Agent skill

Performing Oil Gas Cybersecurity Assessment

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Conduct cybersecurity assessments of upstream, midstream, and downstream oil and gas operations, covering pipeline SCADA, refinery DCS, safety instrumented systems, and remote wellhead RTUs, and…

Apache-2.0Auto-check passedSecurity

Install Performing Oil Gas Cybersecurity Assessment

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-oil-gas-cybersecurity-assessment -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-oil-gas-cybersecurity-assessment --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-oil-gas-cybersecurity-assessment .claude/skills/performing-oil-gas-cybersecurity-assessment && 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-oil-gas-cybersecurity-assessment
GitHub stars
34k
Token cost
~4k tokens
SKILL.md length
392 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Conduct cybersecurity assessments of upstream, midstream, and downstream oil and gas operations, covering pipeline SCADA, refinery DCS, safety instrumented systems, and remote wellhead RTUs, and…

  • Works in 2 steps: Scope Assessment Based on Facility Type → Assess Pipeline SCADA Security
  • Assessing a refinery
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 2 more sections
  • Runs Python scripts from its folder

What it does

Performing Oil Gas Cybersecurity Assessment is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Conduct cybersecurity assessments of upstream, midstream, and downstream oil and gas operations, covering pipeline SCADA, refinery DCS, safety instrumented systems, and remote wellhead RTUs, and evaluate compliance with API 1164, TSA Pipeline Security Directives, and IEC 62443. Use when assessing a refinery, pipeline, or production facility or preparing for TSA/API compliance audits; not for IT-only or purely physical-security assessments.

Its SKILL.md is about 4k 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 Security review. 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

  • Assessing a refinery
  • Production facility
  • Preparing for TSA/API compliance audits
  • Not for IT-only

Example prompts

  • “/performing-oil-gas-cybersecurity-assessment”

Requirements

  • Python 3

Workflow steps

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

  1. Scope Assessment Based on Facility Type
  2. Assess Pipeline SCADA Security

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 Oil Gas Cybersecurity Assessment loads about 4k tokens when it runs, and up to ~4.4k if it reads all its reference files. Until then it costs about 122 tokens; SKILL.md has 392 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~122
When it runs · the whole SKILL.md, loaded when a task matches
~4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.4k

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). 392 words, ~3,989 tokens.

Download SKILL.mdSave it as .claude/skills/performing-oil-gas-cybersecurity-assessment/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
performing-oil-gas-cybersecurity-assessment
description
Conduct cybersecurity assessments of upstream, midstream, and downstream oil and gas operations, covering pipeline SCADA, refinery DCS, safety instrumented systems, and remote wellhead RTUs, and evaluate compliance with API 1164, TSA Pipeline Security Directives, and IEC 62443. Use when assessing a refinery, pipeline, or production facility or preparing for TSA/API compliance audits; not for IT-only or purely physical-security assessments.
domain
cybersecurity
subdomain
ot-ics-security
tags
ot-security, ics, scada, industrial-control, iec62443, oil-gas, pipeline-security, api1164
version
1.0.0
author
mahipal
license
Apache-2.0
nist_csf
PR.IR-01, DE.CM-01, ID.AM-05, GV.OC-02
mitre_attack
T1078, T1190, T1059, T0816, T0836

Performing Oil & Gas Cybersecurity Assessment

When to Use

  • When conducting a cybersecurity assessment of a refinery, pipeline, or production facility
  • When preparing for TSA Pipeline Security Directive compliance (SD-01, SD-02)
  • When assessing cybersecurity posture against API Standard 1164 (Pipeline SCADA Security)
  • When evaluating the security of remote wellhead SCADA systems and satellite communications
  • When a merger, acquisition, or regulatory audit requires a comprehensive OT security evaluation

Do not use for IT-only corporate network assessments of oil and gas companies, for physical security assessments without a cyber component, or for environmental compliance assessments.

