach-O Analysis ↓ class-dump / otool ↓ Strings / Symbols / Libraries ↓ Behavioral Hypothesis AndroidAPK ↓ AndroidManifest.xml ↓ Permissions / Components ↓ Intent Filters ↓ DEX ↓ Decompilation ↓ Application Logic ↓ Behavioral Hypothesis The two platforms use different technologies, but the investigative mindset remains the same.Key Takeaways
class-dump → useful for examining Objective-C class information in iOS binaries.
otool → useful for inspecting Mach-O binaries and linked libraries.
Info.plist → contains important iOS application metadata, including the executable name.
apktool → decodes Android APK resources and manifests for analysis.
AndroidManifest.xml → reveals permissions and application components.
intent-filter → identifies the types of intents to which Android components can respond.
Hashing → provides an efficient method for sample identification and threat-intelligence searches.
Online intelligence → can accelerate investigations by providing existing knowledge about samples and indicators.
Clearly defined objectives → keep malware investigations focused and efficient.
Golden ConceptGood malware analysis is not simply knowing how to use forensic and reverse-engineering tools. It is knowing what question you are trying to answer, which evidence can answer it, and how to systematically connect that evidence into a defensible behavioral hypothesis.