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 datadog-labs/agent-skills --skill security-investigationgit clone --depth 1 https://github.com/datadog-labs/agent-skillsWrote 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/datadog-labs/agent-skills/security-investigation)<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.
<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>- NVIDIA SkillSpector pass
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 | $0.00039 | $0.01468 |
| Opus 5 | $0.00019 | $0.00734 |
| Sonnet 5 | $0.00008 | $0.00294 |
| Haiku 4.5 | $0.00004 | $0.00147 |
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- dd-audit-security-investigation — 100% identical, 0 lines differ
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
- Clarify the investigation scope: who, what resource type, what time window.
- Run the most specific query first; broaden only if results are empty.
- If results are large, pipe to
jqto group or summarize. - 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
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.
- 11d ago First seen · 171 lines · 39 tokens per session scan A 7470b7730af8
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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