LE MÉDIA DE L’IA QUI SERT VRAIMENT.Édition française · Comprendre & passer à l’action
Microsoft

Visualiser des résultats IRQL ou KQL sous forme de graphe

azure-kusto-irql-graph

En bref

Applique des fonctions graphe IRQL à des résultats de requêtes KQL ou IRQL, pour une visualisation dans Kusto Explorer : mappings Lift_To_Graph, vues Graph_Render_View, pliage par propriété, et enrichissements Extract_Node_* / Enrich_Graph_*. Elle accepte une requête fournie ou une demande source limitée en langage naturel ; le SKILL.md précise que ce n’est pas une skill générale de traduction langage naturel vers KQL ou IRQL. Pour une analyse make-graph native, un graph-match, des plus courts chemins, des composantes ou un graphe persistant, il faut utiliser azure-kusto-graph.

Ce que ça fait

  • Mappe des résultats de requête vers un graphe IRQL
  • Prépare la visualisation dans Kusto Explorer
  • Renvoie l’analyse make-graph vers azure-kusto-graph

Pour qui, et un exemple

Les analystes qui ont déjà une requête KQL ou IRQL et veulent en visualiser les résultats sous forme de graphe.

Exemple de demande : « À partir de cette requête IRQL, produis un mapping Lift_To_Graph et une vue Graph_Render_View. »

On l’utilise pour Lift_To_Graph, Graph_Render_View, l’enrichissement graphe IRQL ou le mapping de résultats de requête déjà disponibles, et non pour une analyse make-graph générale. Exemple rédigé par iadujour.fr à partir du SKILL.md, non testé.

Installer

npx skills add microsoft/skills (sélection de la skill dans l’assistant, README).

npx skills add microsoft/skills

Fonctionne avec

  • GitHub Copilot
  • Copilot CLI

Source : README : exemples de « Copilot CLI » et « GitHub Copilot in VS Code » ; l’installation `npx skills add` envoie les fichiers vers le répertoire de l’agent choisi, sans liste exhaustive.

Niveau : Intermédiaire

Suppose un projet déjà en place chez l’éditeur et les outils décrits dans le SKILL.md.

À savoir

Dépôt officiel Microsoft ; le README le présente comme un travail en cours (skills et tests encore enrichis).

Extrait du SKILL.md

La description d’origine, celle que l’agent lit pour décider de charger la skill (en anglais) :

Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, […]

Citée depuis le SKILL.md au commit 4d0badd . Le dossier contient aussi 3 fichiers annexes (references/).

Le SKILL.md compte 291 lignes et 25 sections principales :

  • Scope and Routing
  • Input Contract
  • Activation Triggers
  • Environment
  • Function Preflight
  • IRQL Graph Function Family
  • `Lift_To_Graph(T, mappingJson)`
  • `Graph_Render_View(T)`
  • `Graph_Fold_By_Property(T, NodeType, PropertyName)`
  • Graph Extraction and Enrichment Functions
  • Mapping JSON Schema
  • `node_types[]`
  • `edges[]`
  • Icon Repository
  • Mapping Generation Rules
  • Column Reference (IRQL unified schema)
  • Function Selection
  • Pipeline Pattern
  • Examples
  • Authentication graph: IP -> AuthEvent -> User -> Host
  • Email graph: Sender -> Message -> Recipient
  • Suspicious domain investigation (end-to-end)
  • Process execution graph: User -> Process -> ParentProcess
  • Query Results -> Mapping Translation
  • Opening Queries in Kusto Explorer (Windows Only)

Licence : MIT

Vérifiée le 10 novembre 2026 sur : fichier de licence d’un dossier parent (.github/plugins/azure-kusto-graph-skills/LICENSE) . Licence déclarée dans le frontmatter : « MIT ». Titulaire : Copyright 2025 (c) Microsoft Corporation..

