Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add marysatasselshaped667/skills-collection-1 --skill analyzing-azure-activity-logs-for-threatsgit clone --depth 1 https://github.com/marysatasselshaped667/skills-collection-1Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/marysatasselshaped667/skills-collection-1/analyzing-azure-activity-logs-for-threats)<a href="https://agentmods.dev/skills/marysatasselshaped667/skills-collection-1/analyzing-azure-activity-logs-for-threats"><img src="https://agentmods.dev/badge/skills/marysatasselshaped667/skills-collection-1/analyzing-azure-activity-logs-for-threats/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/marysatasselshaped667/skills-collection-1/analyzing-azure-activity-logs-for-threats"><img src="https://agentmods.dev/badge/skills/marysatasselshaped667/skills-collection-1/analyzing-azure-activity-logs-for-threats.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00464 |
| Opus 5 | $0.00034 | $0.00232 |
| Sonnet 5 | $0.00014 | $0.00093 |
| Haiku 4.5 | $0.00007 | $0.00046 |
Grade A, and why
analyzing-azure-activity-logs-for-threats scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to analyzing-azure-activity-logs-for-threats — 28 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Analyzing Azure Activity Logs for Threats
When to Use
- When investigating security incidents that require analyzing azure activity logs for threats
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Familiarity with security operations concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Instructions
Use azure-monitor-query to execute KQL queries against Azure Log Analytics workspaces, detecting suspicious admin operations and sign-in anomalies.
from azure.identity import DefaultAzureCredential
from azure.monitor.query import LogsQueryClient
from datetime import timedelta
credential = DefaultAzureCredential()
client = LogsQueryClient(credential)
response = client.query_workspace(
workspace_id="WORKSPACE_ID",
query="AzureActivity | where OperationNameValue has 'MICROSOFT.AUTHORIZATION/ROLEASSIGNMENTS/WRITE' | take 10",
timespan=timedelta(hours=24),
)
Key detection queries:
- Role assignment changes (privilege escalation)
- Resource group and subscription modifications
- Key vault secret access from new IPs
- Network security group rule changes
- Conditional access policy modifications
Examples
# Detect new Global Admin role assignments
query = '''
AuditLogs
| where OperationName == "Add member to role"
| where TargetResources[0].modifiedProperties[0].newValue has "Global Administrator"
'''
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 70 lines · 68 tokens per session scan A d4b124688bf2
analyzing-azure-activity-logs-for-threats is a skill published in the GitHub repository marysatasselshaped667/skills-collection-1 (1 stars, last pushed yesterday), licensed MIT. It adds 68 tokens to every session and 464 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to analyzing-azure-activity-logs-for-threats, differing in 28 lines, and is treated as a copy.
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analyzing-azure-activity-logs-for-threats
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