agent-runtime-validati…
Plans and evaluates bounded runtime tests of AI agents, tools, memory, hooks, approvals, and scope enforcement. Use when static…
Measures local Windows and Linux endpoint persistence exposure from supplied evidence by deriving consumer, authority, lifecycle, prevention, context, telemetry, and coverage state. Use when auditing durable-execution risk without creating, activating, testing, ranking, or
Claude Code
$ npx -y skills add zero-lab-ai/skills --skill persistence-surface-assessment --agent claude-code
Codex
$ npx skills add zero-lab-ai/skills --skill persistence-surface-assessment -a codex -y
Cursor
$ npx skills add zero-lab-ai/skills --skill persistence-surface-assessment -a cursor -y
Gemini CLI
$ npx skills add zero-lab-ai/skills --skill persistence-surface-assessment -a gemini-cli -y
GitHub Copilot
$ npx skills add zero-lab-ai/skills --skill persistence-surface-assessment -a github-copilot -y
OpenCode
$ npx skills add zero-lab-ai/skills --skill persistence-surface-assessment -a opencode -y
Windsurf
$ npx skills add zero-lab-ai/skills --skill persistence-surface-assessment -a windsurf -y
name: persistence-surface-assessment description: "Measures local Windows and Linux endpoint persistence exposure from supplied evidence by deriving consumer, authority, lifecycle, prevention, context, telemetry, and coverage state. Use when auditing durable-execution risk without creating, activating, testing, ranking, or removing a persistence mechanism." allowed-tools: Read Grep Glob
Persistence exposure is not proof that persistence exists, executed, survived, was approved, or is malicious. Measure whether current supplied evidence closes the prerequisites for durable local execution while keeping every assessed surface opaque.
This skill is read-only and local-endpoint only. It does not enumerate a live host, reveal concrete locations, create or rank mechanisms, execute triggers, change configuration, test survival, clean artifacts, evade telemetry, inspect directory or cloud control planes, handle credentials, or assess kernel, bootkit, firmware, or hidden-object integrity.
1. Record exact written authority, scoped Windows or Linux assets, the supplied-evidence boundary, assessment time, collection windows, and prohibited active actions. 2. Normalize evidence with one asset, source group, opaque locator, digest status, observed time or bounded window, validity, provenance, limitations, and custody. Do not invent precision, names, ownership, hashes, or independence. 3. Cover every required platform surface. Each asset-category cell is `assessed`, `blocked`, or `not-applicable`; one empty surface never proves asset-wide absence. 4. Represent each existing consumer only by an opaque surface reference and closed category. Keep consumer availability, effective change authority, lifecycle survival, preventive control, execution-context relation, and telemetry state as separate evidence-backed facts. 5. Require current same-asset evidence for every non-unknown fact. Evidence from one source group remains one vantage even when several parsers report it. Stale, unavailable, or disposed material cannot prove current exposure. 6. Keep execution separate from exposure. Execution needs an exact configuration-to-artifact-to- event binding in a compatible window; an existing registration is not compromise or success. 7. Mark higher-context exposure for a privilege-escalation handoff without claiming elevation. If host-view integrity is suspect, derive `inconclusive` and require rootkit triage. 8. Create only closed defensive remediation objectives and owned specialist handoffs. Rank fix urgency, never mechanism usefulness. A fix is complete only from post-change evidence. 9. Derive all surface states, coverage, priorities, and summaries. Preserve blocked, unknown, conditional, conflicting, and not-applicable work rather than converting silence to clean.
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…