Prerequisites

  • Written authorization from facility management and operations team
  • Understanding of oil and gas operations (upstream, midstream, downstream processes)
  • Familiarity with API 1164, TSA SD-01/SD-02, IEC 62443, and NIST CSF
  • Passive monitoring tools for OT network traffic capture
  • Access to network diagrams, SCADA architecture documentation, and safety studies (HAZOP)

Workflow

Step 1: Scope Assessment Based on Facility Type

Oil and gas facilities have unique characteristics based on their operational segment that affect the assessment approach.

yaml
# Oil & Gas Cybersecurity Assessment Scope
facility:
  name: "Gulf Coast Refinery"
  segment: "Downstream"
  capacity: "250,000 barrels per day"
  regulatory: ["TSA SD-02", "API 1164", "IEC 62443", "NIST CSF"]

assessment_areas:
  process_control:
    description: "Refinery DCS and SCADA systems"
    systems:
      - "Honeywell Experion DCS - main process control"
      - "Yokogawa CENTUM VP - hydrocracker unit"
      - "Triconex SIS - emergency shutdown systems"
      - "Allen-Bradley PLCs - utilities and tank farm"
    protocols: ["Modbus/TCP", "OPC UA", "HART", "Foundation Fieldbus"]

  pipeline_scada:
    description: "Pipeline SCADA for crude receipt and product dispatch"
    systems:
      - "ABB RTU560 - pipeline RTUs at pump stations"
      - "GE iFIX SCADA - pipeline control center"
      - "Flow computers - custody transfer metering"
    protocols: ["DNP3", "Modbus RTU over serial", "IEC 60870-5-104"]
    communications: ["Licensed radio", "Leased line", "Satellite (VSAT)"]

  safety_systems:
    description: "Safety Instrumented Systems and fire/gas detection"
    systems:
      - "Schneider Triconex 3008 - process SIS"
      - "Honeywell FSC - fire and gas"
      - "Combustion turbine protection systems"
    criticality: "SIL 2/3 rated - highest priority"

  remote_access:
    description: "Vendor and operator remote access to OT"
    methods:
      - "Citrix-based remote access to SCADA terminals"
      - "VPN to vendor support for DCS maintenance"
      - "Satellite communication to remote pump stations"

  physical_security:
    description: "Physical security integration with cyber"
    systems:
      - "Access control systems (badge readers)"
      - "CCTV with IP network connectivity"
      - "Perimeter intrusion detection"

compliance_mapping:
  tsa_sd_02:
    - "Implement network segmentation between IT and OT"
    - "Develop and maintain a Cybersecurity Implementation Plan (CIP)"
    - "Establish a Cybersecurity Assessment Program"
    - "Report cybersecurity incidents to CISA within 24 hours"
    - "Implement access control measures for critical OT systems"
  api_1164:
    - "Risk-based cybersecurity program for pipeline SCADA"
    - "Asset identification and classification"
    - "Network security and access control"
    - "Personnel security and training"
    - "Incident response and recovery"
Step 2: Assess Pipeline SCADA Security

Pipeline SCADA systems have unique challenges including long-distance communications over untrusted media, unmanned remote sites, and custody transfer integrity requirements.

python
#!/usr/bin/env python3
"""Pipeline SCADA Security Assessment Tool.

Evaluates security of pipeline SCADA systems against
API 1164 and TSA Pipeline Security Directive requirements.
"""

import json
import sys
from dataclasses import dataclass, field, asdict
from datetime import datetime


@dataclass
class AssessmentFinding:
    finding_id: str
    category: str
    severity: str
    title: str
    description: str
    affected_systems: list
    regulatory_reference: str
    remediation: str
    timeline: str


@dataclass
class ComplianceCheck:
    requirement_id: str
    description: str
    standard: str
    status: str  # compliant, partial, non-compliant
    evidence: str
    gap: str = ""


class PipelineSCADAAssessment:
    """Pipeline SCADA security assessment per API 1164 / TSA SD-02."""

