Dubai

• Outcome: Pass
• Latest audit: May 28, 2026, 1:46 AM
• Version:
  1.0.0

Overview

This is a Markdown-only Dubai information skill with no code execution, credentials, persistence, or data access, but users should verify legal, visa, business, safety, and housing-related advice before relying on it.

Install only if you want a static Dubai reference guide. Treat legal, immigration, tax, healthcare, LGBTQ+ safety, education, and business setup sections as starting points, and verify current requirements with official sources or qualified professionals before acting.

SkillSpector

By NVIDIA

Vulnerability Patterns

• Trigger Abuse: Overly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access
• Supply Chain: Unpinned Dependencies, External Script Fetching, Obfuscated Code

Findings (13)

Vague Triggers

Medium

• Confidence: 92% confidence
• Finding: The activation rule is very broad: any question about Dubai for any purpose triggers the skill. Overly permissive activation can cause the agent to invoke this skill in situations requiring narrower domain expertise, including legal, immigration, safety, or business guidance, increasing the chance of overconfident or outdated advice being presented as authoritative.

Missing User Warnings

Medium

• Confidence: 94% confidence
• Finding: The file gives concrete procedural guidance on entity formation, tax treatment, visa steps, and banking expectations as if they are current and generally applicable, but it does not prominently warn that regulations, fees, eligibility rules, and tax interpretations can change and vary by activity, free zone, and user circumstances. In a business setup skill, users may rely directly on this information to make legal and financial decisions, so missing verification/disclaimer language can lead to non-compliance, wasted fees, or rejected applications.

Natural-Language Policy Violations

Low

• Confidence: 89% confidence
• Finding: The statement 'Zayed University | Public | Females; males at Abu Dhabi campus' presents gender-restricted access as a blanket fact without context, qualification, or guidance for affected users. In an education guidance skill, this can mislead users, reinforce exclusionary assumptions, and cause poor decision-making if the policy is outdated, conditional, or more nuanced than stated.

Natural-Language Policy Violations

Medium

• Confidence: 94% confidence
• Finding: The resident profile includes specific nationalities as descriptors of who lives in Palm Jumeirah. In a location-guidance skill, this can enable or normalize nationality-based targeting or steering, which creates fairness and discrimination risk even if presented as market color rather than explicit exclusion.

Natural-Language Policy Violations

Medium

• Confidence: 94% confidence
• Finding: This section similarly profiles the neighborhood using named nationalities, which may support nationality-based inference or selective recommendations. In a housing-related context, that is more sensitive because it can contribute to discriminatory steering or biased user guidance.

Natural-Language Policy Violations

Medium

• Confidence: 95% confidence
• Finding: The Downtown resident profile explicitly segments likely residents by nationality and ethnicity-adjacent categories, which introduces stereotyping and demographic targeting without user need or consent. In a housing/neighborhood guidance context, this is especially sensitive because it can normalize exclusionary assumptions and potentially support discriminatory decision-making.

Natural-Language Policy Violations

Medium

• Confidence: 96% confidence
• Finding: The DIFC section describes residents using nationality-based targeting language, linking a neighborhood to specific national groups and wealthy regional identities. Because the skill is effectively giving relocation and housing advice, this can reinforce discriminatory housing preferences and steer users based on protected characteristics rather than legitimate housing factors.

Natural-Language Policy Violations

Medium

• Confidence: 95% confidence
• Finding: The Business Bay profile includes demographic segmentation by nationality, even if presented as descriptive market context. In a neighborhood-selection skill, that creates a meaningful risk of biased steering and can be used to infer where certain groups 'belong,' which is inappropriate and potentially harmful in housing-related content.

Natural-Language Policy Violations

Medium

• Confidence: 95% confidence
• Finding: The Arabian Ranches resident profile uses nationality-based generalizations and labels one nationality as 'dominant,' which can encode demographic stereotyping into guidance content. In a housing/neighborhood recommendation context, this is especially sensitive because it can influence user decisions in ways that resemble steering or exclusionary housing guidance.

Natural-Language Policy Violations

Medium

• Confidence: 94% confidence
• Finding: The Springs section includes resident profiling by nationality, which introduces protected-characteristic segmentation into neighborhood advice. Because this skill helps users choose where to live, such content can normalize discriminatory decision-making or create the appearance of housing guidance based on ethnicity or national origin.

Natural-Language Policy Violations

Medium

• Confidence: 94% confidence
• Finding: The Meadows section again profiles likely residents by nationality, which is inappropriate in a neighborhood-selection document. In the context of residential advice, repeated demographic labeling increases compliance and reputational risk by suggesting certain groups belong in specific communities.

Natural-Language Policy Violations

Medium

• Confidence: 97% confidence
• Finding: The DSO content combines nationality-based resident profiling with the phrase 'Dubai's Bangalore,' a culturally loaded comparison that can stereotype both the area and its residents. In a relocation/housing skill, this is more dangerous because it may shape where users feel welcome or unwelcome based on protected characteristics rather than objective suitability.

Natural-Language Policy Violations

Medium

• Confidence: 86% confidence
• Finding: The section presents LGBTQ+ legal/safety claims as absolute and categorical without clarifying legal ambiguity, enforcement variability, or citing jurisdiction-specific primary sources. In a travel safety skill, overstated or unsupported legal claims can mislead users about personal risk, potentially causing harm, discrimination, or bad decision-making.

VirusTotal

65/65 vendors flagged this skill as clean.