agent-runtime-validati…
Plans and evaluates bounded runtime tests of AI agents, tools, memory, hooks, approvals, and scope enforcement. Use when static…
Tracks Android and iOS application assessment coverage across packages, platform components, local storage, device behavior, WebViews, native code, network trust, and delegated backend APIs. Use when planning, conducting, reviewing, or handing over an authorized mobile app
Claude Code
$ npx -y skills add zero-lab-ai/skills --skill mobile-application-assessment --agent claude-code
Codex
$ npx skills add zero-lab-ai/skills --skill mobile-application-assessment -a codex -y
Cursor
$ npx skills add zero-lab-ai/skills --skill mobile-application-assessment -a cursor -y
Gemini CLI
$ npx skills add zero-lab-ai/skills --skill mobile-application-assessment -a gemini-cli -y
GitHub Copilot
$ npx skills add zero-lab-ai/skills --skill mobile-application-assessment -a github-copilot -y
OpenCode
$ npx skills add zero-lab-ai/skills --skill mobile-application-assessment -a opencode -y
Windsurf
$ npx skills add zero-lab-ai/skills --skill mobile-application-assessment -a windsurf -y
name: mobile-application-assessment description: "Tracks Android and iOS application assessment coverage across packages, platform components, local storage, device behavior, WebViews, native code, network trust, and delegated backend APIs. Use when planning, conducting, reviewing, or handing over an authorized mobile app penetration test." allowed-tools: Read Grep Glob
A decompiled indicator is not a runtime exploit, a rooted-device observation is not ordinary-device reachability, and one denied backend request is not an API authorization assessment. Keep each claim tied to its build, layer, method, and evidence.
1. Record the exact Android package or iOS bundle, platform, build kind, and SHA-256. Keep evidence from different builds in separate assessments. 2. State allowed action classes, structured test devices and accounts, in-scope origins, and constraints. Prevent production and third-party traffic at the test boundary when the app contains out-of-scope destinations. 3. Inventory one `application` surface per build, then add discovered storage, component, network endpoint, WebView, native library, cryptographic use, runtime defense, privacy channel, and backend API surfaces. 4. Give every surface an evidence reference and disposition. Static reachability supports a conditional exposure; runtime effect needs runtime evidence. 5. Cover all eight current MASVS categories for the application surface: storage, cryptography, authentication, network, platform interaction, code, resilience, and privacy. Add the categories derived for each detailed surface. 6. Record each case as `executed`, `planned`, `blocked`, `not-applicable`, or `delegated`. Only executed cases can claim a finding, no issue, or an inconclusive result. Preserve blockers and technical rationales. 7. Separate app, device, backend, and third-party evidence. A mobile client can expose an API route, but server-side authorization coverage belongs in the web assessment ledger. Preserve a bounded observed backend request as an executed case, then add a separate `delegated` case for the broader handoff. 8. Treat public identifiers, private secrets, exported components, client-side state, pinning, backup settings, root detection, and native code according to demonstrated impact. Their presence alone does not set severity. 9. Build category summaries from all recorded cases. Record the derived open case IDs so planned, blocked, delegated, and inconclusive work stays visible even when a confirmed finding takes precedence in the category claim.
threat model; it does not mean another ordinary app can read the data.
it in a lab is a test-enablement action, not itself a finding.
privilege before reporting exposure.
server authorization issue only when the server accepts the resulting action.
and whether enforcement is local or server-side.
reachability. Trace and test the effect before claiming impact.
Severity depends on data value, token lifetime, replay, device assumptions, and compensating server controls.
bypass proves tester capability, not a defect in the deployed control.
result applies only to that actor, target, operation, identifier, and backend.
authorization. Record an out-of-scope destination without contacting it.
blockers, and honest summaries across static and dynamic methods.
Portable, evidence-bound security skills for authorized defensive assessment, penetration testing, red teaming, detection engineering, purple teaming, and engagement operations. The collection contains 56 skills in 10 installable plugins from zero-lab.ai.
Plans and evaluates bounded runtime tests of AI agents, tools, memory, hooks, approvals, and scope enforcement. Use when static…
Reviews an MCP server's tool surface for tool poisoning, over-broad parameters, missing descriptions, and privilege escalation…
Maps identity, authority, instruction, data, memory, and approval propagation across agents and agent-to-agent handoffs. Use when…
Assesses whether direct, indirect, multi-turn, retrieved, or tool-mediated instructions can override an AI system's intended…
Maps cloud identity and authorization paths across AWS, Azure, GCP, and hybrid trust boundaries, separating proven access from…
Tracks embedded-device and firmware assessment coverage across exact units, acquisition methods, debug interfaces, stored…
Use for authorized security assessment of REST, GraphQL, WebSocket, or SOAP APIs, including discovery, authentication,…
Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys)…
Clean and finalize authorized natural-language text intended for readers by auditing suspicious invisible Unicode and rewriting…