    def __init__(self, facility_name):
        self.facility = facility_name
        self.findings = []
        self.compliance_checks = []
        self.finding_counter = 1

    def assess_network_architecture(self, architecture_data):
        """Evaluate pipeline SCADA network architecture."""
        checks = []

        # TSA SD-02: Network segmentation between IT and OT
        if not architecture_data.get("it_ot_segmentation"):
            self.findings.append(AssessmentFinding(
                finding_id=f"OG-{self.finding_counter:03d}",
                category="Network Architecture",
                severity="critical",
                title="No IT/OT Network Segmentation",
                description=(
                    "Pipeline SCADA network is not segmented from corporate IT. "
                    "An attacker compromising the corporate network could pivot "
                    "directly to pipeline control systems."
                ),
                affected_systems=["Pipeline SCADA servers", "RTU communications"],
                regulatory_reference="TSA SD-02 Section 2.1; API 1164 Section 7",
                remediation="Deploy DMZ with industrial firewall between IT and pipeline SCADA",
                timeline="30 days",
            ))
            self.finding_counter += 1

        # Check for encrypted RTU communications
        if architecture_data.get("rtu_comm_encrypted") is False:
            self.findings.append(AssessmentFinding(
                finding_id=f"OG-{self.finding_counter:03d}",
                category="Communication Security",
                severity="high",
                title="Unencrypted Pipeline RTU Communications",
                description=(
                    "DNP3 communications between control center and remote RTUs "
                    "traverse radio/satellite links without encryption. An attacker "
                    "with radio access could intercept or inject SCADA commands."
                ),
                affected_systems=["Pipeline RTUs", "SCADA master station"],
                regulatory_reference="API 1164 Section 7.3; IEC 62351",
                remediation="Deploy DNP3 Secure Authentication or VPN tunnel for RTU links",
                timeline="90 days",
            ))
            self.finding_counter += 1

        # Check remote pump station physical security
        if not architecture_data.get("remote_site_intrusion_detection"):
            self.findings.append(AssessmentFinding(
                finding_id=f"OG-{self.finding_counter:03d}",
                category="Physical-Cyber Convergence",
                severity="high",
                title="Remote Pump Stations Lack Physical Intrusion Detection",
                description=(
                    "Unmanned pump stations along the pipeline corridor lack physical "
                    "intrusion detection systems. An attacker could gain physical access "
                    "to RTUs and SCADA communication equipment without detection."
                ),
                affected_systems=["Remote pump station RTUs and networking equipment"],
                regulatory_reference="TSA SD-02 Section 2.3; API 1164 Section 10",
                remediation="Install intrusion detection with cellular alerting at remote sites",
                timeline="60 days",
            ))
            self.finding_counter += 1

    def assess_custody_transfer(self, metering_data):
        """Assess security of custody transfer metering systems."""
        if not metering_data.get("flow_computer_auth"):
            self.findings.append(AssessmentFinding(
                finding_id=f"OG-{self.finding_counter:03d}",
                category="Custody Transfer Integrity",
                severity="critical",
                title="Flow Computer Lacks Authentication",
                description=(
                    "Custody transfer flow computers accept unauthenticated Modbus "
                    "commands allowing meter factor and flow calculation parameters "
                    "to be modified. This could enable financial fraud through "
                    "manipulation of custody transfer measurements."
                ),
                affected_systems=["Flow computers at custody transfer points"],
                regulatory_reference="API 1164 Section 8; API MPMS Chapter 21",
                remediation="Implement authenticated access to flow computers; deploy audit logging",
                timeline="45 days",
            ))
            self.finding_counter += 1

