India Price Tracker

• Outcome: Pass
• Latest audit: Sep 12, 2026 · 7:37 AM UTC
• Version: 1.0.0

Overview

This skill runs local mock price-comparison scripts and does not show hidden, destructive, credential-seeking, or remote-execution behavior, but users should not treat its generated prices as real market data.

Install only if you want a local starter/demo workflow for India price-comparison logic. Do not make purchase, resale, or arbitrage decisions from the default outputs; they are generated mock data until you add and validate compliant live adapters. Be careful with bulk_monitor.py --output because it can write to the path you provide.

A.I.G

Vulnerability Patterns

• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• 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
• Unauthorized Access and Privilege Escalation: Obtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns

• MCP Least Privilege: Underdeclared Capability, Wildcard Permission, Missing Permission Declaration
• MCP Tool Poisoning: Hidden Instructions, Unicode Deception, Parameter Description Injection
• 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

Findings (7)

Tp4

High

• Category: MCP Tool Poisoning
• Confidence: 94% confidence
• Finding: The code partially matches the description in that it compares prices across a predefined set of Indian stores and displays list price, effective price, stock, and seller rating. However, several material declared capabilities are absent from this code chunk: there is no arbitrage analysis, no persistence or historical tracking of prices, and no alerting/monitoring mechanism. Additionally, the script uses a mock_search function rather than showing real store access, so the claimed tracking across popular stores is only weakly supported by this snippet. Because the declared purpose includes multiple substantial features beyond simple comparison, this is a description-behavior mismatch.

Tp4

High

• Category: MCP Tool Poisoning
• Confidence: 97% confidence
• Finding: The code partially aligns with the pricing-comparison theme because it models stores, offers, listings, and calculates an effective price after discounts/cashback/shipping. However, the implemented behavior is only a mock data generator (`mock_search`) seeded by the keyword and returning randomized listings. There is no real retrieval of product prices from Amazon India, Flipkart, or other stores, no comparison logic beyond exposing `effective_price`, no arbitrage detection, and no persistence or scheduling for price history or alerts. Therefore, the declared description materially overstates the actual functionality present in this code chunk.

Tp4

High

• Category: MCP Tool Poisoning
• Confidence: 96% confidence
• Finding: The declared description presents a broad real-world price tracking and comparison capability across Indian stores, including offers/cashback normalization, arbitrage detection, and alerting. The supplied code only performs local, mock trend analysis: it parses store names, generates deterministic pseudo-random historical prices, summarizes them, and optionally prints a simple trend direction. This is a materially narrower and different behavior than the declared purpose, so it should be flagged as a mismatch.

Tp4

High

• Category: MCP Tool Poisoning
• Confidence: 90% confidence
• Finding: The code generally aligns with the high-level goal of comparing product prices and issuing alerts, including a simple arbitrage spread check. However, key parts of the declared description are not actually implemented in this chunk: there is no price history storage or monitoring over time, no alerting beyond immediate console output during a single run, and no visible computation of effective prices from offers/cashback—those values are merely read from returned objects. Additionally, the behavior relies on mock_search rather than showing real integrations with the named stores. So the description overstates the implemented functionality of the supplied code chunk.

Lp3

Medium

• Category: MCP Least Privilege
• Confidence: 88% confidence
• Finding: The skill declares executable scripts and an output path (`reports/alerts.txt`) but does not define any explicit tool scope or permission boundaries. In agent environments, undeclared file-write capability can enable unintended writes, overwrites, or misuse of local workspace files because consumers cannot tell what filesystem access the skill expects.

Description-Behavior Mismatch

Medium

• Confidence: 98% confidence
• Finding: The function advertised as price history tracking generates fabricated values using pseudo-random data instead of retrieving actual store prices. In a price-tracking skill, this is dangerous because users may make purchasing, alerting, or arbitrage decisions based on false market data, causing financial harm and undermining trust in the tool.

Intent-Code Divergence

Medium

• Confidence: 95% confidence
• Finding: The CLI claims to analyze price history trends, but all trend outputs are derived from synthetic mock data rather than real historical prices. This creates misleading analytics in a financial/comparison-shopping context, where false trends can influence buying timing, arbitrage behavior, or alerting workflows based on nonexistent price movements.

Static analysis

No suspicious patterns detected.