La licence autorise la reprise : le texte intégral du SKILL.md est reproduit ci-dessous, sans modification, avec sa mention de licence.

Texte intégral du SKILL.md

Reproduit sans modification depuis microsoft/skills (commit 4d0badd) , © Microsoft, sous licence MIT (fichier de licence d’origine ).

Afficher le SKILL.md original (291 lignes, en anglais)
---
name: azure-kusto-irql-graph
description: "Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, Graph_Render_View, Graph_Fold_By_Property, IRQL graph enrichment, graph mapping for existing query results, icon-decorated graph, fold graph nodes. Use azure-kusto-graph for native make-graph analysis, graph-match, shortest paths, components, or persistent graphs."
license: MIT
metadata:
  author: Microsoft
  version: "1.2.1"
---

# IRQL Graph Functions -- Query Results to Visualization

Apply the IRQL graph function family to tabular results. Given a KQL or IRQL query and the user's graph description, generate a `Lift_To_Graph` mapping and compose only the stored graph functions needed to visualize, fold, extract, or enrich the graph in Kusto Explorer. The source query does not need to use IRQL.

## Scope and Routing

| Request | Use |
|---|---|
| Turn supplied KQL/IRQL rows into an icon-decorated visual graph | This skill: `Lift_To_Graph` + `Graph_Render_View` |
| Fold nodes or apply `Extract_Node_*`, `Enrich_Node_*`, or `Enrich_Graph_*` | This skill |
| Use `make-graph`, `graph-match`, shortest paths, connected components, graph models, or snapshots | `azure-kusto-graph` |
| Author a non-trivial KQL/IRQL investigation from natural language | A Kusto or IRQL query-generation skill, then this skill |

If a request mixes visualization and native graph analysis, use this skill for the lift/render portion and `azure-kusto-graph` for operator semantics. Do not replace graph-lift functions with a hand-built edges-first graph unless the user asks for native graph operators.

## Input Contract

- **Preferred input**: a working KQL/IRQL query that produces tabular results, plus a natural-language description of the desired nodes, edges, labels, icons, extracts, enrichments, or folds.
- This skill is **not a natural-language-to-KQL or NL-to-IRQL converter**. It transforms existing query results into graph visualizations. For general NL-to-KQL or NL-to-IRQL conversion, use a dedicated query-generation skill (available separately).
- Preserve the supplied query's retrieval, joins, filters, and aggregations. Add only projections or synthetic IDs required by the graph mapping.
- A basic natural-language source request is supported only when it maps directly to one known table or IRQL `Get_*` selector with obvious columns and simple filters. State the assumed source, and do not invent joins, schema, or investigation logic.
- For non-trivial query construction, use a separate Kusto/IRQL query-generation skill first, then apply this skill to its output.
- If no query or output schema is available and the source is not trivial, request the KQL query or its result columns before generating a mapping.

## Activation Triggers

Use this skill when the user:
- Supplies KQL/IRQL results and asks for an IRQL graph visualization or mapping
- Mentions `Lift_To_Graph`, `Graph_Render_View`, or `Graph_Fold_By_Property`
- Asks for icon-decorated node/edge mappings in Kusto Explorer
- Wants to fold/collapse nodes by a shared property
- Requests graph extraction or enrichment through `Extract_Node_*`, `Enrich_Node_*`, or `Enrich_Graph_*`

Do not activate this skill solely for `graph-match`, graph paths/components, persistent graphs, or generic `make-graph` construction; those belong to `azure-kusto-graph`.

**Not a natural-language-to-KQL/IRQL converter.** The input should generally be a working KQL or IRQL query whose results need graph visualization. Basic NL source requests work only for trivial single-table/selector cases. For general NL-to-KQL or NL-to-IRQL, use a dedicated query-generation skill (available separately).