    def check_tsa_compliance(self):
        """Evaluate compliance with TSA Pipeline Security Directives."""
        tsa_requirements = [
            ComplianceCheck("TSA-01", "Cybersecurity Coordinator designated",
                           "TSA SD-01", "compliant", "CySec coordinator appointed"),
            ComplianceCheck("TSA-02", "Incident reporting to CISA within 24 hours",
                           "TSA SD-01", "partial", "Process exists but not tested",
                           gap="Need tabletop exercise to validate reporting timeline"),
            ComplianceCheck("TSA-03", "Cybersecurity Implementation Plan",
                           "TSA SD-02", "non-compliant", "No formal CIP exists",
                           gap="Develop and submit CIP to TSA within 90 days"),
            ComplianceCheck("TSA-04", "Network segmentation between IT and OT",
                           "TSA SD-02", "non-compliant", "Flat network observed",
                           gap="Implement DMZ and zone-based segmentation"),
            ComplianceCheck("TSA-05", "Access control for critical OT systems",
                           "TSA SD-02", "partial", "Shared accounts on SCADA",
                           gap="Implement individual accounts with role-based access"),
            ComplianceCheck("TSA-06", "Continuous monitoring and detection",
                           "TSA SD-02", "non-compliant", "No OT IDS deployed",
                           gap="Deploy OT intrusion detection (Dragos/Nozomi/Claroty)"),
            ComplianceCheck("TSA-07", "Patch management for critical systems",
                           "TSA SD-02", "partial", "Ad hoc patching only",
                           gap="Establish formal OT patch management program"),
        ]
        self.compliance_checks.extend(tsa_requirements)

    def generate_report(self):
        """Generate comprehensive assessment report."""
        report = []
        report.append("=" * 70)
        report.append(f"OIL & GAS CYBERSECURITY ASSESSMENT REPORT")
        report.append(f"Facility: {self.facility}")
        report.append(f"Date: {datetime.now().strftime('%Y-%m-%d')}")
        report.append("=" * 70)

        # Findings summary
        report.append(f"\nFINDINGS: {len(self.findings)}")
        for sev in ["critical", "high", "medium", "low"]:
            count = sum(1 for f in self.findings if f.severity == sev)
            if count:
                report.append(f"  {sev.upper()}: {count}")

        for f in self.findings:
            report.append(f"\n  [{f.finding_id}] [{f.severity.upper()}] {f.title}")
            report.append(f"    Category: {f.category}")
            report.append(f"    {f.description}")
            report.append(f"    Regulatory: {f.regulatory_reference}")
            report.append(f"    Remediation: {f.remediation} ({f.timeline})")

        # Compliance summary
        report.append(f"\n{'='*70}")
        report.append("TSA PIPELINE SECURITY DIRECTIVE COMPLIANCE")
        report.append("=" * 70)
        for c in self.compliance_checks:
            icon = "+" if c.status == "compliant" else "~" if c.status == "partial" else "-"
            report.append(f"  [{icon}] {c.requirement_id}: {c.description}")
            report.append(f"      Status: {c.status.upper()}")
            if c.gap:
                report.append(f"      Gap: {c.gap}")

        return "\n".join(report)


if __name__ == "__main__":
    assessment = PipelineSCADAAssessment("Gulf Coast Refinery")

    assessment.assess_network_architecture({
        "it_ot_segmentation": False,
        "rtu_comm_encrypted": False,
        "remote_site_intrusion_detection": False,
    })

    assessment.assess_custody_transfer({
        "flow_computer_auth": False,
    })

    assessment.check_tsa_compliance()
    print(assessment.generate_report())
Show full SKILL.md (199 more words)Show less

