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Security audit

yoooclaw-hotspot-topic-scout-en

Security checks for vulnerabilities and agentic risk

Overview

This skill is meant to find content ideas from notifications and web trends, but it has broad access to private/internal messages and can turn those signals into external searches and outputs.

Install only if you are comfortable with the agent reading recent mobile notifications that may include private chats, workplace discussions, fan messages, and third-party content. Use narrow time ranges and explicitly name allowed apps, groups, accounts, and topics; avoid using it for confidential team plans or personal messages unless you are prepared for derived terms to be searched externally and summarized in the session.

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs
Findings (1)

other

Warning
Location
SKILL.md:9
Finding

Broad Collection and Potential External Disclosure of Private Notification Content

Content
View full analysis

Vulnerability Details

File Location: SKILL.md, lines 9-16 and 28-46
Vulnerability Type: Privacy overcollection and potential disclosure
Risk Level: Medium

Vulnerable Code Snippet

text
This Skill collects materials from two channels and combines them internally and externally:
- **Internal signals**: Message notifications on users’ mobile phones (content platform push, industry group chat, team discussion, fan feedback)
- **External hot spots**: Use `byted-web-search` to search for the latest industry trends, benchmark bloggers’ recent content, and hot topics on the track through the Internet

Users set three types of attention dimensions through the installation pop-up window:
- Who to follow: Benchmark bloggers, peer accounts, competing product creators, brand accounts or content sources that users clearly follow.
- What to focus on: account tracks, content positioning, audience portraits, industry keywords (models, products, platforms, companies, technical directions, consumer trends, policy events, etc.).
- Which groups and applications to pay attention to: monitored information source platforms and groups, such as Xiaohongshu, Bilibili, Jiji, official accounts, WeChat industry groups, creator groups, and internal team discussion groups.
text
### Phase 1: Collect internal signals

1. To query notifications within a specified time range, use exec to execute:
If the user does not provide the corresponding time, query notifications from yesterday to the current time:
command: openclaw ntf search --from start time --to end time
yieldMs: 30000

2. As long as the task involves "yesterday", "recent", "just now" and "latest notification", the query must be re-queried and the old results will not be reused.
3. Read the user's settings of who to follow, what to follow, and which groups and applications to follow; if the user does not provide it, the most likely filtering direction is inferred from the current request and notification 
...[truncated 3532 chars]
Remediation
View remediation

Remediation Suggestions

  1. Require explicit, informed user consent before reading notification data, clearly identifying the sources and time range involved.
  2. Apply least-privilege retrieval controls directly in the notification query:
    • Allowlist specific applications.
    • Allowlist approved groups, accounts, or senders.
    • Use the shortest necessary time interval.
    • Exclude private and unrelated applications by default.
  3. Do not infer permission from notification context when configuration is absent. Ask the user to specify authorized sources instead.
  4. Filter and classify notification content locally before any external request is made.
  5. Remove names, handles, message text, organization identifiers, project names, and other personal or confidential information from derived search terms.
  6. Obtain separate confirmation before transmitting any notification-derived term to an external search provider.
  7. Prohibit external searches derived from internal team discussions, private messages, or other confidential channels unless expressly authorized.
  8. Add output controls that summarize trends without reproducing private message content or identifying third parties.
  9. Document retention, logging, deletion, and external-provider handling rules for notification-derived information.
  10. Record which approved sources contributed to each result so users can review the provenance and verify that collection stayed within scope.
Vulnerability Patterns
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (5)

Ssd 3

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The skill explicitly directs the model to collect materials from mobile notifications, industry group chats, team discussions, and fan feedback, then combine them into output. This creates a direct privacy and confidentiality risk because private communications and internal business discussions may be summarized or exposed beyond their original context, potentially leaking personal data, trade secrets, or sensitive operational information.

Content

No source excerpt is available for this finding.

Ssd 3

High
Category
Not specified by scanner
Confidence
98% confidence
Finding

The workflow specifically tells the model to extract clues from team discussions, group-forwards, fan questions, and benchmark mentions inside notifications and use them as output material. This is dangerous because it operationalizes surveillance-like processing of interpersonal communications and increases the chance that confidential business context or personal correspondence is transformed into shareable summaries.

Content

No source excerpt is available for this finding.

Ssd 3

High
Category
Not specified by scanner
Confidence
97% confidence
Finding

The output format requires reporting insights sourced from comments, private messages, communities, and team reports back to the user, which institutionalizes disclosure of sensitive communications in generated text. Even if the user is the device owner, summarizing these sources can expose third-party data, private opinions, or confidential team matters beyond what those participants expected.

Content

No source excerpt is available for this finding.

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
84% confidence
Finding

The invocation description is broad enough to match generic requests about trends, topic ideas, or competitor activity, which could cause the skill to activate in ordinary conversations where the user did not intend notification mining. That increases the risk of over-collection from private device data sources and makes consent and user expectations ambiguous.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The skill instructs collection and analysis of mobile notifications, fan feedback, and internal group discussions without any explicit consent, sensitivity warning, or guidance to minimize personal or confidential data exposure. This is dangerous because users may trigger the skill without realizing it processes private communications and workplace discussions, leading to unintended disclosure of sensitive personal or organizational information.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.