## Environment

- **Cluster**: `https://kc7001.eastus.kusto.windows.net`
- **Databases**: `ValdyTimes`, `JoJosHospital` (graph functions pre-deployed)
- **Rendering**: Kusto Explorer desktop app (make-graph visualization window)
- **Tool**: `kusto_query` (via Azure MCP Server)

### Function Preflight

`Lift_To_Graph` and `Graph_Render_View` are stored functions, not built-in Kusto operators. Before generating or running a lift pipeline against a target database, check what is deployed:

```kql
.show functions
| where Name in~ ("Lift_To_Graph", "Graph_Render_View", "Graph_Fold_By_Property")
| project Name
```

- `Lift_To_Graph` and `Graph_Render_View` are required.
- `Graph_Fold_By_Property` is required only when folding is requested.
- Check any `Extract_Node_*`, `Enrich_Node_*`, or `Enrich_Graph_*` function before using it; omit optional enrichment when unavailable unless the user wants it deployed.
- If a required function is missing and you have permission to alter the database, **ask the user for confirmation before deploying**. Then use the `.create-or-alter function` definitions in [references/DEPLOY_IRQL_FUNCTIONS.md](references/DEPLOY_IRQL_FUNCTIONS.md). Run the relevant `.create-or-alter` block, then rerun the preflight check to confirm.
- If you do not have alter permissions, tell the user which functions are missing and point them to `references/DEPLOY_IRQL_FUNCTIONS.md` for manual deployment.

## IRQL Graph Function Family

### `Lift_To_Graph(T, mappingJson)`

Transforms any tabular KQL result into a unified node + edge table.

**Input**: Any table `T` + a JSON mapping string.
**Output**: Rows with `EntityType` = `"node"` or `"edge"`, ready for `make-graph`.

### `Graph_Render_View(T)`

Takes `Lift_To_Graph` output, splits nodes/edges, and calls `make-graph` to open Kusto Explorer's graph window.

### `Graph_Fold_By_Property(T, NodeType, PropertyName)`

Collapses nodes of a given type sharing a property value into a single node. Rewires edges automatically.

### Graph Extraction and Enrichment Functions

These are additional stored functions that must already be deployed on the target database. They are **not** bundled in `references/DEPLOY_IRQL_FUNCTIONS.md`. Use `.show functions` to verify availability before including in a pipeline.

| Function | Operation | Key Property |
|---|---|---|
| `Extract_Node_Email_Sender_Domain(T, displayName)` | Adds `Domain` to node props | `EmailSender` |
| `Extract_Node_Employee_Firstname(T, displayName)` | Adds `Firstname` to node props | `Name` |
| `Extract_Node_Event_Network_Domain(T, displayName)` | Adds `DomainName` to node props | `Url` |
| `Enrich_Node_Ip_Employee(T, displayName)` | Adds employee info to IP nodes | `ClientIp` |
| `Enrich_Node_Username_Employee(T, displayName)` | Adds employee info to user nodes | `Username` |
| `Enrich_Node_Event_Authentication_Username(T, displayName)` | Adds auth context | `Username` |
| `Enrich_Node_Ip_Domain(T, displayName)` | Adds DNS domains | `ClientIp` |
| `Enrich_Node_Ip_Event_NetworkOutbound(T, displayName)` | Adds outbound events | `ClientIp` |
| `Enrich_Graph_Ip_Employee(T, mappingJson)` | Expands graph with employee nodes | `ClientIp` |
| `Enrich_Graph_Username_Employee(T, mappingJson)` | Expands graph with employee nodes | `Username` |
| `Enrich_Graph_Event_Authentication_Username(T, mappingJson)` | Expands with auth nodes | `Username` |

## Mapping JSON Schema

The JSON mapping has two arrays: `node_types` and `edges`.

