Chdb Datastore
vemetric/vemetric
A skill your agent uses when the user has tabular data (pandas DataFrame, parquet, csv, Arrow, json) and wants to filter, group, aggregate, join, or speed up slow pandas.
Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify…
Install Detecting Shadow It Cloud Usage
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-it-cloud-usage --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/detecting-shadow-it-cloud-usage .claude/skills/detecting-shadow-it-cloud-usage && rm -rf skills-srcUse ~/.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/
Install the "detecting-shadow-it-cloud-usage" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-it-cloud-usage into .claude/skills/detecting-shadow-it-cloud-usage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-it-cloud-usage", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-it-cloud-usageType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-it-cloud-usage --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/detecting-shadow-it-cloud-usage .agents/skills/detecting-shadow-it-cloud-usage && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "detecting-shadow-it-cloud-usage" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-it-cloud-usage into .agents/skills/detecting-shadow-it-cloud-usage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-it-cloud-usage", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-it-cloud-usage --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/detecting-shadow-it-cloud-usage .cursor/skills/detecting-shadow-it-cloud-usage && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "detecting-shadow-it-cloud-usage" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-it-cloud-usage into .cursor/skills/detecting-shadow-it-cloud-usage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-it-cloud-usage", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/detecting-shadow-it-cloud-usage--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-it-cloud-usage --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/detecting-shadow-it-cloud-usage .gemini/skills/detecting-shadow-it-cloud-usage && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "detecting-shadow-it-cloud-usage" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-it-cloud-usage into .gemini/skills/detecting-shadow-it-cloud-usage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-it-cloud-usage", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-it-cloud-usageInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/detecting-shadow-it-cloud-usage .github/skills/detecting-shadow-it-cloud-usage && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "detecting-shadow-it-cloud-usage" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-it-cloud-usage into .github/skills/detecting-shadow-it-cloud-usage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-it-cloud-usage", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills detecting-shadow-it-cloud-usage --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/detecting-shadow-it-cloud-usage .opencode/skills/detecting-shadow-it-cloud-usage && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "detecting-shadow-it-cloud-usage" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/detecting-shadow-it-cloud-usage into .opencode/skills/detecting-shadow-it-cloud-usage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "detecting-shadow-it-cloud-usage", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
detecting-shadow-it-cloud-usage- GitHub stars
- 34k
- Token cost
- ~637 tokens
- SKILL.md length
- 240 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 639
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify…
- Works in 7 steps: Parse proxy access logs and extract… → Parse DNS query logs to identify… → Aggregate traffic by domain using pandas… → …
- Auditing an organization for unsanctioned cloud/SaaS usage
- SKILL.md covers Overview, When to Use, Prerequisites and Steps, plus 1 more section
- Runs Python scripts from its folder
What it does
Detecting Shadow It Cloud Usage is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify domains against known SaaS categories, and score risk by data volume and user count. Use when auditing an organization for unsanctioned cloud/SaaS usage or generating a shadow IT discovery report with remediation recommendations.
Its SKILL.md is about 640 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 Data & Analytics, covering DataFrames. It works with pandas and Python. 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
- Auditing an organization for unsanctioned cloud/SaaS usage
- Generating a shadow IT discovery report with remediation recommendations
Example prompts
- “/detecting-shadow-it-cloud-usage”
Requirements
- Python 3
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Parse proxy access logs and extract destination domains with traffic volumes
- Parse DNS query logs to identify resolved cloud service domains
- Aggregate traffic by domain using pandas — total bytes, request counts, unique users
- Classify domains against known SaaS categories (storage, email, dev tools, AI)
- Flag unauthorized services not on the approved application list
- Calculate risk scores based on data volume, user count, and service category
- Generate shadow IT discovery report with remediation recommendations
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
Detecting Shadow It Cloud Usage loads about 637 tokens when it runs, and up to ~1.2k if it reads all its reference files. Until then it costs about 114 tokens; SKILL.md has 240 words of instructions outside code blocks.
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). 240 words, ~637 tokens.
Download SKILL.mdSave it as
.claude/skills/detecting-shadow-it-cloud-usage/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- detecting-shadow-it-cloud-usage
- description
- Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify domains against known SaaS categories, and score risk by data volume and user count. Use when auditing an organization for unsanctioned cloud/SaaS usage or generating a shadow IT discovery report with remediation recommendations.
