Agent skill

Performing Insider Threat Investigation

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining…

Apache-2.0Auto-check passedSecurity

Install Performing Insider Threat Investigation

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-insider-threat-investigation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-insider-threat-investigation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/performing-insider-threat-investigation .claude/skills/performing-insider-threat-investigation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
performing-insider-threat-investigation
GitHub stars
34k
Token cost
~2.9k tokens
SKILL.md length
941 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining…

  • Works in 6 steps: Receive and Validate the Allegation → Collect Evidence Covertly → Analyze User Behavior Patterns → …
  • DLP alerts flag large data transfers to personal cloud storage
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Performing Insider Threat Investigation is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining digital forensics, user behavior analytics, and HR/legal coordination to build an evidence-based case. Use when DLP alerts flag large data transfers to personal cloud storage or USB devices, when UBA detects anomalous access patterns for a user account, or when investigating employee data theft, privilege misuse, or…

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Digital forensics. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • DLP alerts flag large data transfers to personal cloud storage
  • UBA detects anomalous access patterns for a user account
  • Investigating employee data theft
  • Privilege misuse

Example prompts

  • “Use the performing-insider-threat-investigation skill to investigate insider threat incidents involving employees, contractors, or trusted partners…”
  • “/performing-insider-threat-investigation”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Receive and Validate the Allegation
  2. Collect Evidence Covertly
  3. Analyze User Behavior Patterns
  4. Reconstruct the Activity Timeline
  5. Assess Impact and Determine Response
  6. Preserve Evidence for Legal Proceedings

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Performing Insider Threat Investigation loads about 2.9k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 147 tokens; SKILL.md has 941 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~147
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 941 words, ~2,873 tokens.

Download SKILL.mdSave it as .claude/skills/performing-insider-threat-investigation/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
performing-insider-threat-investigation
description
Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining digital forensics, user behavior analytics, and HR/legal coordination to build an evidence-based case. Use when DLP alerts flag large data transfers to personal cloud storage or USB devices, when UBA detects anomalous access patterns for a user account, or when investigating employee data theft, privilege misuse, or internal threat detection requests.
domain
cybersecurity
subdomain
incident-response
tags
insider-threat, user-behavior-analytics, data-exfiltration, privilege-misuse, DFIR
mitre_attack
T1486, T1490, T1070, T1078, T1048
version
1.0.0
author
mahipal
license
Apache-2.0
nist_csf
RS.MA-01, RS.MA-02, RS.AN-03, RC.RP-01

Performing Insider Threat Investigation

When to Use

  • DLP (Data Loss Prevention) alerts on large data transfers to personal cloud storage or USB devices
  • User behavior analytics (UBA) detects anomalous access patterns for a user account
  • HR reports a departing employee suspected of taking proprietary information
  • A privileged user is observed accessing systems outside their job function
  • Whistleblower or coworker report alleges policy violations or data theft

Do not use for external attacker investigations where compromised credentials are used without insider collusion; use standard incident response procedures instead.

Prerequisites

  • Legal counsel approval before initiating any monitoring or investigation of an employee
  • HR partnership with defined investigation procedures and employee privacy guidelines
  • DLP platform with content inspection and policy enforcement (Symantec DLP, Microsoft Purview, Digital Guardian)
  • User behavior analytics platform (Microsoft Sentinel UEBA, Exabeam, Securonix)
  • Forensic imaging capability for endpoint examination
  • Chain of custody procedures for evidence that may be used in legal proceedings
  • Clear authority and scope documentation approved by legal and HR

Workflow

Step 1: Receive and Validate the Allegation

Document the initial report and validate before proceeding:

  • Record the source of the allegation (DLP alert, UBA detection, HR referral, manager report)
  • Confirm with legal counsel that the investigation is authorized
  • Define the investigation scope: what activity is being investigated, time period, systems involved
  • Establish the investigation team: security, legal, HR (never investigate alone)
  • Create a restricted case file accessible only to the investigation team
Investigation Authorization:
━━━━━━━━━━━━━━━━━━━━━━━━━━━
Case ID:           INV-2025-042
Subject:           [Employee Name] - [Title] - [Department]
Allegation:        Unauthorized transfer of proprietary data to personal cloud storage
Reported By:       DLP system alert + manager concern
Legal Approval:    [Counsel Name] - 2025-11-15
HR Liaison:        [HR Name]
Scope:             File access and transfer activity from 2025-10-01 to present
Systems in Scope:  Workstation, email, cloud storage, VPN, DLP logs
Step 2: Collect Evidence Covertly

Gather evidence without alerting the subject to the investigation:

Log-Based Evidence (non-intrusive):

