Anomalib Tiled Ensemble
open-edge-platform/anomalib
Runs and configures the anomalib tiled-ensemble pipeline, which trains/evaluates one model per image tile and merges results (with optional seam smoothing) for high-resolution anomaly detection.
Agent skill
Implementing Cloud Workload Protection
Implements cloud workload protection using boto3 and google-cloud APIs for runtime security monitoring, process anomaly detection, and file integrity checking on EC2/GCE instances.
Install Implementing Cloud Workload Protection
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-cloud-workload-protection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-cloud-workload-protection --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/implementing-cloud-workload-protection .claude/skills/implementing-cloud-workload-protection && 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 "implementing-cloud-workload-protection" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-cloud-workload-protection into .claude/skills/implementing-cloud-workload-protection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-cloud-workload-protection", 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/implementing-cloud-workload-protectionType 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 implementing-cloud-workload-protection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-cloud-workload-protection --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/implementing-cloud-workload-protection .agents/skills/implementing-cloud-workload-protection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "implementing-cloud-workload-protection" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-cloud-workload-protection into .agents/skills/implementing-cloud-workload-protection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-cloud-workload-protection", 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 implementing-cloud-workload-protection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-cloud-workload-protection --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/implementing-cloud-workload-protection .cursor/skills/implementing-cloud-workload-protection && 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 "implementing-cloud-workload-protection" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-cloud-workload-protection into .cursor/skills/implementing-cloud-workload-protection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-cloud-workload-protection", 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/implementing-cloud-workload-protection--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 implementing-cloud-workload-protection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-cloud-workload-protection --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/implementing-cloud-workload-protection .gemini/skills/implementing-cloud-workload-protection && 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 "implementing-cloud-workload-protection" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-cloud-workload-protection into .gemini/skills/implementing-cloud-workload-protection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-cloud-workload-protection", 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 implementing-cloud-workload-protectionInstalls 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 implementing-cloud-workload-protection -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/implementing-cloud-workload-protection .github/skills/implementing-cloud-workload-protection && 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 "implementing-cloud-workload-protection" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-cloud-workload-protection into .github/skills/implementing-cloud-workload-protection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-cloud-workload-protection", 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 implementing-cloud-workload-protection -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 implementing-cloud-workload-protection --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/implementing-cloud-workload-protection .opencode/skills/implementing-cloud-workload-protection && 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 "implementing-cloud-workload-protection" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-cloud-workload-protection into .opencode/skills/implementing-cloud-workload-protection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-cloud-workload-protection", 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
implementing-cloud-workload-protection- GitHub stars
- 34k
- Token cost
- ~578 tokens
- SKILL.md length
- 134 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 639
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Implements cloud workload protection using boto3 and google-cloud APIs for runtime security monitoring, process anomaly detection, and file integrity checking on EC2/GCE instances.
- Works in 5 steps: Process monitoring for cryptominers and… → File integrity monitoring on critical… → Network connection auditing for C2… → …
- Building runtime security controls for cloud compute workloads
- SKILL.md covers When to Use, Prerequisites, Instructions and Examples
- Runs Python scripts from its folder
What it does
Implementing Cloud Workload Protection is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Implements cloud workload protection using boto3 and google-cloud APIs for runtime security monitoring, process anomaly detection, and file integrity checking on EC2/GCE instances. Scans for cryptomining, reverse shells, and unauthorized binaries. Use when building runtime security controls for cloud compute workloads.
Its SKILL.md is about 580 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 Anomaly detection. It works with Google Cloud. 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
- Building runtime security controls for cloud compute workloads
- Tasks that involve Anomaly detection
Example prompts
- “Use the implementing-cloud-workload-protection skill to implement cloud workload protection using boto3 and google-cloud APIs for runtime security…”
- “/implementing-cloud-workload-protection”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Process monitoring for cryptominers and reverse shells
- File integrity monitoring on critical system files
- Network connection auditing for C2 callbacks
- Resource utilization anomaly detection (CPU spikes)
- Unauthorized binary detection via hash comparison
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
Implementing Cloud Workload Protection loads about 578 tokens when it runs, and up to ~1k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 134 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). 134 words, ~578 tokens.
Download SKILL.mdSave it as
.claude/skills/implementing-cloud-workload-protection/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- implementing-cloud-workload-protection
- description
- Implements cloud workload protection using boto3 and google-cloud APIs for runtime security monitoring, process anomaly detection, and file integrity checking on EC2/GCE instances. Scans for cryptomining, reverse shells, and unauthorized binaries. Use when building runtime security controls for cloud compute workloads.
