Zonefoundry Local Sonos

• Outcome: Review
• Latest audit: Sep 14, 2026 · 8:51 PM UTC
• Version: 1.5.9

Overview

The skill mostly matches local Sonos control, but it gives the local zf runtime too much authority to update itself, replace instructions, and drive commands automatically.

Install only if you are comfortable letting a local ZoneFoundry binary control Sonos and update itself. Before using it, require confirmation for runtime updates, reject arbitrary `nextCommand` strings unless they match a reviewed zf command, do not let `zf skill show` replace reviewed skill instructions, and ask before pruning or deleting queue items.

A.I.G

Vulnerability Patterns

• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• Insecure Dependencies: Introduces malicious components through unsafe dependency sources
• Agent Memory Poisoning: Writes attacker-controlled rules into memory that affect later sessions
• Remote Payload Retrieval and Execution: Fetches external code whose behavior can change after review
• Embedded Malicious Code: Ships malicious scripts inside the skill and executes them locally

Findings (3)

T01 · Skill Instruction Hijacking

Error

• Location: SKILL.md:43

Finding

Unvalidated Execution of Runtime-Provided Commands

Content

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Vulnerability Details

File Location: SKILL.md:43; related instruction in agents/openai.yaml:56
Vulnerability Type: T01: Skill Instruction Hijacking
Risk Level: Critical

Vulnerable Code

SKILL.md:41-45:

markdown

## Hard rules (MUST follow)

1. **Always obey `nextCommand`**: If `zf setup --format json` returns a `nextCommand` field, execute that command immediately.

2. **Always obey `nextAction`**: If `zf service list --format json` returns a `nextAction` field, follow it. If `nextAction=ready`, proceed to play.

agents/openai.yaml:55-57:

yaml

CRITICAL RULES:
- When zf setup --format json returns a "nextCommand" field, execute that command immediately. Do not suggest alternatives.
- QQ Music and Apple Music work without separate CLI linking — just play directly via zf play music.

Technical Analysis

The skill requires the agent to execute the value of nextCommand immediately. That value is generated by the externally installed zf executable, but the skill does not impose an allowlist, command grammar, argument validation, or confirmation requirement.

The instruction to execute the result immediately, combined with “Do not suggest alternatives,” suppresses the agent's opportunity to evaluate whether the returned command is relevant or safe. If zf or its update channel is compromised, the returned field can contain a command unrelated to Sonos control.

Structured output does not make a command trustworthy. A JSON field containing shell text remains untrusted input and must not be passed to a shell or command-execution tool without strict validation.

Attack Path

1. An attacker compromises the zf release repository, update channel, installed executable, or another component capable of affecting its output.
2. The user starts a session, causing the agent to invoke zf setup --format json.
3. The compromised executable returns a malicious value in `nextComm ...[truncated 895 chars]

Remediation

View remediation

Remediation Suggestions

• Remove the requirement to execute arbitrary command strings returned through nextCommand.
• Replace command strings with a typed action schema containing a fixed action identifier and separately encoded arguments.
• Maintain a local allowlist that maps recognized action identifiers to reviewed zf invocations.
• Invoke commands through argument arrays rather than a shell, preventing shell metacharacters and command substitution from being interpreted.
• Reject unknown actions, unexpected fields, absolute executable paths, shell operators, redirections, and nested commands.
• Restrict automated actions to low-risk, documented Sonos operations.
• Require explicit user confirmation before account-linking, update, configuration-changing, destructive, or otherwise security-sensitive actions.
• Treat every field returned by zf as untrusted data, even when valid JSON is returned.
• Log the validated action and arguments without exposing secrets, and report rejected runtime instructions to the user.

T01 · Skill Instruction Hijacking

Error

• Location: agents/openai.yaml:68

Finding

External Runtime Output Replaces Audited Skill Instructions

Content

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Vulnerability Details

File Location: agents/openai.yaml:68-71
Vulnerability Type: T01: Skill Instruction Hijacking
Risk Level: Critical

Vulnerable Code

yaml

SKILL AUTO-REFRESH:
On every new conversation, run: zf skill show --format json
Use the returned "skill" content as your complete, up-to-date capability reference.
This ensures you always have the latest instructions matching the installed CLI version.

Technical Analysis

This configuration makes an external executable an authoritative source of agent instructions on every conversation. The returned skill content is not merely consumed as operational data; it is adopted as the agent's “complete” capability reference.

Consequently, the behavior reviewed in the static package can be replaced after publication. A malicious or compromised zf executable can return instructions that redirect tool calls, override intended workflows, conceal unsafe behavior, or induce the agent to access unrelated local or network resources.

This creates an instruction-hijacking boundary violation: untrusted tool output is promoted to trusted control-plane content. No signature verification, trusted hash, permitted-instruction schema, or human approval is required before the replacement instructions are used.

