machine-learning-ops-ml-pipeline

Pass

Audited by Gen Agent Trust Hub on Aug 3, 2026

Risk Level: SAFEPROMPT_INJECTION
Full Analysis
  • [PROMPT_INJECTION]: The skill facilitates an orchestration workflow where user input from the $ARGUMENTS variable is directly inserted into the prompts for specialized sub-agents (Data Engineer, Data Scientist). This creates a surface for indirect prompt injection if the user input contains instructions designed to manipulate the sub-agents' behavior.
  • Ingestion points: User input is ingested via the $ARGUMENTS placeholder in SKILL.md and passed to multiple <Task> prompts.
  • Boundary markers: The skill lacks delimiters (such as triple quotes or XML tags) or explicit instructions for the agents to ignore embedded commands within the $ARGUMENTS string.
  • Capability inventory: The orchestrated agents are tasked with generating executable Python code, Hyperparameter optimization scripts (Optuna), Kubernetes manifests (Helm charts), and Infrastructure as Code (Terraform), which could be compromised by malicious input.
  • Sanitization: There is no evidence of input validation, filtering, or escaping of the user-provided content before it is processed by the sub-agents.
Audit Metadata
Risk Level
SAFE
Analyzed
Aug 3, 2026, 03:59 PM
Security Audit — agent-trust-hub — machine-learning-ops-ml-pipeline