azure-monitor-ingestion-py
No security findings. Scanned 1 time, most recently 2026-02-05.
Second scanner: NVIDIA SkillSpector
SkillSpector found no issues but could not fully inspect the package, usually because SKILL.md refers to a file that is not present, so it fails closed to CAUTION instead of SAFE. Read it as "not fully checked", not as a finding. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API. Triggers: "azure-monitor-ingestion", "LogsIngestionClient", "custom logs", "DCR", "data collection rule", "Log Analytics".
- Package
- 2 files, 11 KB
- SKILL.md
- 532 words, 12+ sections
- Code
- None. Instructions only.
SKILL.md covers: Azure Monitor Ingestion SDK for Python · Installation · Environment Variables · Data Collection Endpoint (DCE) · Data Collection Rule (DCR) immutable ID · Stream name from DCR · Prerequisites · Authentication · Upload Custom Logs · Upload from JSON File · Custom Error Handling · Retry failed logs
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 5.3 KB |
references/acceptance-criteria.md | doc | 5.7 KB |
External hosts referenced
example.ingest.monitor.azure.us monitor.azure.us github.com my-dce.westus2.ingest.monitor.azure.com workspace-id.ods.opinsights.azure.com
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit cfbcbbdc679c. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Llm analyzer. A language model reads the skill and reports intent-level issues the rules cannot express.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
- Meta analyzer. A second model pass that validates, deduplicates and re-scores the other analyzers' findings.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/microsoft/agent-skills
- Raw scan result: github-skills-azure-monitor-ingestion-py-scan.json
- Badge for your README:
- Request a re-scan