- domain
- cybersecurity
- subdomain
- cloud-security
- tags
- cloud-security, cwpp, workload-protection, boto3, runtime-security, process-anomaly-detection
- 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
- T1078.004, T1530, T1537, T1580, T1071
Implementing Cloud Workload Protection
When to Use
- When deploying or configuring implementing cloud workload protection capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- Familiarity with cloud security concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Instructions
Monitor cloud workloads for runtime threats by checking process lists, network connections, file integrity, and resource utilization anomalies.
import boto3
ssm = boto3.client("ssm")
# Run command on EC2 instances to check for suspicious processes
response = ssm.send_command(
InstanceIds=["i-1234567890abcdef0"],
DocumentName="AWS-RunShellScript",
Parameters={"commands": ["ps aux | grep -E 'xmrig|minerd|cryptonight'"]},
)Key protection areas:
- Process monitoring for cryptominers and reverse shells
- File integrity monitoring on critical system files
- Network connection auditing for C2 callbacks
- Resource utilization anomaly detection (CPU spikes)
- Unauthorized binary detection via hash comparison
Examples
# Check for unauthorized outbound connections
ssm.send_command(
InstanceIds=instances,
DocumentName="AWS-RunShellScript",
Parameters={"commands": ["ss -tlnp | grep ESTABLISHED"]},
)© 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/implementing-cloud-workload-protection 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
Implementing Cloud Workload Protection 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 |
|---|---|---|---|---|---|---|
| Implementing Cloud Workload Protection this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~578 | Automated safety check: Pass | Apache-2.0 | |
| Anomalib Tiled Ensembleopen-edge-platform/anomalib | 6.2k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Dt Obs HostsDynatrace/dynatrace-for-ai | 161 | — | ~5.5k | Automated safety check: Pass | Apache-2.0 | |
| TimesFM Forecastinggoogle-research/timesfm | 34k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| Anomalib Adding A Modelopen-edge-platform/anomalib | 6.2k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Kqlmicrosoft/fabric-rti-mcp | 131 | — | ~6.2k | Automated safety check: Pass | MIT |
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Forecasts any univariate time series zero-shot with Google's TimesFM model, returning point forecasts and calibrated prediction intervals without training.
Anomalib Adding A Model
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Adds a new anomaly-detection model to anomalib under src/anomalib/models/.
- Official
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KQL language expertise for writing correct, efficient Kusto queries using the Fabric RTI MCP tools.
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Build a new time-series analytics use case on top of the deployed Time Series Analytics microservice — bring it up with Docker Compose (from a repo clone, or by fetching the compose files from…
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Related
Works with
Categories
Questions about Implementing Cloud Workload Protection
What does Implementing Cloud Workload Protection do?
Implements cloud workload protection using boto3 and google-cloud APIs for runtime security monitoring, process anomaly detection, and file integrity checking on EC2/GCE instances. Implementing Cloud Workload Protection is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Implements cloud workload protection using boto3 and google-cloud APIs for runtime security monitoring, process anomaly detection, and file integrity checking on EC2/GCE instances.
When should I use Implementing Cloud Workload Protection?
Implementing Cloud Workload Protection fits situations like: building runtime security controls for cloud compute workloads; tasks that involve Anomaly detection.
How do I install Implementing Cloud Workload Protection in Claude Code?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-cloud-workload-protection -a claude-code`. Or copy the skill folder (skills/implementing-cloud-workload-protection in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-cloud-workload-protection in your project. Claude Code loads it when a task matches its description.
How do I install Implementing Cloud Workload Protection in Codex?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-cloud-workload-protection -a codex`. Or copy the skill folder (skills/implementing-cloud-workload-protection in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-cloud-workload-protection in your project. Codex loads it when a task matches its description.
Can I use Implementing Cloud Workload Protection 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 implementing-cloud-workload-protection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-cloud-workload-protection, .gemini/skills/implementing-cloud-workload-protection, .github/skills/implementing-cloud-workload-protection and .opencode/skills/implementing-cloud-workload-protection in your project.
What does Implementing Cloud Workload Protection need to run?
Going by SKILL.md and its folder, Implementing Cloud Workload Protection needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Implementing Cloud Workload Protection 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 Implementing Cloud Workload Protection 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 Implementing Cloud Workload Protection use?
Implementing Cloud Workload Protection 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 Implementing Cloud Workload Protection use?
About 578 tokens (SKILL.md is roughly 2.3k 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 426 tokens, read only when the agent opens those files.
What are the alternatives to Implementing Cloud Workload Protection?
Skills that share tags, products or a category with Implementing Cloud Workload Protection: Anomalib Tiled Ensemble (open-edge-platform/anomalib, 6.2k stars), Dt Obs Hosts (Dynatrace/dynatrace-for-ai, 161 stars), TimesFM Forecasting (google-research/timesfm, 34k stars) and Anomalib Adding A Model (open-edge-platform/anomalib, 6.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Implementing Cloud Workload Protection?
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.