dd-audit-security-investigation

dd-audit-security-investigation is a skill for Claude Code, Codex from datadog-labs/agent-skills. It costs 39 tokens per session (1,468 once invoked), scanned A, original, MIT.

A Datadog Audit Trail guide for investigating security-related activity. Audit Trail is a record of actions such as deletions, configuration changes, logins, and permission updates.

In plain words
What is it for?
Use it to investigate deletions, changes to a particular resource, activity by a user or IP address, unusual locations, bulk actions, and off-hours events.
Why use it?
It turns broad security questions like “who changed this?” into targeted searches with a defined person, resource, action, or time window.

Skill for Claude CodeCodex

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

Good fit Use it to investigate deletions, changes to a particular resource, activity by a user or IP address, unusual locations, bulk actions, and off-hours events.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/datadog-labs/agent-skills/security-investigation
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 datadog-labs/agent-skills --skill security-investigation
Clone the repo
git clone --depth 1 https://github.com/datadog-labs/agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for dd-audit-security-investigation

README.md
[![agentmods](https://agentmods.dev/badge/skills/datadog-labs/agent-skills/security-investigation/github.svg)](https://agentmods.dev/skills/datadog-labs/agent-skills/security-investigation)
Your own site
<a href="https://agentmods.dev/skills/datadog-labs/agent-skills/security-investigation"><img src="https://agentmods.dev/badge/skills/datadog-labs/agent-skills/security-investigation/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.

agentmods 80×15 button for dd-audit-security-investigation

Your own site · 80×15
<a href="https://agentmods.dev/skills/datadog-labs/agent-skills/security-investigation"><img src="https://agentmods.dev/badge/skills/datadog-labs/agent-skills/security-investigation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,468 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 $0.00039 $0.01468
Opus 5 $0.00019 $0.00734
Sonnet 5 $0.00008 $0.00294
Haiku 4.5 $0.00004 $0.00147

Measured 11d ago against content hash 7470b7730af8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

dd-audit-security-investigation 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 11d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

dd-audit/security-investigation/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audit Trail: Security Investigation

Answer common security investigation questions using pup audit-logs.

Prerequisites

pup auth login   # OAuth2 (recommended)
# or set DD_API_KEY + DD_APP_KEY with audit_logs_read scope

Command Execution Order

  1. Clarify the investigation scope: who, what resource type, what time window.
  2. Run the most specific query first; broaden only if results are empty.
  3. If results are large, pipe to jq to group or summarize.
  4. Highlight anomalies: bulk operations, unusual geo, off-hours activity, support user actions.

Common Investigation Queries

Who deleted resources in a time window?

pup audit-logs search --query "@action:deleted" --from 24h -o json \
  | jq '[.data[] | {
      timestamp: .attributes.timestamp,
      user: .attributes.attributes.usr.email,
      actor_type: .attributes.attributes.evt.actor.type,
      resource_type: .attributes.attributes.asset.type,
      resource_id: .attributes.attributes.asset.id,
      country: .attributes.attributes.network.client.geoip.country.name
    }]'

Who modified a specific resource (by ID)?

pup audit-logs search --query "@asset.id:RESOURCE_ID" --from 7d -o json \
  | jq '[.data[] | {
      timestamp: .attributes.timestamp,
      user: .attributes.attributes.usr.email,
      action: .attributes.attributes.action,
      event: .attributes.attributes.evt.name
    }]'

What did a specific user do?

pup audit-logs search --query "@usr.email:[email protected]" --from 7d --limit 200 -o json \
  | jq '[.data[] | {
      timestamp: .attributes.timestamp,
      action: .attributes.attributes.action,
      event: .attributes.attributes.evt.name,
      resource_type: .attributes.attributes.asset.type,
      resource_id: .attributes.attributes.asset.id,
      ip: .attributes.attributes.network.client.ip,
      country: .attributes.attributes.network.client.geoip.country.name
    }]'

Login activity — all logins with geo

Read the full file on GitHub · 171 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. 11d ago First seen · 171 lines · 39 tokens per session scan A 7470b7730af8

Subscribe to this mod's changes

dd-audit-security-investigation is a skill published in the GitHub repository datadog-labs/agent-skills (168 stars, last pushed 15d ago), licensed MIT. It adds 39 tokens to every session and 1,468 once invoked, about $0.0002 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 2026-08-30.

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