vesper: iOS reverse engineering platform: MCP tools and agent skills for runtime inspection, automation, decryption

by Wtrwx · MCP Server · ★ 54

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars54
Forks7
LanguageJavaScript
CategoryMCP Server
LicenseMIT
Quality Score66/100
Last Updated2026-10-25
Created2026-10-22
Platformsmcp, node
Est. Tokens~17k

About vesper

vesper English | 简体中文 An iOS reverse engineering platform combining MCP primitives and agent skills for runtime inspection, app automation, decryption, debugging and tweak development. vesper connects an MCP client to SSH, Frida, and an optional licensed IDA installation. Inspect UIKit views, explore Objective-C metadata, trace method calls, and build app-scoped tweaks through structured tools.

Compatible Skills

These tools work well together with vesper for enhanced workflows:

  • AETHER — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)
  • REx-skill — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)
  • sentinel-reverse — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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