### `node_types[]`

| Field | Required | Description |
|---|---|---|
| `type` | Yes | Node type label (e.g. `"User"`, `"Host"`, `"IP"`) |
| `id` | Yes | Prefix for node ID; usually same as type |
| `key` | Yes | Column name whose value becomes the node's identity |
| `props` | Yes | Array of columns to carry as node properties |
| `defaults` | No | Object of fallback values for null/empty properties |
| `defIcon` | No | Default icon URL for this node type |
| `displayName` | No | Column to use for display label (defaults to `id`) |
| `color` | No | Column to source color from |
| `size` | No | Column to source size from |

### `edges[]`

| Field | Required | Description |
|---|---|---|
| `type` | Yes | Edge type label (e.g. `"AuthenticatesTo"`, `"SentEmail"`) |
| `source` | Yes | `{"id": "<prefix>", "type": "<NodeType>"}` |
| `target` | Yes | `{"id": "<prefix>", "type": "<NodeType>"}` |
| `props` | No | Array of columns to carry as edge properties |
| `displayName` | No | Column for edge label |
| `color` | No | Column for edge color |

### Icon Repository

Use icons from `https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/`:
- IP: `Public-IP-Addresses-(Classic).svg`
- Host/VM: `Virtual-Machine.svg`
- User: `Users.svg`
- Email: `Mailbox.svg` (or `azure-cds/command-1070-Mail.svg`)
- Process: `App-Services.svg`
- File: `Storage-Accounts.svg`
- Alert: `Activity-Log.svg`
- Domain: `DNS-Zones.svg`

## Mapping Generation Rules

Given the supplied query columns and the user's graph description, generate the mapping JSON by:

1. **Identify entities** -> each distinct noun becomes a `node_type`
2. **Identify relationships** -> each verb/preposition becomes an `edge`
3. **Map to columns** -> use actual columns produced by the supplied query; never assume unavailable columns
4. **Set direction** -> source is the actor, target is the acted-upon
5. **Add properties** -> include columns relevant to investigation (timestamps, results, hashes)
6. **Assign icons** -> pick from the icon set above based on entity type

### Column Reference (IRQL unified schema)

| Entity | Key Column | Available Props |
|---|---|---|
| User | `Username` | `Username`, `Name`, `Role`, `Email` |
| Host | `Hostname` | `Hostname` |
| IP | `ClientIp` | `ClientIp` |
| Email Message | `Subject` | `EnvTime`, `Subject`, `Verdict`, `Url` |
| Sender | `EmailSender` | `EmailSender`, `Domain` |
| Recipient | `EmailRecipient` | `EmailRecipient` |
| Process | `ProcessName` | `EnvTime`, `ProcessName`, `ProcessCommandLine`, `ProcessHash` |
| File | `Filename` | `EnvTime`, `Filename`, `Path`, `Sha256` |
| Domain | `DomainName` | `DomainName` |
| Auth Event | (synthetic ID) | `EnvTime`, `UserAgent`, `Result`, `Description` |

## Function Selection

1. Start with the supplied KQL/IRQL tabular pipeline.
2. Use `Lift_To_Graph(mapping)` to create graph entities.
3. Add `Extract_Node_*`, `Enrich_Node_*`, or `Enrich_Graph_*` only when requested and compatible with the mapped keys.
4. Add `Graph_Fold_By_Property()` only when grouping/collapse is requested.
5. End visual output with `Graph_Render_View()`.
6. Preflight the exact stored functions selected for the pipeline.

## Pipeline Pattern

```kql
// 1. Preserve the supplied KQL or IRQL query
<input query>
// 2. Lift to graph
| invoke Lift_To_Graph(<mapping_json>)
// 3. Optionally extract or enrich graph entities
| invoke <Extract_Node_* | Enrich_Node_* | Enrich_Graph_*>()
// 4. Optionally fold nodes when requested
| invoke Graph_Fold_By_Property("<NodeType>", "<PropertyName>")
// 5. Render
| invoke Graph_Render_View()
```

## Examples

For additional prompts and worked examples, see [references/EXAMPLES.md](references/EXAMPLES.md).

