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Security audit

Crypto Social Intel

Security checks for vulnerabilities and agentic risk

Overview

This Markdown-only skill uses a disclosed crypto-social-data service and shows no evidence of hidden code, persistence, credential theft, or destructive behavior.

Install only if you are comfortable sending crypto sentiment/trend queries to Antalpha's disclosed MCP service. Treat Santiment-backed social data as delayed reference material, not real-time trading guidance, and be aware that some outputs may default to Chinese wording.

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
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • 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 (2)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
91% confidence
Finding

The activation description is very broad and includes many generic English and Chinese phrases such as sentiment, trending, unusual social activity, and Fear & Greed queries. In an agent environment, this can cause the skill to trigger in contexts where the user did not intend to invoke this specific external-data workflow, leading to unnecessary tool calls, over-collection of context, or misleading responses based on delayed third-party data.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The skill prescribes Chinese-language output templates and required appended disclaimers without conditioning on the user's language preference. This can override user intent, degrade usability, and in multilingual deployments may cause confusion or conceal important caveats if the user cannot read the forced language well.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.