agent-observability
Pass
Audited by Gen Agent Trust Hub on Sep 24, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill processes untrusted data from model responses and tool outputs to generate logs and traces, creating a potential ingestion surface for indirect prompt injection.
- Ingestion points: The tracing wrappers in
SKILL.md(traced_llm_call,traced_tool) capture raw message content, tool arguments, and model responses. - Boundary markers: The implementation does not explicitly utilize prompt delimiters or 'ignore' instructions for the data being monitored, though this is typical for observability-focused skills.
- Capability inventory: The skill possesses network capabilities via the OpenTelemetry OTLP exporter and
httpxfor context propagation, along with structured logging to standard output. - Sanitization: The skill mitigates risks by including a comprehensive PII redaction module (
pii_redactor.py). This module uses regular expressions to scrub sensitive patterns including emails, SSNs, credit cards, JWTs, and API keys from all spans and logs before they are exported to external systems. - [SAFE]: The skill is designed with a strong security posture. It includes specific mechanisms for cost monitoring to prevent resource exhaustion (runaway loops) and implements data privacy controls (redaction) as a core feature rather than an afterthought.
Audit Metadata