### Authentication graph: IP -> AuthEvent -> User -> Host

**Input query**: `Get_Event_Authentication_All | where Result == "Failed Login" | take 200`

**Graph request**: "Show IPs, authentication events, users, and hosts; fold events by result."

```kql
let auth_mapping = '{"node_types":[{"type":"SrcIp","id":"SrcIp","key":"ClientIp","props":["ClientIp"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Public-IP-Addresses-(Classic).svg"},{"type":"Host","id":"Host","key":"Hostname","props":["Hostname"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Virtual-Machine.svg"},{"type":"User","id":"User","key":"Username","props":["Username"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Users.svg"},{"type":"AuthEvent","id":"AuthEvent","key":"AuthEventId","props":["AuthEventId","EnvTime","UserAgent","Result","Description"],"defaults":{"Result":"unknown"},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Activity-Log.svg"}],"edges":[{"type":"RequestsAuth","source":{"id":"SrcIp","type":"SrcIp"},"target":{"id":"AuthEvent","type":"AuthEvent"},"props":["EnvTime"]},{"type":"TargetsUser","source":{"id":"AuthEvent","type":"AuthEvent"},"target":{"id":"User","type":"User"},"props":["EnvTime"]},{"type":"AgainstHost","source":{"id":"AuthEvent","type":"AuthEvent"},"target":{"id":"Host","type":"Host"},"props":["EnvTime"]}]}';
Get_Event_Authentication_All
| extend AuthEventId = strcat(Username, "_", Hostname, "_", EnvTime)
| where Result == "Failed Login"
| take 200
| invoke Lift_To_Graph(auth_mapping)
| invoke Graph_Fold_By_Property("AuthEvent", "Result")
| invoke Graph_Render_View()
```

### Email graph: Sender -> Message -> Recipient

**Input query**: `Get_Email_All | take 400`

**Graph request**: "Visualize sender-to-message-to-recipient flow and fold messages by verdict."

```kql
let mail_mapping = '{"node_types":[{"type":"EmailMessage","id":"Message","key":"Subject","props":["EnvTime","Subject","Verdict"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Media-File.svg"},{"type":"Sender","id":"Email","key":"EmailSender","props":["EmailSender"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-cds/command-1070-Mail.svg"},{"type":"Recipient","id":"Email","key":"EmailRecipient","props":["EmailRecipient"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-cds/command-1070-Mail.svg"}],"edges":[{"type":"SentBy","source":{"id":"Message","type":"EmailMessage"},"target":{"id":"Email","type":"Sender"},"props":["EnvTime","Verdict"]},{"type":"DeliveredTo","source":{"id":"Message","type":"EmailMessage"},"target":{"id":"Email","type":"Recipient"},"props":["EnvTime","Verdict"]}]}';
Get_Email_All
| take 400
| invoke Lift_To_Graph(mail_mapping)
| invoke Graph_Fold_By_Property("EmailMessage", "Verdict")
| invoke Graph_Render_View()
```

### Suspicious domain investigation (end-to-end)

**Basic source request**: "Use outbound network events for these suspicious domains and graph IP-to-domain connections enriched with employee names."

This is the limited fallback: one known selector, one extractor, and one direct filter.

```kql
let suspicious_domain_mapping = '{"node_types":[{"type":"IP","id":"IP","key":"ClientIp","props":["ClientIp"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Public-IP-Addresses-(Classic).svg"},{"type":"Domain","id":"Domain","key":"DomainName","props":["DomainName"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/DNS-Zones.svg"}],"edges":[{"type":"ConnectsTo","source":{"id":"IP","type":"IP"},"target":{"id":"Domain","type":"Domain"},"props":["EnvTime"]}]}';
Get_Event_NetworkOutbound
| invoke Extract_Event_Network_Domain()
| where DomainName has_any ("raisinkanes.com", "nothing-to-see-here.net", "totally-legit-domain.com")
| invoke Lift_To_Graph(suspicious_domain_mapping)
| invoke Enrich_Node_Ip_Employee("Name")
| invoke Graph_Fold_By_Property("Domain", "DomainName")
| invoke Graph_Render_View()
```

