agent-runtime-validati…
Plans and evaluates bounded runtime tests of AI agents, tools, memory, hooks, approvals, and scope enforcement. Use when static…
Maps lateral movement candidates and multi-hop routes across Windows, Linux, network, DevOps, and cloud environments while separating transport reachability, authentication material, destination rights, authorization, execution proof, resulting access, detection exposure, and
Claude Code
$ npx -y skills add zero-lab-ai/skills --skill lateral-movement-map --agent claude-code
Codex
$ npx skills add zero-lab-ai/skills --skill lateral-movement-map -a codex -y
Cursor
$ npx skills add zero-lab-ai/skills --skill lateral-movement-map -a cursor -y
Gemini CLI
$ npx skills add zero-lab-ai/skills --skill lateral-movement-map -a gemini-cli -y
GitHub Copilot
$ npx skills add zero-lab-ai/skills --skill lateral-movement-map -a github-copilot -y
OpenCode
$ npx skills add zero-lab-ai/skills --skill lateral-movement-map -a opencode -y
Windsurf
$ npx skills add zero-lab-ai/skills --skill lateral-movement-map -a windsurf -y
name: lateral-movement-map description: "Maps lateral movement candidates and multi-hop routes across Windows, Linux, network, DevOps, and cloud environments while separating transport reachability, authentication material, destination rights, authorization, execution proof, resulting access, detection exposure, and cleanup. Use when planning or documenting remote access paths after a foothold." allowed-tools: Read Grep Glob
Lateral movement is a chain of claims. A listening service does not prove reachability. Reachability does not prove authentication. Authentication does not prove destination rights. A successful hop does not prove the next hop.
This skill maps supplied facts and bounded validation plans. It does not supply commands, recover or replay secrets, contact systems, create remote processes, deploy tunnels, establish persistence, or authorize activity.
1. Record the objective, assessment window, supplied operational-signal ceiling or null, written authorization, permitted sources, destinations, material references, and action classes. Preserve explicit prohibitions. 2. Inventory assets and current access contexts. Mark a context `observed` only when evidence establishes that identity and privilege on that asset. Projected contexts identify the exact prior movement that would create them. 3. Inventory authentication material as references only. Record type, identity, state, source, permitted use, limitations, and evidence. Never place a raw password, hash, ticket, token, key, or secret in the map. 4. Separate reachability, destination rights, administrative baseline, and telemetry health. Each answers a different question and needs its own evidence. 5. Build each candidate hop from one source context to one destination. Link the material, transport, required right, authorization, expected defensive artifacts, operational signal, stop conditions, and cleanup obligation. 6. Derive hop state. Known deny or prohibition is `blocked`; missing prerequisites are `unknown`; complete prerequisites behind a consent gate are `approval-required`; authorized complete prerequisites are `authorized`. Only execution evidence can produce `executed` or `failed`. 7. Record resulting access narrowly. Planned access is `projected`; achieved identity and privilege are `observed` only after cited execution evidence. 8. Assemble ordered routes. The destination of one hop must be the source of the next, and the next source context must be derived from the preceding hop. Route state is limited by its weakest hop. 9. Select the smallest authorized validation that advances the objective within the signal ceiling. Unknown sensor health increases uncertainty; it does not make an action quiet. 10. Cover every required planning and evidence category. Record blocked or unknown work explicitly, then complete the assessment.
and privilege paths before operational movement.
this skill accepts references and allowed-use state only.
transition here only when it participates in the movement campaign.
detector, rather than reach an engagement objective.
authentication, rights, policy, or resulting privilege.
authorized material cannot support a movement hop.
are destination and capability specific.
baseline, sensors, target sensitivity, and actual implementation.
and the next hop needs a real or explicitly projected source context.
query window, silence is not an outcome.
the state-changing hop.
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…