  • DLP logs: file transfers, policy violations, content matches
  • Cloud access logs: SharePoint, OneDrive, Google Drive activity
  • Email logs: messages to personal accounts, large attachments, forwarding rules
  • VPN and authentication logs: access times, locations, devices
  • Badge access logs: physical access patterns
  • Print logs: large print jobs of sensitive documents
  • USB device connection logs: device type, serial number, connection times

User Activity Monitoring (requires legal approval):

  • Screen capture or session recording (only if legally authorized and documented)
  • Keystroke logging (jurisdiction-dependent, requires explicit legal approval)
  • Network traffic capture for the subject's workstation

Endpoint Forensics (if warranted by evidence):

  • Create forensic image of the subject's workstation
  • Analyze browser history, download history, and installed applications
  • Examine deleted files and Recycle Bin contents
  • Review cloud sync application logs (Dropbox, Google Drive desktop client)
Step 3: Analyze User Behavior Patterns

Build a behavioral profile comparing normal vs. anomalous activity:

Behavioral Analysis:
━━━━━━━━━━━━━━━━━━
Normal Baseline (6-month average):
- Login time: 08:30-09:00 weekdays
- Files accessed: 15-25 per day (marketing department files)
- Email volume: 45 sent, 80 received per day
- Data transferred: 50MB per day average
- USB usage: None

Investigation Period (last 30 days):
- Login time: 22:00-02:00 (after hours, multiple occasions)
- Files accessed: 200+ per day (finance, engineering, executive files)
- Email volume: 120 sent per day (30% to personal gmail)
- Data transferred: 2.5GB per day average
- USB usage: 3 unique devices connected (Kingston DataTraveler)
- Print jobs: 847 pages (competitor analysis, customer lists, source code)

Anomaly Score: 94/100 (Critical)
Step 4: Reconstruct the Activity Timeline

Build a chronological timeline of the subject's actions:

Timeline of Activity:
2025-10-15  Subject submits resignation (2-week notice)
2025-10-16  First after-hours login at 23:15, accessed engineering Git repository
2025-10-17  USB device (Kingston DT 64GB) first connected at 23:30
2025-10-18  DLP alert: 450 files copied to USB, including CAD drawings
2025-10-19  200+ emails forwarded to personal Gmail account
2025-10-20  Google Drive desktop client installed, syncing corporate SharePoint
2025-10-22  Accessed executive SharePoint site (not normally accessed)
2025-10-25  Second USB device connected, 2.1GB transferred
2025-10-28  Print job: 847 pages including customer contact database
Step 5: Assess Impact and Determine Response

Evaluate the severity and coordinate the response with HR and legal:

Impact Assessment:

  • What data was accessed or exfiltrated (classification level, business impact)
  • Was the data shared externally (competitors, public, personal storage)
  • Regulatory implications (PII, PHI, financial data, export-controlled)
  • Contractual implications (NDA violations, IP assignment agreements)
  • Potential financial damage to the organization

Response Options (determined by legal and HR):

  • Confront the subject with evidence during an interview (HR-led)
  • Terminate employment and revoke all access immediately
  • Pursue civil litigation for breach of NDA or trade secret theft
  • Refer to law enforcement for criminal prosecution (theft of trade secrets, CFAA violation)
  • Negotiate a settlement with return/destruction of data

Ensure all evidence meets legal admissibility standards:

  • Maintain strict chain of custody for all physical and digital evidence
  • Document all analysis steps in detail (reproducible by another examiner)
  • Hash all evidence files and maintain an integrity log
  • Store evidence in a secure, access-controlled repository with audit logging
  • Retain evidence per legal hold requirements (do not destroy during active investigation or litigation)
Show full SKILL.md (352 more words)Show less

Key Concepts

TermDefinition
Insider ThreatRisk posed by individuals with authorized access who intentionally or unintentionally cause harm to the organization
User Behavior Analytics (UBA)Technology that analyzes user activity patterns to detect anomalies indicating potential insider threats
Data Loss Prevention (DLP)Technology that monitors, detects, and blocks unauthorized transfer of sensitive data outside the organization
Legal HoldDirective to preserve all relevant evidence and suspend normal document destruction policies during an investigation
Need to KnowInformation access principle restricting insider threat investigation details to only authorized team members
Exfiltration VectorMethod used to move data outside the organization: USB, email, cloud storage, print, screen capture, photography

Tools & Systems

  • Microsoft Purview (formerly Compliance Center): Insider risk management, DLP, eDiscovery, and content search
  • Exabeam / Securonix: User and entity behavior analytics (UEBA) platforms for anomaly detection
  • Digital Guardian: DLP and insider threat detection platform with endpoint agent
  • Magnet AXIOM: Digital forensics platform supporting endpoint, cloud, and mobile evidence analysis
  • Relativity: eDiscovery platform for legal review of collected evidence in insider threat cases

Common Scenarios

Scenario: Departing Engineer Exfiltrating Source Code

Context: A senior software engineer with access to critical repositories submits a two-week resignation notice. The engineering manager reports that the engineer has been working unusual hours and downloading large amounts of code.