### Process execution graph: User -> Process -> ParentProcess

**Input query**: `Get_Event_Process_All | where ProcessCommandLine has "powershell" | take 300`

**Graph request**: "Visualize process, parent process, host, and user relationships."

```kql
let proc_mapping = '{"node_types":[{"type":"Process","id":"Proc","key":"ProcessName","props":["ProcessName","ProcessCommandLine","ProcessHash"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/App-Services.svg"},{"type":"ParentProcess","id":"Proc","key":"ParentProcessName","props":["ParentProcessName","ParentProcessHash"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/App-Services.svg"},{"type":"Host","id":"Host","key":"Hostname","props":["Hostname"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Virtual-Machine.svg"},{"type":"User","id":"User","key":"Username","props":["Username"],"defaults":{},"defIcon":"https://raw.githubusercontent.com/benc-uk/icon-collection/master/azure-icons/Users.svg"}],"edges":[{"type":"SpawnedBy","source":{"id":"Proc","type":"Process"},"target":{"id":"Proc","type":"ParentProcess"},"props":["EnvTime"]},{"type":"RanOn","source":{"id":"Proc","type":"Process"},"target":{"id":"Host","type":"Host"},"props":["EnvTime"]},{"type":"ExecutedBy","source":{"id":"Proc","type":"Process"},"target":{"id":"User","type":"User"},"props":["EnvTime"]}]}';
Get_Event_Process_All
| where ProcessCommandLine has "powershell"
| take 300
| invoke Lift_To_Graph(proc_mapping)
| invoke Graph_Render_View()
```

## Query Results -> Mapping Translation

When the user supplies a query and describes the graph:

1. Inspect the query's final output columns
2. Parse the entity nouns and relationship verbs
3. Generate the mapping JSON using only those columns
4. Preserve the supplied pipeline and append `Lift_To_Graph()`
5. Include `Graph_Render_View()` at the end
6. If the user mentions grouping/collapsing and the function exists, add `Graph_Fold_By_Property()`

Output the complete KQL -- the supplied query plus mapping JSON inline as a string `let` binding -- after the required-function preflight passes. Clearly mark unverified function dependencies when the target database cannot be checked.

## Opening Queries in Kusto Explorer (Windows Only)

> **Optional convenience feature.** The default workflow is to output the KQL in chat and let the user copy it into Kusto Explorer or the VS Code Kusto extension manually. Auto-launch is opt-in only.

Always output the complete KQL query in the chat response with Step 1 (connect) and Step 2 (query) clearly labeled:

```
// Step 1: Connect to your cluster (skip if already connected)
// Example: uncomment to connect to the KC7 training cluster
// #connect cluster('kc7001.eastus.kusto.windows.net').database('ValdyTimes')
// Or replace with your own cluster:
// #connect cluster('<YOUR_CLUSTER>').database('<YOUR_DATABASE>')

// Step 2: Run the query below
<KQL_QUERY>
```

If the user asks to save or open in Kusto Explorer, follow the procedure in [references/KUSTO_EXPLORER_LAUNCH.md](references/KUSTO_EXPLORER_LAUNCH.md). Key rules:

- Use `ask_user` to confirm before writing files or launching executables
- Display file contents in chat so the user can review before opening
- Never use shell interpolation or here-strings — write files via `Set-Content`/`Add-Content`
- Never encode queries into browser URLs
- On macOS/Linux, save the `.kql` file and suggest the VS Code Kusto extension or ADX Web Explorer
Source. Fiche rédigée par iadujour.fr à partir de : Frontmatter, sections et corps du SKILL.md, README du dépôt. Consultée le 10 novembre 2026. Dépôt : microsoft/skills .
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