- domain
- cybersecurity
- subdomain
- cloud-security
- tags
- shadow-IT, SaaS-discovery, proxy-logs, DNS-analysis, netflow, cloud-security, pandas
- version
- 1.0
- author
- mahipal
- license
- Apache-2.0
- nist_csf
- PR.IR-01, ID.AM-08, GV.SC-06, DE.CM-01
- mitre_attack
- T1567.002, T1526, T1078.004, T1213
Detecting Shadow IT Cloud Usage
Overview
Shadow IT refers to unauthorized SaaS applications and cloud services used without IT approval. This skill analyzes proxy logs, DNS query logs, and firewall/netflow data to identify unauthorized cloud service usage, classify discovered domains against known SaaS categories, measure data transfer volumes, and flag high-risk services based on security posture and compliance requirements.
When to Use
- When investigating security incidents that require detecting shadow it cloud usage
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Python 3.9+ with
pandas,tldextract - Proxy logs (Squid, Zscaler, or Palo Alto format) or DNS query logs
- SaaS application catalog/blocklist for classification
- Network firewall logs with FQDN resolution (optional)
Steps
- Parse proxy access logs and extract destination domains with traffic volumes
- Parse DNS query logs to identify resolved cloud service domains
- Aggregate traffic by domain using pandas — total bytes, request counts, unique users
- Classify domains against known SaaS categories (storage, email, dev tools, AI)
- Flag unauthorized services not on the approved application list
- Calculate risk scores based on data volume, user count, and service category
- Generate shadow IT discovery report with remediation recommendations
Expected Output
- JSON report listing discovered cloud services with traffic volumes, user counts, risk scores, and approval status
- Top unauthorized services ranked by data exfiltration risk
© 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/detecting-shadow-it-cloud-usage of mukul975/Anthropic-Cybersecurity-Skills.
- SKILL.md
- LICENSE
- references/api-reference.md
- scripts/agent.py
Open the folder on GitHubat commit 54a7988
Compare with similar skills
Detecting Shadow It Cloud Usage next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Detecting Shadow It Cloud Usage this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~637 | Automated safety check: Pass | Apache-2.0 | |
| Chdb Datastorevemetric/vemetric | 394 | 2 repos | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| CSV Data Summarizercoffeefuelbump/csv-data-summarizer-claude-skill | 468 | 2 repos | ~1.4k | Automated safety check: Pass | None | |
| Python Executorcortega26/chile-hub | 113 | 2 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Retentioneering Product Analyticsretentioneering/retentioneering-tools | 920 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Pandas ProJeffallan/claude-skills | 12k | 1 repos | ~1.5k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Detecting Shadow It Cloud Usage
What does Detecting Shadow It Cloud Usage do?
Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify…. Detecting Shadow It Cloud Usage is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify domains against known SaaS categories, and score risk by data volume and user count.
When should I use Detecting Shadow It Cloud Usage?
Detecting Shadow It Cloud Usage fits situations like: auditing an organization for unsanctioned cloud/SaaS usage; generating a shadow IT discovery report with remediation recommendations.
How do I install Detecting Shadow It Cloud Usage in Claude Code?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a claude-code`. Or copy the skill folder (skills/detecting-shadow-it-cloud-usage in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/detecting-shadow-it-cloud-usage in your project. Claude Code loads it when a task matches its description.
How do I install Detecting Shadow It Cloud Usage in Codex?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-shadow-it-cloud-usage -a codex`. Or copy the skill folder (skills/detecting-shadow-it-cloud-usage in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/detecting-shadow-it-cloud-usage in your project. Codex loads it when a task matches its description.
Can I use Detecting Shadow It Cloud Usage 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 detecting-shadow-it-cloud-usage -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/detecting-shadow-it-cloud-usage, .gemini/skills/detecting-shadow-it-cloud-usage, .github/skills/detecting-shadow-it-cloud-usage and .opencode/skills/detecting-shadow-it-cloud-usage in your project.
What does Detecting Shadow It Cloud Usage need to run?
Going by SKILL.md and its folder, Detecting Shadow It Cloud Usage needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Detecting Shadow It Cloud Usage 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 Detecting Shadow It Cloud Usage 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 Detecting Shadow It Cloud Usage use?
Detecting Shadow It Cloud Usage 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 Detecting Shadow It Cloud Usage use?
About 637 tokens (SKILL.md is roughly 2.5k 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 600 tokens, read only when the agent opens those files.
What are the alternatives to Detecting Shadow It Cloud Usage?
Skills that share tags, products or a category with Detecting Shadow It Cloud Usage: Chdb Datastore (vemetric/vemetric, 394 stars), CSV Data Summarizer (coffeefuelbump/csv-data-summarizer-claude-skill, 468 stars), Python Executor (cortega26/chile-hub, 113 stars) and Retentioneering Product Analytics (retentioneering/retentioneering-tools, 920 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Detecting Shadow It Cloud Usage?
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,870 GitHub stars. The repository holds 639 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.