Approach:

  1. Obtain legal authorization to investigate before taking any action
  2. Pull Git access logs showing repository clones and downloads for the past 60 days
  3. Review DLP logs for USB device connections and large file transfers
  4. Check email gateway for messages with code attachments sent to personal accounts
  5. Analyze browser history for personal cloud storage uploads
  6. Image the workstation forensically before the employee's last day
  7. Present findings to legal and HR for determination of next steps

Pitfalls:

  • Investigating without legal counsel authorization (may violate employee privacy rights)
  • Alerting the subject to the investigation before evidence is preserved
  • Not preserving the workstation before the employee's departure date
  • Assuming all after-hours access is malicious without comparing to the employee's historical baseline
  • Failing to check personal mobile devices that may have accessed corporate cloud services

Output Format

INSIDER THREAT INVESTIGATION REPORT
=====================================
Case ID:          INV-2025-042
Classification:   CONFIDENTIAL - Need to Know Only
Subject:          [Name Redacted] - Senior Engineer
Investigation Period: 2025-10-01 to 2025-10-28
Investigator:     [Name]
Legal Counsel:    [Name]
HR Liaison:       [Name]

ALLEGATION
Unauthorized exfiltration of proprietary source code and customer
data following resignation submission.

EVIDENCE SUMMARY
1. Git logs: 47 repositories cloned (vs. baseline of 3)
2. USB transfers: 4.6 GB across 3 unique devices over 12 sessions
3. Email: 200+ emails with attachments forwarded to personal Gmail
4. Cloud: Google Drive sync client installed, syncing corporate files
5. Print: 847 pages including customer contact database
6. Physical access: After-hours badge access on 8 of 12 workdays

BEHAVIORAL ANALYSIS
[Baseline vs. anomalous activity comparison]

IMPACT ASSESSMENT
Data Classification:  Confidential (source code, customer PII)
Estimated Volume:     7.2 GB exfiltrated
Regulatory Impact:    Potential GDPR notification (customer PII)
Business Impact:      Competitive advantage at risk

TIMELINE
[Chronological event listing]

RECOMMENDATIONS
1. [Legal/HR decision on employment action]
2. [Evidence preservation actions]
3. [Regulatory notification assessment]
4. [Access control improvements]

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/performing-insider-threat-investigation of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

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TShark Traffic AnalysisAgentSecOps/SecOpsAgentKit2201 repos~4.8kAutomated safety check: NotesCustom licence
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Categories

Questions about Performing Insider Threat Investigation

What does Performing Insider Threat Investigation do?

Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining…. Performing Insider Threat Investigation is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining digital forensics, user behavior analytics, and HR/legal coordination to build an evidence-based case.

When should I use Performing Insider Threat Investigation?

Performing Insider Threat Investigation fits situations like: DLP alerts flag large data transfers to personal cloud storage; UBA detects anomalous access patterns for a user account; investigating employee data theft; privilege misuse.

How do I install Performing Insider Threat Investigation in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-insider-threat-investigation -a claude-code`. Or copy the skill folder (skills/performing-insider-threat-investigation in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/performing-insider-threat-investigation in your project. Claude Code loads it when a task matches its description.

How do I install Performing Insider Threat Investigation in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-insider-threat-investigation -a codex`. Or copy the skill folder (skills/performing-insider-threat-investigation in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/performing-insider-threat-investigation in your project. Codex loads it when a task matches its description.

Can I use Performing Insider Threat Investigation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-insider-threat-investigation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performing-insider-threat-investigation, .gemini/skills/performing-insider-threat-investigation, .github/skills/performing-insider-threat-investigation and .opencode/skills/performing-insider-threat-investigation in your project.

What does Performing Insider Threat Investigation need to run?

Going by SKILL.md and its folder, Performing Insider Threat Investigation needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Performing Insider Threat Investigation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Performing Insider Threat Investigation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Performing Insider Threat Investigation use?

Performing Insider Threat Investigation is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Performing Insider Threat Investigation use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 475 tokens, read only when the agent opens those files.

What are the alternatives to Performing Insider Threat Investigation?

Skills that share tags, products or a category with Performing Insider Threat Investigation: Oss Forensics (Tommy-yw/RunbookHermes, 546 stars), Ctf Malware (ljagiello/ctf-skills, 3.4k stars), Dfir (transilienceai/communitytools, 563 stars) and TShark Traffic Analysis (AgentSecOps/SecOpsAgentKit, 220 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Performing Insider Threat Investigation?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.