Security audit

patent-gap-supply-chain

Security checks for vulnerabilities and agentic risk

Overview

This is a disclosed Markdown-only research workflow for patent-based supply-chain analysis, with no hidden execution, persistence, or credential handling found.

Before installing, treat the skill as a specialized public-source competitive-intelligence workflow, not a general company research assistant. Use it when you explicitly want patent-gap, supplier, customer, or technology-dependency analysis, and review its confidence ratings carefully because supply-chain inferences can be wrong or stale.

A.I.G

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

SkillSpector

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 (8)

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 93% confidence
Finding: The trigger examples are broad enough to activate on ordinary analyst requests such as generic company research, supplier analysis, or customer identification. In a competitive-intelligence skill that performs multi-step inference about supply-chain relationships, this can cause the workflow to run outside its intended boundary, producing speculative or privacy-/compliance-sensitive conclusions without explicit user intent or sufficient guardrails.
Content: No source excerpt is available for this finding.

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 88% confidence
Finding: The description combines broad use cases with specialized investigative functions without firm boundaries, making invocation scope ambiguous. That ambiguity can route ordinary research tasks into a workflow designed for competitive intelligence and supplier/customer inference, which may produce unnecessary sensitive analysis and increase the risk of overreach or false-positive conclusions.
Content: No source excerpt is available for this finding.

Vague Triggers

Medium

Category: Not specified by scanner
Confidence: 92% confidence
Finding: The trigger list is very broad and includes common research phrases such as industry analysis, tech stock research, supplier identification, and customer identification. In an agent environment, this can cause the skill to activate for routine research requests that do not warrant this specialized workflow, increasing the chance of unintended data gathering, over-scoped competitive-intelligence behavior, or misleading patent-based inferences.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 88% confidence
Finding: This markdown file includes natural-language content stating that the skill uses Chinese and English trigger keywords for cross-locale agent triggering. Because the text specifies locale behavior without mentioning user choice, opt-in, or a clearly justified regional constraint, it may conflict with the language/locale policy guidance.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 65% confidence
Finding: The document is explicitly organized into Chinese and English sections, but it does not state that the skill will honor the user's preferred language or locale. Because locale/language policy violations are in scope for all file types, this is a mild concern if the skill defaults to these languages without user opt-in.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 77% confidence
Finding: This markdown file contains natural-language content that assumes use of both English and Chinese script, beginning with the title line. Under the policy rule, forcing a specific language or locale without user opt-in can be a violation, and the file does not explain that bilingual presentation is optional or required for a region-specific purpose.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 77% confidence
Finding: This markdown guide includes multiple untranslated Chinese company names and regulatory terms such as 中芯国际, 药审中心, and 集采 within otherwise English prose. That can impose a mixed-language experience without explicit user opt-in or a stated China-specific locale scope, which fits the language/locale policy category.
Content: No source excerpt is available for this finding.

Vague Triggers

Low

Category: Not specified by scanner
Confidence: 87% confidence
Finding: This markdown file includes a trigger description stating to use the reverse workflow when the user provides a technology-owning company and wants to identify downstream customers, plus several example phrasings. While the examples are helpful, the activation condition remains broad and does not provide exclusion conditions or negative examples, which could cause the workflow to be applied to general customer-identification questions outside the intended patent/supply-chain context.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.