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[DOCS-11464] doc for new Users explorer #30842

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DOCS-11464

New topic covering the new Users explorer for App and API Protection.

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  • Ready for merge

@michaelcretzman michaelcretzman self-assigned this Jul 31, 2025
@michaelcretzman michaelcretzman requested a review from a team as a code owner July 31, 2025 22:33
@michaelcretzman michaelcretzman added the editorial review Waiting on a more in-depth review label Jul 31, 2025
@github-actions github-actions bot added the Architecture Everything related to the Doc backend label Jul 31, 2025
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github-actions bot commented Jul 31, 2025

📝 Documentation Team Review Required

This pull request requires approval from the @DataDog/documentation team before it can be merged.

Please ensure your changes follow our documentation guidelines and wait for a team member to review and approve your changes.

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## Overview

Datadog App and API Protection identifies users as risks when one or more signals is associated with a user ID, email, or name.
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The Users explorer includes all users that are associated with security traces, not signals. There are multiple ways customers can associate a user to a trace: https://docs.datadoghq.com/security/application_security/how-it-works/add-user-info/?tab=java#adding-authenticated-user-information-to-traces-and-enabling-user-blocking-capability

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Users are identified by the @usr.id. When they are available, we also display the user name and e-mail.

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Users aren't a risk in themselves, or at least not generally. Some risks are about the user being under attack (for instance, attempts to compromise them) where they're the victim

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Also, if we're tracking traces, then any login attempt will cause a user to show up in there. In this case, the explorer becomes a user inventory (we then want to discourage a heavy handed approach to block any user in the explorer)

- **Signal explorer**: Provides a list of actionable alerts such as Credential Stuffing Attack or Command Injection. Signals have workflow capabilities, a description, severity, and correlated Traces. Interactions include user assignment workflows, automated protection, analytics, search, and pivoting to Trace Explorer.
- **Trace explorer**: List of evidence for business logic events, such as logins, or attack payloads. Interactions include analytics and search.
- **Attackers explorer**: Identifies attackers as suspicious (IP addresses that have attacked in the last 24 hours up to a threshold) and flagged (IP addresses that have exceeded that threshold).
- **Users explorer**: List of authenticated users associated with one or more signals. Interactions include:
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Suggested change
- **Users explorer**: List of authenticated users associated with one or more signals. Interactions include:
- **Users explorer**: List of authenticated users associated with one or more traces. Interactions include:

Comment on lines 109 to 124
### Threat Intel Category

**Benefit:** Shows the associated [Threat Intelligence Category][5].

Comparing helps you:
* Understand the vector of compromise.
* Prioritize responses (for example, `hosting_proxy` might require different mitigation than `malware`).

### Threat Intel Intention

**Benefit:** Clarifies **why the attacker stole the credentials** (fraud, espionage, resale, lateral movement, etc.).

Matching intentions reveal:
* Common attacker **goals**.
* Whether your users were part of a **targeted vs opportunistic** campaign.
* Whether you should expect **further action**, like BEC (business email compromise) or internal movement.
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All the threat intel information provide insights about the attacker IPs reputation.

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Aligned, flagged IPs aren't necessarily bad, they're just known to sometimes be misused (often without the user knowing in case of residential_proxy) and worth paying closer attention to

The Users explorer assigns one or more of the following risk categories to a user identified as a risk:

- **New Geolocation:** User activity from an unfamiliar location might signal unauthorized access or legitimate travel requiring verification.
- **Impossible Travel:** Occurs when a user logs in from two distant locations in an unrealistically short time, indicating possible credential compromise.
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Worth highlighting that this sometimes misfire in case users are leveraging VPNs


Comparing helps you:
* Understand the vector of compromise.
* Prioritize responses (for example, `hosting_proxy` might require different mitigation than `malware`).
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Not really, maybe a better exemple would be corp_vpn (which are IPs used by businesses) and hosting_proxy which is almost exclusively malicious

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Looks good! Just left a few minor suggestions. 🚀

@@ -0,0 +1,178 @@
---
title: Users Explorer
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Just a general note that there is inconsistent capitalization for these explorers. For example, Attackers Explorer is all uppercase on its dedicated page.

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incorp peer edit

Co-authored-by: Brett Blue <[email protected]>
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