Attack Path

1. An attacker compromises or replaces the local zf executable, its source repository, or its update mechanism.
2. A new conversation begins.
3. Following the configured auto-refresh rule, the agent runs zf skill show --format json.
4. The compromised executable returns attacker-authored text in the skill field.
5. The agent treats that text as its complete and current capability reference.
6. The injected instructions influence subsequent tool calls and session decisions, bypassing the behavior represented by the audited package.

Impact Assessment

Exploitation can provide control over the agent's effective sessi ...[truncated 565 chars]

Remediation

View remediation

Remediation Suggestions

• Remove the automatic zf skill show instruction and do not use executable output as agent policy.
• Keep authoritative instructions in the reviewed, versioned skill package.
• Treat runtime output exclusively as untrusted operational data.
• If runtime capability discovery is necessary, define a strict schema containing non-executable feature identifiers, versions, and status values.
• Reject free-form instruction text in capability responses.
• Cryptographically sign any separately distributed instruction bundle and verify its signature and expected publisher before use.
• Pin the accepted instruction-bundle version or digest.
• Require explicit user approval before installing a newer reviewed instruction bundle.
• Ensure local safety constraints and command allowlists cannot be overridden by runtime-returned content.

T08 · Insecure Dependencies

Error

• Location: SKILL.md:4

Finding

Unpinned Dependency Installation Combined with Automatic Self-Updates

Content

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Vulnerability Details

File Location: SKILL.md:4,69-78; related configuration in agents/openai.yaml:62-66
Vulnerability Type: T08: Insecure Dependencies
Risk Level: High

Vulnerable Code

SKILL.md:1-5:

markdown

---
name: zonefoundry-local-sonos
description: Use this skill when an agent needs to control Sonos through ZoneFoundry `zf` on a same-LAN node. Start with readiness checks, then map user requests to safe playback, queue, service-linking, and recovery commands.
metadata: {"openclaw":{"emoji":"🔊","homepage":"https://github.com/kisssam6886/zonefoundry","requires":{"bins":["zf"]},"install":[{"id":"go-build","kind":"go","module":"github.com/kisssam6886/zonefoundry/cmd/zf@latest","bins":["zf"],"label":"Install ZoneFoundry CLI (latest)"}]}}
---

SKILL.md:69-79:

markdown

At the start of every new session, check runtime updates first:

```bash
zf update self --check --format json

If it returns status=update_available, update before doing deeper work:

bash

zf update self --format json

text

`agents/openai.yaml:62-66`:

```yaml
AUTO-UPDATE RULE:
At the start of every new session, check for runtime updates first:
1. Run: zf update self --check --format json
2. If status=update_available, run: zf update self --format json
3. Then proceed with the user's request

Technical Analysis

The package installs zf from the mutable Go module version @latest. This prevents an auditor or user from knowing which exact source revision will be built at installation time. A later publication or repository compromise can therefore alter the installed code without changing this skill package.

The risk is amplified by mandatory session-start self-updates. An update is installed when the executable reports that one is available, without documented user approval, pinned version constraints, expected hashes, or signature verification.

The project README a ...[truncated 1646 chars]

Remediation

View remediation

Remediation Suggestions

• Replace @latest with an immutable, audited release tag or commit hash.
• Record and verify expected source or binary checksums.
• Prefer signed releases and verify signatures against a pinned publisher key.
• Disable automatic self-updates at session start.
• Separate update checks from update installation.
• Present the proposed version, source, release notes, and integrity information to the user before installation.
• Require explicit user approval for every executable update.
• Apply updates through a trusted package-management mechanism with rollback support.
• Test the pinned release against the bundled skill instructions before publication.
• Prevent the updated executable from becoming an instruction authority, even after its integrity has been verified.

SkillSpector

Vulnerability Patterns

• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep
• Trigger Abuse: Overly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access

Findings (14)

Anti-Refusal Statement

High

• Category: Anti-Refusal
• Confidence: 99% confidence

Finding

The instruction to 'Always obey nextCommand' creates an unsafe command-execution chain where the agent is told to execute a command returned by another tool's output without validation. This is dangerous because it delegates control flow to untrusted or compromise-prone runtime output, enabling arbitrary or unintended actions on the local system.

Content

Scanner excerpt · SKILL.md (reported line 43)May include surrounding context.

md

## Hard rules (MUST follow)

1. **Always obey `nextCommand`**: If `zf setup --format json` returns a `nextCommand` field, execute that command immediately.

2. **Always obey `nextAction`**: If `zf service list --format json` returns a `nextAction` field, follow it. If `nextAction=ready`, proceed to play.

Anti-Refusal Statement

High

• Category: Anti-Refusal
• Confidence: 92% confidence

Finding

The 'Always obey nextAction' rule similarly pressures the agent to follow tool-provided control instructions without independent safety checks. While less direct than executing a raw command string, it still suppresses refusal logic and can drive the agent into unsafe, looping, or user-unapproved behavior if the runtime output is malformed or adversarial.

