Kubernetes Network Root Cause Analysis
kubeshark/kubeshark
Investigates past Kubernetes incidents from Kubeshark traffic snapshots: takes captures, dissects API calls, extracts PCAPs and compares traffic over time.
Agent skill
Plans and facilitates tabletop exercises simulating ransomware incidents, using realistic scenarios based on threat actors like LockBit and ALPHV/BlackCat with injects covering double extortion and…
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-ransomware-tabletop-exercise -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-ransomware-tabletop-exercise --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/performing-ransomware-tabletop-exercise .claude/skills/performing-ransomware-tabletop-exercise && 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 "performing-ransomware-tabletop-exercise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-ransomware-tabletop-exercise into .claude/skills/performing-ransomware-tabletop-exercise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-ransomware-tabletop-exercise", 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/performing-ransomware-tabletop-exerciseType 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 performing-ransomware-tabletop-exercise -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-ransomware-tabletop-exercise --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/performing-ransomware-tabletop-exercise .agents/skills/performing-ransomware-tabletop-exercise && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "performing-ransomware-tabletop-exercise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-ransomware-tabletop-exercise into .agents/skills/performing-ransomware-tabletop-exercise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-ransomware-tabletop-exercise", 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 performing-ransomware-tabletop-exercise -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-ransomware-tabletop-exercise --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/performing-ransomware-tabletop-exercise .cursor/skills/performing-ransomware-tabletop-exercise && 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 "performing-ransomware-tabletop-exercise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-ransomware-tabletop-exercise into .cursor/skills/performing-ransomware-tabletop-exercise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-ransomware-tabletop-exercise", 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/performing-ransomware-tabletop-exercise--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 performing-ransomware-tabletop-exercise -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-ransomware-tabletop-exercise --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/performing-ransomware-tabletop-exercise .gemini/skills/performing-ransomware-tabletop-exercise && 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 "performing-ransomware-tabletop-exercise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-ransomware-tabletop-exercise into .gemini/skills/performing-ransomware-tabletop-exercise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-ransomware-tabletop-exercise", 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 performing-ransomware-tabletop-exerciseInstalls 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 performing-ransomware-tabletop-exercise -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/performing-ransomware-tabletop-exercise .github/skills/performing-ransomware-tabletop-exercise && 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 "performing-ransomware-tabletop-exercise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-ransomware-tabletop-exercise into .github/skills/performing-ransomware-tabletop-exercise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-ransomware-tabletop-exercise", 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 performing-ransomware-tabletop-exercise -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 performing-ransomware-tabletop-exercise --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/performing-ransomware-tabletop-exercise .opencode/skills/performing-ransomware-tabletop-exercise && 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 "performing-ransomware-tabletop-exercise" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-ransomware-tabletop-exercise into .opencode/skills/performing-ransomware-tabletop-exercise/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-ransomware-tabletop-exercise", 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.
performing-ransomware-tabletop-exercisePlans and facilitates tabletop exercises simulating ransomware incidents, using realistic scenarios based on threat actors like LockBit and ALPHV/BlackCat with injects covering double extortion and…
Performing Ransomware Tabletop Exercise is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Plans and facilitates tabletop exercises simulating ransomware incidents, using realistic scenarios based on threat actors like LockBit and ALPHV/BlackCat with injects covering double extortion and backup destruction, then evaluates responses against NIST CSF and CISA guidelines. Use when planning or running a ransomware tabletop exercise or incident response readiness drill.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).
It sits in DevOps & Cloud, covering Incident response. 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.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
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.
Ships 2 files in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Performing Ransomware Tabletop Exercise loads about 2.9k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 105 tokens; SKILL.md has 1,095 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.
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.
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 1,095 words, ~2,944 tokens.
.claude/skills/performing-ransomware-tabletop-exercise/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Do not use as a substitute for technical controls testing. Tabletop exercises validate procedures and decision-making, not technical detection or prevention capabilities.
