Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add autohandai/community-skills --skill analyzing-ios-app-security-with-objectiongit clone --depth 1 https://github.com/autohandai/community-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/autohandai/community-skills/analyzing-ios-app-security-with-objection)<a href="https://agentmods.dev/skills/autohandai/community-skills/analyzing-ios-app-security-with-objection"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/analyzing-ios-app-security-with-objection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/autohandai/community-skills/analyzing-ios-app-security-with-objection"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/analyzing-ios-app-security-with-objection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.01468 |
| Opus 5.5 | $0.00040 | $0.00587 |
| Sonnet 5.5 | $0.00020 | $0.00294 |
| Haiku 4.5 | $0.00010 | $0.00147 |
Grade A, and why
analyzing-ios-app-security-with-objection scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to analyzing-ios-app-security-with-objection — 34 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 patchipato 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:
# 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):
# Patch IPA with Frida gadget
objection patchipa --source target.ipa --codesign-signature "Apple Development: [email protected]"
# Install patched IPA
ideviceinstaller -i target-patched.ipa
Step 2: Attach Objection to Target App
# 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)
# 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
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 187 lines · 99 tokens per session scan A d456f2ebcd5f
analyzing-ios-app-security-with-objection is a skill published in the GitHub repository autohandai/community-skills (13 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 99 tokens to every session and 1,468 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to analyzing-ios-app-security-with-objection, differing in 34 lines, and is treated as a copy.
analyzing-ios-app-security-with-objection compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| analyzing-ios-app-security-with-objectionautohandai/community-skills | Skill | 13 | 3mo ago | Apache-2.0 | A | 99 | Claude Code, Codex |
| analyzing-ios-app-security-with-objectionmukul975/Anthropic-Cybersecurity-Skills | Skill | 36k | 2mo ago | Apache-2.0 | A | 49 | Claude Code |
| analyzing-ios-app-security-with-objection26zl/cybersec-toolkit | Skill | 89 | 4d ago | MIT | A | 99 | Claude Code |
| analyzing-ios-app-security-with-objectionoyi77/1ai-skills | Skill | 17 | yesterday | MIT | A | 100 | Claude Code |
| analyzing-ios-app-security-with-objectionkillvxk/cybersecurity-skills-zh | Skill | 57 | 6mo ago | Apache-2.0 | A | 119 | Claude Code |
| analyzing-ios-app-security-with-objectionplurigrid/asi | Skill | 72 | 7d ago | MIT | A | 99 | Claude Code |
| analyzing-ios-app-security-with-objectionbalsm-health/Balsm-AI | Skill | 3 | 26d ago | none | A | 49 | Claude Code |