Back to skill

Security audit

AI ML Engineer

Security checks for vulnerabilities and agentic risk

Overview

This skill appears to be a straightforward career-roadmap API integration, though users should know it sends career-profile details and session identifiers to an external service.

Before installing, treat this as a hosted API integration: send only the career, skills, and goals data needed for a roadmap, omit userId unless required, and review the provider's privacy terms if you plan to submit identifiable or sensitive professional information.

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
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (4)

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The skill describes collecting and analyzing personal career profile data, including experience, skills, goals, and session-based tracking, but provides no privacy notice, retention guidance, or warning about how submitted data may be handled. This can mislead users into sharing sensitive professional information without informed consent, increasing privacy and compliance risk.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The sample request explicitly transmits a session identifier, user identifier, and timestamp without any accompanying warning about tracking, correlation, or personal data handling. Example payloads strongly influence implementation, so this omission can normalize unnecessary identifier sharing and lead to privacy-invasive integrations.

Content

No source excerpt is available for this finding.

External Transmission

Medium
Category
Data Exfiltration
Confidence
50% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · SKILL.md (reported line 210)May include surrounding context.

md
## References

- **Kong Route:** https://api.mkkpro.com/career/ai-ml-engineer
- **API Docs:** https://api.mkkpro.com:8055/docs

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
83% confidence
Finding

This is a manifest/config file, so vague-trigger checks apply. The operation is described only as "Generate Roadmap" and "Generate personalized AI/ML engineering roadmap" without any explicit trigger phrases, scope limits, or exclusion conditions, making activation criteria ambiguous in systems that derive skill invocation behavior from OpenAPI descriptions.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.