Build a realistic scenario based on current threat actor TTPs:
Scenario Structure:
Phase 1: Initial Detection (30 min)
- SOC receives alert for suspicious process execution on file server
- EDR detects Cobalt Strike beacon on 3 workstations
- Inject: External threat intel report links C2 IP to LockBit affiliate
Phase 2: Escalation (30 min)
- Ransomware executes on 40% of servers during overnight hours
- Ransom note demands $2M in Bitcoin with 72-hour deadline
- Inject: Attackers contact media claiming data theft of customer PII
Phase 3: Decision Points (45 min)
- Backup assessment reveals immutable copies are intact but primary backups encrypted
- Legal advises on breach notification timeline (72 hours GDPR, varies by US state)
- Inject: Threat actor publishes sample of stolen data on leak site
Phase 4: Recovery and Communication (45 min)
- Recovery time estimate: 5-7 days from immutable backups
- Insurance carrier engages negotiation firm
- Inject: Major customer threatens contract termination without update within 24 hoursScenario Variables to Customize:
Create the following documents for participants:
Key Decision Points to Include:
Facilitator Responsibilities:
Probing Questions by Phase:
Phase 1 - Detection:
Phase 2 - Escalation:
Phase 3 - Decision:
Phase 4 - Recovery:
Score each functional area against defined criteria:
| Evaluation Area | Score (1-5) | Criteria |
|---|---|---|
| Detection & Escalation | Timely incident declaration, proper chain of command | |
| Containment | Network isolation, credential reset, scope assessment | |
| Communication - Internal | Employee notification, executive briefing, documented decisions | |
| Communication - External | Regulatory notification, customer communication, media response | |
| Recovery Planning | Backup verification, recovery priority, RTO tracking | |
| Legal & Compliance | Breach notification timelines, evidence preservation, law enforcement engagement | |
| Business Continuity | Manual operations, customer impact mitigation, revenue loss estimation | |
| Payment Decision | Structured framework, legal review, OFAC sanctions check |
Produce an after-action report (AAR) within 5 business days:
AAR Contents:
| Term | Definition |
|---|---|
| Tabletop Exercise (TTX) | Discussion-based exercise where participants walk through a simulated incident scenario to test plans and procedures |
| Inject | New information introduced during the exercise to change the scenario and force additional decision-making |
| SITREP | Situation Report providing current status of the simulated incident at each exercise phase |
| After-Action Report (AAR) | Post-exercise document capturing findings, gaps, strengths, and remediation actions |
| Double Extortion | Ransomware tactic where attackers both encrypt data and threaten to publish stolen data unless ransom is paid |
| OFAC Check | Verification that ransom payment recipient is not on the US Treasury OFAC sanctions list, which would make payment illegal |
Context: A 5-hospital healthcare system conducts an annual ransomware tabletop. Previous exercise revealed gaps in HIPAA breach notification and clinical system recovery priority. This year's scenario simulates a double extortion attack targeting the EMR system.
Approach:
Pitfalls:
## Ransomware Tabletop Exercise - After Action Report
**Exercise Date**: [Date]
**Facilitator**: [Name]
**Scenario**: [Brief description]
**Duration**: [Hours]
**Participants**: [Count by department]
### Exercise Objectives
1. [Objective] - Met / Partially Met / Not Met
2. [Objective] - Met / Partially Met / Not Met
### Key Decisions Log
| Time | Decision Point | Decision Made | Rationale | Assessment |
|------|---------------|--------------|-----------|------------|
### Strengths Observed
1. [Strength]
### Gaps Identified
| Gap | Severity | Affected Area | Current State | Desired State |
|-----|----------|--------------|---------------|---------------|
### Remediation Actions
| Action | Owner | Deadline | Priority | Status |
|--------|-------|----------|----------|--------|
### Comparison to Previous Exercise
| Area | Previous Score | Current Score | Trend |
|------|---------------|--------------|-------|© 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
SKILL.md and 7 other files (scripts, references, assets) in skills/performing-ransomware-tabletop-exercise of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Performing Ransomware Tabletop Exercise 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 |
|---|---|---|---|---|---|---|
| Performing Ransomware Tabletop Exercise this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Kubernetes Network Root Cause Analysiskubeshark/kubeshark | 12k | — | ~5.3k | Automated safety check: Pass | Apache-2.0 | |
| UModel Root Cause Analysisalibaba/UnifiedModel | 415 | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Learningskortix-ai/suna | 20k | — | ~1.1k | Automated safety check: Pass | Custom licence | |
| Oncallpigweed-project/pigweed | 548 | — | ~992 | Automated safety check: Pass | Apache-2.0 | |
| Loop Triage Reportcobusgreyling/loop-engineering | 11k | — | ~500 | Automated safety check: Pass | MIT |
kubeshark/kubeshark
Investigates past Kubernetes incidents from Kubeshark traffic snapshots: takes captures, dissects API calls, extracts PCAPs and compares traffic over time.
