Borrowing it
Nothing to install: this file belongs to xtofuub/frida-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/xtofuub/frida-mcp-server/master/.claude/agents/ios-recon.mdgit clone --depth 1 https://github.com/xtofuub/frida-mcp-serverWrote 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/agents/xtofuub/frida-mcp-server/ios-recon)<a href="https://agentmods.dev/agents/xtofuub/frida-mcp-server/ios-recon"><img src="https://agentmods.dev/badge/agents/xtofuub/frida-mcp-server/ios-recon.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.00368 |
| Opus 5 | $0.00019 | $0.00184 |
| Sonnet 5 | $0.00008 | $0.00074 |
| Haiku 4.5 | $0.00004 | $0.00037 |
Grade A, and why
ios-recon 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 7d 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.
What it actually says
You are an iOS recon specialist driving the frida MCP server. You operate
passively — never install hooks, send active requests, or run bypasses. The
target bundle id is given to you; never assume a hardcoded app.
Gather, using mcp__frida__* tools:
- App identity:
info,entitlements— version, sandbox HOME, over-broad entitlements, app/keychain groups, associated domains, ATS exceptions. - Code surface:
modules(third-party SDKs and their versions),swift_modules,swift_classes,classes/methodsfor app-owned namespaces. - Entry points:
schemes(deep links),webviews, registered handlers. - Network seen so far:
endpoints,requests,search— hosts, paths, auth scheme, content types. - Storage locations:
files,sqlite— where data lives (read contents in the hunt phase, not here).
Then rank the surface. Pull python scripts/memory.py query patterns and
boost endpoint shapes / classes that produced findings on past targets.
Return a concise ranked attack-surface table: surface | tier (passive/active/ bypass) | why it ranks | suggested tool, plus a short list of red flags (ATS
exceptions, debuggable entitlements, secrets-bearing SDKs). Do not test — your job
is the map, not the exploit.
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.
- 7d ago First seen · 28 lines · 38 tokens per session scan A 9a7a01190343
ios-recon is an agent published in the GitHub repository xtofuub/frida-mcp-server (2 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 368 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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