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 adriannoes/awesome-agentic-ai --skill m365-entra-attackgit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/m365-entra-attack)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/m365-entra-attack"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/m365-entra-attack/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/adriannoes/awesome-agentic-ai/m365-entra-attack"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/m365-entra-attack.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 | $0.00128 | $0.05343 |
| Opus 5 | $0.00064 | $0.02671 |
| Sonnet 5 | $0.00026 | $0.01069 |
| Haiku 4.5 | $0.00013 | $0.00534 |
Grade A, and why
m365-entra-attack scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
import urllib.request, urllib.parse, ssl, time, json, os This is a copy
95% identical to m365-entra-attack — 35 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.
How it starts
The opening of the file, as written. The whole thing — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use this skill
Trigger when:
- Target uses M365 / Entra ID (autodiscover.* records, login.microsoftonline.com redirects, "Microsoft Office 365" in tech-stack notes)
- You have a list of corporate emails or stealer-leaked creds
- Engagement involves "credential spray", "password spray", "Entra attack", "ATO via M365"
- You see
*.onmicrosoft.com,*-my.sharepoint.com,enterpriseregistration.*,enterpriseenrollment.*in recon - Client mentions "Conditional Access", "MFA bypass", "compliant device"
DO NOT use for:
- On-prem-only Active Directory (use a separate AD-attack skill)
- Service-to-service token attacks (different threat model)
- Phishing-required attack chains (covered by phishing skills) — but you can prep for the credential-validation step here
Tenant discovery (msftrecon)
# For each owned domain
msftrecon -d client.example
msftrecon -d clientltd.example
msftrecon -d sister-brand-school.example
Key fields in output:
- Tenant ID (different domains may share OR have separate tenants — always test all owned domains)
- Federation Information.Namespace Type =
Managed(cloud-only, ROPC works) |Federated(ADFS, different attack) - SharePoint Detected (Yes = OneDrive enum vector available)
- Communication Services Teams/Skype (post-auth lateral targets)
- Admin Consent Endpoint accessible (consent-phishing surface)
Red flag: if the org has multiple Entra tenants for sister domains, each is a separate attack surface with its own user list, lockout policy, and CA configuration. Don't assume one spray covers all.
AADSTS code reference (memorize)
| AADSTS | Meaning | Lockout impact | What to do |
|---|---|---|---|
| 50034 | User does not exist | None | Skip; remove from spray list |
| 50126 | Invalid username/password | +1 attempt counter | User exists — try alternate password later (within cap) |
| 50053 | Account locked (Smart Lockout) | None (already locked) | Pre-existing → flag to SOC; don't retry |
| 53003 | CA blocked token issuance | +1 attempt counter | PASSWORD VALID — STOP, password is correct |
| 50076 | MFA required | +1 attempt counter | PASSWORD VALID — second factor needed |
| 50079 | Strong auth required | +1 attempt counter | PASSWORD VALID — same as 50076 |
| 50158 | External auth required | +1 attempt counter | PASSWORD VALID — federated MFA |
| 530003 | Device-state required | +1 attempt counter | PASSWORD VALID — needs compliant device |
| 65001 | Consent required | +1 attempt counter | App-consent issue, not auth |
| 700016 | App not in tenant | None | User in different tenant — adjust target |
| 90002 | Tenant does not exist | None | Tenant typo / dead tenant |
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.
- 9d ago First seen · 383 lines · 128 tokens per session scan A 2fee95fc5e58
m365-entra-attack is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 128 tokens to every session and 5,343 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 95% identical to m365-entra-attack, differing in 35 lines, and is treated as a copy.
Other skills, from other repositories
importing-a-codebase
Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced project (brainstorming).
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
brainstorming
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.