alibaba/UnifiedModel
Investigates a service incident to its root cause by querying a UModel object graph alongside metrics, logs, topology and recent deployments.
kortix-ai/suna
The project's episodic memory: a timestamped ledger of rules paid for with real outages and near-misses, one entry per incident.
pigweed-project/pigweed
Pigweed oncall rotation runbooks and maintenance workflows (such as rolling CIPD client tools for b/315378787).
cobusgreyling/loop-engineering
Turns CI failures, open issues, recent commits and chat threads into a prioritized markdown report that an automation loop can act on without inventing architecture work.
openclaw/clawhub
Investigates incidents and production problems with hypothesis-driven debugging, queries Axiom observability data when available, and keeps secrets out of commands and output.
mukul975/Anthropic-Cybersecurity-Skills
Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.
mukul975/Anthropic-Cybersecurity-Skills
Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.
mukul975/Anthropic-Cybersecurity-Skills
Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.
mukul975/Anthropic-Cybersecurity-Skills
Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.
mukul975/Anthropic-Cybersecurity-Skills
Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.
mukul975/Anthropic-Cybersecurity-Skills
Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.
Categories
Plans and facilitates tabletop exercises simulating ransomware incidents, using realistic scenarios based on threat actors like LockBit and ALPHV/BlackCat with injects covering double extortion and…. Performing Ransomware Tabletop Exercise is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Plans and facilitates tabletop exercises simulating ransomware incidents, using realistic scenarios based on threat actors like LockBit and ALPHV/BlackCat with injects covering double extortion and backup destruction, then evaluates responses against NIST CSF and CISA guidelines.
Performing Ransomware Tabletop Exercise fits situations like: running a ransomware tabletop exercise; incident response readiness drill.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-ransomware-tabletop-exercise -a claude-code`. Or copy the skill folder (skills/performing-ransomware-tabletop-exercise in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/performing-ransomware-tabletop-exercise in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-ransomware-tabletop-exercise -a codex`. Or copy the skill folder (skills/performing-ransomware-tabletop-exercise in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/performing-ransomware-tabletop-exercise in your project. Codex loads it when a task matches its description.
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-ransomware-tabletop-exercise -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-ransomware-tabletop-exercise, .gemini/skills/performing-ransomware-tabletop-exercise, .github/skills/performing-ransomware-tabletop-exercise and .opencode/skills/performing-ransomware-tabletop-exercise in your project.
Going by SKILL.md and its folder, Performing Ransomware Tabletop Exercise needs Python for the scripts in its folder. Our summary lists: Python 3.
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.
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.
Performing Ransomware Tabletop Exercise 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.
About 2.9k tokens (SKILL.md is roughly 12k 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 2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Performing Ransomware Tabletop Exercise: Kubernetes Network Root Cause Analysis (kubeshark/kubeshark, 12k stars), UModel Root Cause Analysis (alibaba/UnifiedModel, 415 stars), Learnings (kortix-ai/suna, 20k stars) and Oncall (pigweed-project/pigweed, 548 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,993 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.