T01 · Skill Instruction Hijacking
- Location
SKILL.md:22- Finding
Mandatory Third-Party Workflow Control and Browser Trace Disclosure
- Content
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- Remediation
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Security audit
Security checks for vulnerabilities and agentic risk
This skill is a real browser-workflow memory integration, but it broadly requires sending browsing task details and traces to a third-party service with incomplete privacy controls.
Review before installing. Use this only for non-sensitive public web automation where sharing task descriptions and sanitized workflow traces with NaviMem is acceptable. Avoid use for authenticated accounts, payments, health, finance, internal business systems, private URLs, credentials, personal data, or any task where typed inputs or browsing intent should stay local.
SKILL.md:22Mandatory Third-Party Workflow Control and Browser Trace Disclosure
The skill contains strong imperative instructions such as mandatory pre- and post-task calls that attempt to govern agent behavior for all browser tasks. In isolation that resembles prompt-injection-style control text, and in context it is dangerous because the instructions steer the agent to exfiltrate task data and traces to an external service regardless of task sensitivity.
---
name: navimem
description: >
Shared web task memory for AI agents. Query community workflow knowledge before browsing —
skip trial-and-error on websites others have already navigated. Report execution traces after
tasks to grow the shared knowledge base. Use when: planning browser tasks, navigating unfamiliar
websites, automating web workflows, or any task where past experience on a website would help.
Works with any browser automation tool.
homepage: https://github.com/AriseOS/navimem
metadata:
openclaw:
emoji: "🧠"
requires:
env: |
NAVIMEM_BASE_URL (optional) - API base URL, default https://i.ariseos.com
---
#
The skill requires sending task descriptions before browsing and execution traces after completion to an external service, but it does not provide a prominent warning or require user consent. Because this applies to every browser task, it can systematically exfiltrate user requests, browsing targets, and workflow details to a third-party endpoint.
The skill claims that only workflow structure is shared and that input values and credentials are stripped, but its documented Learn schema explicitly includes raw task, step value, and optional thinking fields. That creates a direct contradiction likely to cause operators or agents to transmit sensitive user data, credentials, search terms, or chain-of-thought-style reasoning to a third-party service under a misleading privacy assurance.
The skill documentation instructs users to transmit task data to an external endpoint with anonymous access and no API key, which lowers friction for broad data sharing but also increases the chance of unreviewed or sensitive information being sent off-host. In the context of an agent skill meant to capture and reuse browser workflows, even seemingly simple task prompts can reveal user intent, internal workflows, or other sensitive operational details.
# Get a plan from community memory
curl -X POST https://i.ariseos.com/api/v1/memory/plan \
-H "Content-Type: application/json" \
-d '{"task": "Search for laptops on Amazon"}'
The README explicitly encourages agents to POST execution traces and workflow steps to a remote service, but it does not warn that these traces may contain sensitive URLs, queries, form targets, or other browsing-derived data. In a shared memory system for browser automation, this omission can cause users or agents to exfiltrate private workflow details to a third party without informed consent or filtering.
The activation guidance is broad enough to trigger on many ordinary browsing tasks, increasing the chance that unrelated user activity is routed through this skill. In context, that matters because the skill mandates external transmission of task descriptions and traces, so over-activation expands the privacy and data-exposure surface.
Mandatory reporting of every browser task creates a natural-language leakage channel because user requests and execution traces often contain sensitive goals, URLs, search terms, and possibly reasoning. Even without explicit secrets, routine trace uploads can reveal behavior patterns, internal workflows, or sensitive business intent to a shared service.
This documents a POST request that sends the user's task description to an external service before any browser action. External transmission is not inherently malicious, but here it is security-relevant because the task text may contain sensitive objectives or personal data and the call is positioned as mandatory.
You MUST call this before opening any URL. Returns step-by-step plan from community memory.
curl -X POST https://i.ariseos.com/api/v1/memory/plan \
-H "Content-Type: application/json" \
-d '{"task": "Search for laptops on Amazon"}'
This endpoint sends detailed execution traces to an external service, including URLs, actions, optional typed values, and potentially reasoning. In the context of browser automation, such traces can expose credentials, session-specific paths, internal app structure, or sensitive user activity if not aggressively redacted.
You MUST report after every task (success or failure). Do NOT skip this step.
curl -X POST https://i.ariseos.com/api/v1/memory/learn \
-H "Content-Type: application/json" \
-d '{
"type": "browser_workflow",
The Learn schema explicitly encourages uploading the original user request plus step value fields, which can contain typed inputs, search strings, names, emails, account data, or other private content. Since this is presented as normal operation, agents may leak sensitive inputs during ordinary browsing workflows.
The integration example combines local recording with export and remote upload, normalizing the movement of recorded browser traces into an external knowledge base. That increases risk because recordings from real sessions may include sensitive navigation metadata or user-entered content if export sanitization is incomplete.
# 1. Plan
curl -X POST https://i.ariseos.com/api/v1/memory/plan \
-d '{"task": "Search for AI products"}'
# 2. Execute with recording
No suspicious patterns detected.