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Analyzing Ios App Security With Objection

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mukul975
analyzing-ios-app-security-with-objection

Runtime iOS app security testing with Objection (Frida): inspect keychain and filesystem data, explore app internals at runtime, and validate/bypass client-side protections during authorized mobile assessments.

Overview

Publishermukul975
RepositoryAnthropic-Cybersecurity-Skills
Skill nameanalyzing-ios-app-security-with-objection
Stars
32.9K
Forks
4K
Bundled files
6
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mukul975 on GitHub. Read the source before you install it.

Installation

Install the Analyzing Ios App Security With Objection AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git /tmp/Anthropic-Cybersecurity-Skills
mkdir -p .claude/skills
cp -r /tmp/Anthropic-Cybersecurity-Skills/skills/analyzing-ios-app-security-with-objection .claude/skills/analyzing-ios-app-security-with-objection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyzing Ios App Security With Objection in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyzing Ios App Security With Objection on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyzing Ios App Security With Objection is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Analyzing iOS App Security with Objection

When to Use

Use this skill when:

  • Performing runtime security assessment of iOS applications during authorized penetration tests
  • Inspecting iOS keychain, filesystem, and memory for sensitive data exposure
  • Bypassing client-side security controls (SSL pinning, jailbreak detection) during security testing
  • Evaluating iOS app behavior at runtime without access to source code

Do not use this skill on production devices without explicit authorization -- Objection modifies app runtime behavior and may trigger security monitoring.

Prerequisites

  • Python 3.10+ with pip
  • Objection installed: pip install objection
  • Frida installed: pip install frida-tools
  • Target iOS device (jailbroken with Frida server, or non-jailbroken with repackaged IPA)
  • For non-jailbroken: objection patchipa to inject Frida gadget into IPA
  • macOS recommended for iOS testing (Xcode, ideviceinstaller)
  • USB connection to target device or network Frida server

Workflow

Step 1: Prepare the Testing Environment

For jailbroken devices:

bash
# Install Frida server on device via Cydia/Sileo
# SSH to device and start Frida server
ssh root@<device_ip> "/usr/sbin/frida-server -D"

# Verify Frida connectivity
frida-ps -U  # List processes on USB-connected device

For non-jailbroken devices (authorized testing):

bash
# Patch IPA with Frida gadget
objection patchipa --source target.ipa --codesign-signature "Apple Development: test@example.com"

# Install patched IPA
ideviceinstaller -i target-patched.ipa

Step 2: Attach Objection to Target App

bash
# Attach to running app by bundle ID
objection --gadget "com.target.app" explore

# Or spawn the app fresh
objection --gadget "com.target.app" explore --startup-command "ios hooking list classes"

Once attached, Objection provides an interactive REPL for runtime exploration.

Step 3: Assess Data Storage Security (MASVS-STORAGE)

bash
# Dump iOS Keychain items accessible to the app
ios keychain dump

# List files in app sandbox
ios plist cat Info.plist
env  # Show app environment paths

# Inspect NSUserDefaults for sensitive data
ios nsuserdefaults get

# List SQLite databases
sqlite connect app_data.db
sqlite execute query "SELECT * FROM credentials"

# Check for sensitive data in pasteboard
ios pasteboard monitor

Step 4: Evaluate Network Security (MASVS-NETWORK)

bash
# Disable SSL/TLS certificate pinning
ios sslpinning disable

# Verify pinning is bypassed by observing traffic in Burp Suite proxy
# Monitor network-related class method calls
ios hooking watch class NSURLSession
ios hooking watch class NSURLConnection

Step 5: Inspect Authentication and Authorization (MASVS-AUTH)

bash
# List all Objective-C classes
ios hooking list classes

# Search for authentication-related classes
ios hooking search classes Auth
ios hooking search classes Login
ios hooking search classes Token

# Hook authentication methods to observe parameters
ios hooking watch method "+[AuthManager validateToken:]" --dump-args --dump-return

# Monitor biometric authentication calls
ios hooking watch class LAContext

Step 6: Assess Binary Protections (MASVS-RESILIENCE)

bash
# Check jailbreak detection implementation
ios jailbreak disable

# Simulate jailbreak detection bypass
ios jailbreak simulate

# List loaded frameworks and libraries
memory list modules

# Search memory for sensitive strings
memory search "password" --string
memory search "api_key" --string
memory search "Bearer" --string

# Dump specific memory regions
memory dump all dump_output/

Step 7: Review Platform Interaction (MASVS-PLATFORM)

bash
# List URL schemes registered by the app
ios info binary
ios bundles list_frameworks

# Hook URL scheme handlers
ios hooking watch method "-[AppDelegate application:openURL:options:]" --dump-args

# Monitor clipboard access
ios pasteboard monitor

# Check for custom keyboard restrictions
ios hooking search classes UITextField

Key Concepts

TermDefinition
ObjectionRuntime mobile exploration toolkit built on Frida that provides pre-built scripts for common security testing tasks
Frida GadgetShared library injected into app process to enable Frida instrumentation without jailbreak
KeychainiOS secure credential storage system; Objection can dump items accessible to the target app's keychain access group
SSL Pinning BypassRuntime modification of certificate validation logic to allow proxy interception of HTTPS traffic
Method HookingIntercepting Objective-C/Swift method calls at runtime to observe arguments, return values, and modify behavior

Tools & Systems

  • Objection: High-level Frida-powered mobile security exploration toolkit with pre-built commands
  • Frida: Dynamic instrumentation framework providing JavaScript injection into native app processes
  • Frida-tools: CLI utilities for Frida including frida-ps, frida-trace, and frida-discover
  • ideviceinstaller: Cross-platform tool for installing/managing iOS apps via USB
  • Burp Suite: HTTP proxy for intercepting traffic after SSL pinning bypass

Common Pitfalls

  • App crashes on attach: Some apps implement Frida detection. Use --startup-command to hook anti-Frida checks early in the app lifecycle.
  • Keychain access scope: Objection can only dump keychain items within the app's access group. System keychain items require separate jailbreak-level tools.
  • Swift name mangling: Swift method names are mangled in the runtime. Use ios hooking list classes with grep to find demangled names.
  • Non-persistent changes: All Objection modifications are runtime-only and reset on app restart. Document findings immediately.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analyzing Ios App Security With Objection AI skill do?

Runtime iOS app security testing with Objection (Frida): inspect keychain and filesystem data, explore app internals at runtime, and validate/bypass client-side protections during authorized mobile assessments.

Why use Analyzing Ios App Security With Objection on TypingMind?

Because you install it once and use it with any model. Analyzing Ios App Security With Objection is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyzing Ios App Security With Objection in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-ios-app-security-with-objection. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analyzing Ios App Security With Objection?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyzing Ios App Security With Objection?

As many as you like. As long as a model supports skills, you can use Analyzing Ios App Security With Objection with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyzing Ios App Security With Objection AI skill free?

Yes. It is published on GitHub by mukul975 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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