detecting-azure-lateral-movement

detecting-azure-lateral-movement is a skill for Claude Code, Codex from xalgorix/xalgorix. It costs 54 tokens per session (950 once invoked), scanned A, original, Apache-2.0.

A guide to detecting lateral movement in Azure identity systems, where an attacker moves from one account, application, or tenant to another. It correlates Microsoft Graph, sign-in, and Microsoft Sentinel logs.

In plain words
What is it for?
Writing Sentinel KQL detections, investigating token theft and privilege changes, and tracing suspicious movement across Azure environments.
Why use it?
It helps find attacks that use application consent, stolen tokens, delegated access, or cross-tenant connections instead of traditional network access.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Writing Sentinel KQL detections, investigating token theft and privilege changes, and tracing suspicious movement across Azure environments.

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Install with agentmods
npx agentmods add skills/xalgorix/xalgorix/detecting-azure-lateral-movement
Install

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.

Any agent
npx skills add xalgorix/xalgorix --skill detecting-azure-lateral-movement
Clone the repo
git clone --depth 1 https://github.com/xalgorix/xalgorix

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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Your own site
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Your own site · 80×15
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Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 950 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.00950
Opus 5 $0.00027 $0.00475
Sonnet 5 $0.00011 $0.00190
Haiku 4.5 $0.00005 $0.00095

Measured 7d ago against content hash 993221d49b68, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

detecting-azure-lateral-movement 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 7d 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.

internal/tools/skills/data/cloud-security/detecting-azure-lateral-movement/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Detecting Azure Lateral Movement

Overview

Lateral movement in Azure AD/Entra ID differs from on-premises environments. Attackers pivot through OAuth application consent grants, service principal abuse, cross-tenant access policies, and stolen refresh tokens rather than SMB/RDP connections. Detection requires correlating Microsoft Graph API audit logs, Azure AD sign-in logs, and Entra ID protection risk events using KQL queries in Microsoft Sentinel. This skill covers building detection analytics for common Azure lateral movement techniques including application impersonation, mailbox delegation abuse, and conditional access policy bypasses.

When to Use

  • When investigating security incidents that require detecting azure lateral movement
  • 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

Detection Gaps & Validation

Common evasions / false-negatives that defeat these KQL analytics:

  • Watching only SigninLogs. Refresh-token and PRT replay land in AADNonInteractiveUserSignInLogs; app-only pivots land in AADServicePrincipalSignInLogs. Interactive-only queries miss both.
  • Cross-tenant B2B pivots show ResultType == 0 with ResourceTenantId != HomeTenantId — filter on the tenant mismatch, not just location.
  • Mailbox delegation abuse (Add-MailboxPermission FullAccess/SendAs, Add delegated permission grant) is in the Office 365 / Exchange audit feed, not Entra AuditLogs.
  • Credential-add detail is buried in TargetResources[0].modifiedProperties[*].newValue (KeyDescription / KeyType) — keying only on OperationName misses cert-based persistence.

Validate the rule actually fires:

union withsource=Tbl AADNonInteractiveUserSignInLogs, AADServicePrincipalSignInLogs, SigninLogs
| summarize rows=count() by Tbl   // any 0 = diagnostic setting missing, rule is silently dead
  • Tune FP by baselining each service principal's sign-in IP/location over 14+ days before alerting on "new" location, and exclude managed-identity object IDs and known automation egress IPs.

Read the full file on GitHub · 94 lines

Changes

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.

  1. 7d ago First seen · 94 lines · 54 tokens per session scan A 993221d49b68

Subscribe to this mod's changes

detecting-azure-lateral-movement is a skill published in the GitHub repository xalgorix/xalgorix (972 stars, last pushed yesterday), licensed Apache-2.0. It adds 54 tokens to every session and 950 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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