Key Concepts

TermDefinition
API 1164American Petroleum Institute standard for Pipeline SCADA Security providing a risk-based framework for cybersecurity of pipeline control systems
TSA Pipeline Security DirectivesMandatory cybersecurity requirements issued by TSA for pipeline operators including SD-01 (reporting) and SD-02 (implementation)
Custody TransferTransfer of ownership of petroleum products between parties, requiring metering system integrity to prevent financial fraud
DCSDistributed Control System used in refineries for continuous process control with redundant controllers and operator stations
Remote Terminal Unit (RTU)Field device at remote pipeline sites that collects sensor data and executes control commands, communicating via radio/satellite
Safety Integrity Level (SIL)IEC 61511 rating for safety instrumented functions, with SIL 1-4 defining probability of failure on demand
HAZOPHazard and Operability Study identifying potential hazards in process design; cybersecurity should be integrated with HAZOP results

Tools & Systems

  • Dragos Platform: OT cybersecurity platform with specific detection for oil and gas threat groups (XENOTIME, KAMACITE, ERYTHRITE)
  • Claroty xDome: Comprehensive asset discovery and vulnerability management for oil and gas OT environments
  • Nozomi Guardian: Network monitoring with support for pipeline protocols (DNP3, Modbus, IEC 60870-5-104)
  • Honeywell Forge Cybersecurity: OT security platform designed for Honeywell DCS environments common in refineries

Output Format

Oil & Gas Cybersecurity Assessment Report
==========================================
Facility: [Name]
Segment: Upstream / Midstream / Downstream
Date: YYYY-MM-DD
Standards: API 1164, TSA SD-02, IEC 62443

FINDINGS:
  Critical: [N]  High: [N]  Medium: [N]  Low: [N]

COMPLIANCE STATUS:
  TSA SD-02: [N]% compliant
  API 1164: [N]% compliant
  IEC 62443: [N]% compliant

© 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-oil-gas-cybersecurity-assessment 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

Performing Oil Gas Cybersecurity Assessment 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.

Performing Oil Gas Cybersecurity Assessment compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Performing Oil Gas Cybersecurity Assessment this skillmukul975/Anthropic-Cybersecurity-Skills34k—~4kAutomated safety check: PassApache-2.0
Deepsec Documentation Guidevercel-labs/deepsec8.1k—~956Automated safety check: PassApache-2.0
Kubernetes Network Security Auditkubeshark/kubeshark12k—~7.3kAutomated safety check: NotesApache-2.0
Native Dependency Updatemono/SkiaSharp5.6k—~4.1kAutomated safety check: PassMIT
Semgrep Security Scantrailofbits/skills7.5k—~3.7kAutomated safety check: NotesCC-BY-SA-4.0
Skillward AuditFangcun-AI/SkillWard143—~2.9kAutomated safety check: PassCustom licence

Similar skills

  • Deepsec Documentation Guide

    vercel-labs/deepsec

    Official

    Points the agent at deepsec's own docs to answer questions about initializing, configuring, resuming, scanning with and extending the vulnerability scanner.

    8.1k GitHub stars~956 tokensUpdated 12 days ago
    SecurityAuto-check passed
  • Hunts for compromised workloads and malicious traffic in a Kubernetes cluster by sweeping network data through Kubeshark MCP, mapped to MITRE ATT&CK.

    12k GitHub stars~7.3k tokensUpdated yesterday
    SecurityAuto-check: notes
  • Update native dependencies (libpng, libexpat, zlib, libwebp, harfbuzz, freetype, libjpeg-turbo, etc.) in SkiaSharp's Skia fork.

    5.6k GitHub stars~4.1k tokensUpdated yesterday
    SecurityAuto-check passed
  • Semgrep Security Scan

    trailofbits/skills

    Official

    Detects languages, proposes rulesets for approval, then runs the approved Semgrep scan across a codebase and merges the output into one SARIF file.

    7.5k GitHub stars~3.7k tokensUpdated yesterday
    SecurityAuto-check: notes
  • Skillward Audit

    Fangcun-AI/SkillWard

    Security-audit a third-party skill bundle (folder with SKILL.md, or .zip / .tar.gz archive) before installing it, using the SkillWard cloud scanner.

