azure-monitor-opentelemetry-py

The skill azure-monitor-opentelemetry-py primarily consists of markdown documentation and Python code snippets demonstrating how to use the azure-monitor-opentelemetry library.

1. Prompt Injection: No patterns indicative of prompt injection were found in the skill's description or content. The language is instructional and benign.

2. Data Exfiltration: The core function of the azure-monitor-opentelemetry library is to collect and send telemetry data (traces, metrics, logs) to Azure Application Insights. This is its intended purpose, not malicious data exfiltration. The skill instructs users to provide a connection string, ideally via environment variables, which is a recommended security practice for sensitive information. There are no commands to read or exfiltrate arbitrary sensitive local files (e.g., ~/.aws/credentials, ~/.ssh/id_rsa).

3. Obfuscation: No obfuscated content (Base64, zero-width characters, homoglyphs, URL/hex/HTML encoding) was detected in either SKILL.md or references/acceptance-criteria.md.

4. Unverifiable Dependencies: The skill instructs pip install azure-monitor-opentelemetry. This is an external dependency. However, the references/acceptance-criteria.md file explicitly links to the GitHub repository https://github.com/Azure/azure-sdk-for-python, which is under the Azure organization. Azure is listed as a trusted GitHub organization. Therefore, this external dependency is considered low risk, and the finding is downgraded to INFO.

5. Privilege Escalation: No commands like sudo, chmod +x, chmod 777, or other privilege escalation attempts were found.

6. Persistence Mechanisms: No attempts to establish persistence (e.g., modifying .bashrc, crontab, authorized_keys) were detected.

7. Metadata Poisoning: The skill's metadata (name, description) is clean and accurately reflects its purpose.

8. Indirect Prompt Injection: The skill itself does not process external, untrusted user input in a way that would lead to indirect prompt injection for an LLM. It configures a Python library.

9. Time-Delayed / Conditional Attacks: No conditional logic or time-based triggers for malicious behavior were found.

Adversarial Reasoning: The skill's instructions are straightforward and align with the stated purpose of integrating with Azure Monitor. The use of a trusted, well-known SDK from a major vendor significantly reduces the risk associated with external dependencies and data transmission. The recommendation to use environment variables for the connection string further enhances security. The analysis concludes that the skill is safe for use, as its operations are transparent and from a trusted source.