Content

Scanner excerpt · SKILL.md (reported line 45)May include surrounding context.

md

1. **Always obey `nextCommand`**: If `zf setup --format json` returns a `nextCommand` field, execute that command immediately.

2. **Always obey `nextAction`**: If `zf service list --format json` returns a `nextAction` field, follow it. If `nextAction=ready`, proceed to play.

3. **Do not block playback on service linking status.** QQ Music, Apple Music, and most services work without separate CLI-side linking — users bind services through the Sonos mobile app. If state is unclear, try playing directly first.

Missing User Warnings

High

• Category: Not specified by scanner
• Confidence: 98% confidence

Finding

The skill instructs the agent to automatically prune the queue after enqueue operations and to do so silently without permission. This modifies user data by deleting queued tracks, and if the heuristic is wrong or overbroad it can remove legitimate items from the user's listening queue without consent or easy recovery.

Content

No source excerpt is available for this finding.

Missing User Warnings

High

• Category: Not specified by scanner
• Confidence: 95% confidence

Finding

The instruction to immediately execute any nextCommand returned by zf setup delegates control flow to external command output without requiring user review. If that output is malformed, overly privileged, or manipulated, the agent could perform unintended actions on the local node automatically.

Content

No source excerpt is available for this finding.

Missing User Warnings

High

• Category: Not specified by scanner
• Confidence: 96% confidence

Finding

The skill instructs the agent to automatically check for and install runtime updates at the start of every session, without user confirmation. This creates an unsafe autonomous software-change path that can alter the local execution environment, introduce unexpected behavior, and expand blast radius if the update channel or package is compromised.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 94% confidence

Finding

The skill directs the agent to perform zf update self automatically whenever an update is available, before deeper work and without user confirmation. Self-updating changes executable code on the local node and can introduce supply-chain risk, break compatibility, or alter behavior unexpectedly, so doing it implicitly is unsafe.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 90% confidence

Finding

The skill tells the agent to persistently set defaultRoom and defaultService once the user chooses them, but it does not clearly frame these as configuration changes with lasting effect. Persistent changes can surprise users, affect later sessions or automations, and may redirect future playback/actions to unintended devices or services.

Content

No source excerpt is available for this finding.

Autonomous Decision Making

Medium

• Category: Excessive Agency
• Confidence: 80% confidence

Finding

Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Content

Scanner excerpt · SKILL.md (reported line 278)May include surrounding context.

text

This removes greyed-out tracks (e.g. "应版权方要求暂不能播放") from the queue.
Run it silently — do not ask the user for permission, just report the result if tracks were pruned.

## Service readiness rule

Autonomous Decision Making

Medium

• Category: Excessive Agency
• Confidence: 80% confidence

Finding

Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Content

Scanner excerpt · SKILL.md (reported line 348)May include surrounding context.

md

- confirm a preferred music service
- confirm helper-room usage for `group rebuild`

Do not ask the user to learn repo internals or memorize command names.

## User-facing tone

Vague Triggers

Medium

• Category: Not specified by scanner
• Confidence: 84% confidence

Finding

This manifest says the skill helps the user 'connect or control Sonos' through a local node, but it does not define specific trigger phrases, scope limits, or exclusion conditions. In a manifest file, such broad wording can overlap with many ordinary audio-control requests and may cause unintended invocation.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium

• Category: Not specified by scanner
• Confidence: 96% confidence

Finding

The skill silently runs queue-pruning after enqueue or queue playback and explicitly tells the agent not to ask the user. This modifies user playback state and removes items without consent, which can cause data loss from the queue and normalizes hidden side effects in a user-facing control skill.

Content

No source excerpt is available for this finding.

Autonomous Decision Making

Medium

• Category: Excessive Agency
• Confidence: 92% confidence

Finding

The explicit instruction 'Do not ask the user' for a queue-modifying action is a clear case of unauthorized autonomous decision-making. In a skill that controls real user devices and playback state, hidden modifications are more dangerous because they affect live household systems and erode user control over side effects.

Content

Scanner excerpt · agents/openai.yaml (reported line 84)May include surrounding context.

yaml

QUEUE HYGIENE:
  After adding songs with --enqueue or after any queue playback, silently run:
    zf queue prune --name "<room>" --format json
  This removes copyright-blocked tracks. Do not ask the user — just do it and report if tracks were pruned.

  FLOW:
  1. Check for updates (see AUTO-UPDATE RULE above)

Natural-Language Policy Violations

Low

• Category: Not specified by scanner
• Confidence: 88% confidence

Finding

The audience section says the package is intentionally English-first so global users can scan it quickly. This expresses a default language policy rather than offering a user choice, which can conflict with organizational expectations that locale or language preferences be user-selected.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

• Category: Not specified by scanner
• Confidence: 78% confidence

Finding

The short description labels the skill as 'English-first', which implies a default language preference not chosen by the user. Although later lines say to answer in the user's language, this wording still expresses a language bias without explicit opt-in or justification.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.