    143 GitHub stars~2.9k tokensUpdated 2 mo ago
    SecurityAuto-check passed
  • Security Audit

    TheDecipherist/claude-code-mastery

    Checks a codebase for hardcoded secrets, vulnerable dependencies, weak input handling, weak authentication and unsafe transport settings before deployment or merge.

    551 GitHub stars~1.3k tokensUpdated 5 mo ago
    SecurityAuto-check: notes

More from mukul975/Anthropic-Cybersecurity-Skills

All 644 skills in this repo
  • Campaign Attribution Evidence Analysis

    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.

    34k GitHub stars~2.3k tokensUpdated 1 mo ago
    Auto-check passed
  • Go Malware Analysis in Ghidra

    mukul975/Anthropic-Cybersecurity-Skills

    Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.

    34k GitHub stars~2.8k tokensUpdated 1 mo ago
    Auto-check passed
  • LNK and Jump List Forensics

    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.

    34k GitHub stars~2.8k tokensUpdated 1 mo ago
    Auto-check passed
  • Malware Persistence Analysis with Autoruns

    mukul975/Anthropic-Cybersecurity-Skills

    Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.

    34k GitHub stars~1.2k tokensUpdated 1 mo ago
    Auto-check passed
  • NTFS MFT Deleted File Recovery

    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.

    34k GitHub stars~2.7k tokensUpdated 1 mo ago
    Auto-check passed
  • Network Covert Channel Analysis

    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.

    34k GitHub stars~2k tokensUpdated 1 mo ago
    Auto-check passed

Categories

Questions about Performing Oil Gas Cybersecurity Assessment

What does Performing Oil Gas Cybersecurity Assessment do?

Conduct cybersecurity assessments of upstream, midstream, and downstream oil and gas operations, covering pipeline SCADA, refinery DCS, safety instrumented systems, and remote wellhead RTUs, and…. Performing Oil Gas Cybersecurity Assessment is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Conduct cybersecurity assessments of upstream, midstream, and downstream oil and gas operations, covering pipeline SCADA, refinery DCS, safety instrumented systems, and remote wellhead RTUs, and evaluate compliance with API 1164, TSA Pipeline Security Directives, and IEC 62443.

When should I use Performing Oil Gas Cybersecurity Assessment?

Performing Oil Gas Cybersecurity Assessment fits situations like: assessing a refinery; production facility; preparing for TSA/API compliance audits; not for IT-only.

How do I install Performing Oil Gas Cybersecurity Assessment in Claude Code?

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

How do I install Performing Oil Gas Cybersecurity Assessment in Codex?

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

Can I use Performing Oil Gas Cybersecurity Assessment 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-oil-gas-cybersecurity-assessment -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-oil-gas-cybersecurity-assessment, .gemini/skills/performing-oil-gas-cybersecurity-assessment, .github/skills/performing-oil-gas-cybersecurity-assessment and .opencode/skills/performing-oil-gas-cybersecurity-assessment in your project.

What does Performing Oil Gas Cybersecurity Assessment need to run?

Going by SKILL.md and its folder, Performing Oil Gas Cybersecurity Assessment needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Performing Oil Gas Cybersecurity Assessment 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 Oil Gas Cybersecurity Assessment 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 Oil Gas Cybersecurity Assessment use?

Performing Oil Gas Cybersecurity Assessment 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 Oil Gas Cybersecurity Assessment use?

About 4k tokens (SKILL.md is roughly 16k 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 392 tokens, read only when the agent opens those files.

What are the alternatives to Performing Oil Gas Cybersecurity Assessment?

Skills that share tags, products or a category with Performing Oil Gas Cybersecurity Assessment: Deepsec Documentation Guide (vercel-labs/deepsec, 8.1k stars), Kubernetes Network Security Audit (kubeshark/kubeshark, 12k stars), Native Dependency Update (mono/SkiaSharp, 5.6k stars) and Semgrep Security Scan (trailofbits/skills, 7.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Performing Oil Gas Cybersecurity Assessment?

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.