Data Exfiltration Investigation logo

Data Exfiltration Investigation

Organization
CDESpace
Data Exfiltration Investigation

Investigate an escalated data-exfiltration alert. Quantifies what actually left — volume against baseline, the data's sensitivity, and the destination — attributes the transfer to a principal and channel, and distinguishes a backup or sanctioned sync from theft before returning a verdict with scope and containment actions.

Overview

PublisherCDESpace
RepositoryDetection-Skills
Skill nameData Exfiltration Investigation
Stars
57
Forks
5
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by CDESpace on GitHub. Read the source before you install it.

Installation

Install the Data Exfiltration Investigation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/CDESpace/Detection-Skills/tree/main/skills/investigation/Data%20Exfiltration%20Investigation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable Data Exfiltration Investigation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Data Exfiltration Investigation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Data Exfiltration Investigation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Data Exfiltration Investigation

Runs on alerts escalated by triage (see the cloud and application exfiltration triage skills): a principal moved an unusual volume of data, or sent it to an unusual destination, in a way triage judged anomalous. Triage established the transfer looked wrong; investigation quantifies it and attributes it. The question is not "did data move" — it did — but "how much, how sensitive, where to, and who sent it."

Inputs

  • The escalated alert (principal, source store, destination, volume, timing) and the triage report.
  • Access and data-transfer logs (cloud storage access logs, DLP events, proxy/egress logs, SaaS download/export logs), the principal's activity history, and data-classification metadata where available.

Investigation steps

Collect all four signals; the verdict is derived from them at the end.

1. Volume and baseline — signal A

Measure what actually moved and compare it to the principal's own history and their peers'. Signal A fires when the volume is a sharp departure from baseline — orders of magnitude over what this principal, role, or service normally transfers — and especially a bulk pull (a whole bucket, a full mailbox, an entire table) rather than incremental access.

2. Sensitivity — signal B

Classify what left, not just how much. Signal B fires when the data is sensitive — credentials/secrets, regulated PII/PHI, source code, customer databases, or crown-jewel stores — using classification labels, path/bucket names, and sampled content. A large transfer of public or low-value data weighs far less than a small transfer of secrets.

3. Destination and channel — signal C

Attribute where it went and how. Signal C fires when the destination is external and unsanctioned — a personal cloud account, a newly-seen domain, an anonymizer, an attacker-controlled host — or the channel is an evasion (archived/encrypted before send, DNS/ICMP tunneling, a covert upload). An internal or sanctioned destination (approved backup, corporate SaaS) weakens it.

4. Actor and intent — signal D

Attribute the transfer to a principal and situate it. Signal D fires when the actor is compromised or acting against pattern: the principal was flagged earlier in an intrusion, a service account moved data it never touches, or a departing employee bulk-pulled right before leaving. This separates theft from a legitimate-but-noisy job.

Verdict rule

  • malicious: signal C plus A or B — sensitive or high-volume data to an unsanctioned destination or through an evasion channel, especially tied to a compromised or against-pattern actor (D). Secrets or a customer database leaving to attacker-controlled infrastructure is malicious on its own.
  • suspicious: an anomalous transfer (A or B) whose destination can't be cleared as sanctioned and whose actor intent can't be established, but benign use can't be shown either.
  • inconclusive: the transfer volume, contents, or destination can't be reconstructed because transfer/DLP logs are missing.
  • benign: the transfer resolves to a sanctioned job — a scheduled backup, an approved data-pipeline sync, a user moving their own files to corporate storage — matching the principal's baseline and role, to an internal or approved destination, with no sensitivity or evasion concern.

Output

Verdict

One of malicious / suspicious / inconclusive / benign, with the signals that decided it.

Recommended actions

When not benign: revoke the principal's access to the source store and active sessions, block the destination, preserve transfer logs and any staged archives, notify data-owner and privacy/legal when regulated or customer data is confirmed out, and hunt for the same principal/destination across other stores. Scale notification to the sensitivity found in step 2.

Evidence

The measured volume against baseline, the classification of what left, the destination attribution and channel, the actor and their status, and the window and source store involved.

Reasoning

Name the signals and how they stacked — a service account archiving an entire customer database and pushing it to a personal cloud account it has never used, right after that account was flagged, is malicious; the nightly backup job copying its usual volume to the approved backup bucket is benign.

Frequently asked questions

What does the Data Exfiltration Investigation AI skill do?

Investigate an escalated data-exfiltration alert. Quantifies what actually left — volume against baseline, the data's sensitivity, and the destination — attributes the transfer to a principal and channel, and distinguishes a backup or sanctioned sync from theft before returning a verdict with scope and containment actions.

Why use Data Exfiltration Investigation on TypingMind?

Because you install it once and use it with any model. Data Exfiltration Investigation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Data Exfiltration Investigation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CDESpace/Detection-Skills/tree/main/skills/investigation/Data%20Exfiltration%20Investigation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Data Exfiltration Investigation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Data Exfiltration Investigation?

As many as you like. As long as a model supports skills, you can use Data Exfiltration Investigation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Data Exfiltration Investigation AI skill free?

Yes. It is published on GitHub by CDESpace under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