Agent skill

Performing Agentless Vulnerability Scanning

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.

Apache-2.0Auto-check passedSecurity

Install Performing Agentless Vulnerability Scanning

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-agentless-vulnerability-scanning -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-agentless-vulnerability-scanning --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-agentless-vulnerability-scanning .claude/skills/performing-agentless-vulnerability-scanning && 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-agentless-vulnerability-scanning
GitHub stars
34k
Token cost
~3.8k tokens
SKILL.md length
506 words
Files
8 (incl. scripts, references, assets)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.

  • Works in 4 steps: SSH-Based Agentless Scanning (Linux) → WinRM-Based Agentless Scanning (Windows) → Cloud Snapshot Scanning (AWS) → …
  • Tasks that involve Vulnerability scanning
  • SKILL.md covers Overview, When to Use, Prerequisites and Core Concepts, plus 4 more sections
  • Runs Python scripts from its folder; calls ssh

What it does

Performing Agentless Vulnerability Scanning is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.

Its SKILL.md is about 3.8k 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 Security, covering Vulnerability scanning. It works with Linux. 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

  • Tasks that involve Vulnerability scanning

Example prompts

  • “/performing-agentless-vulnerability-scanning”

Requirements

  • Python 3

Workflow steps

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

  1. SSH-Based Agentless Scanning (Linux)
  2. WinRM-Based Agentless Scanning (Windows)
  3. Cloud Snapshot Scanning (AWS)
  4. Vuls Open-Source Agentless Scanner

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 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • ssh

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

  • Network

    No URLs in SKILL.md. Its commands use ssh, which can reach the network depending on how they are called.

    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 Agentless Vulnerability Scanning loads about 3.8k tokens when it runs, and up to ~5.6k if it reads all its reference files. Until then it costs about 57 tokens; SKILL.md has 506 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.6k

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). 506 words, ~3,807 tokens.

Download SKILL.mdSave it as .claude/skills/performing-agentless-vulnerability-scanning/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
performing-agentless-vulnerability-scanning
description
Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.
domain
cybersecurity
subdomain
vulnerability-management
tags
agentless-scanning, vulnerability-assessment, cloud-security, ssh, wmi, snapshot-analysis, vuls, tenable
version
1.0
author
mahipal
license
Apache-2.0
nist_ai_rmf
GOVERN-1.1, MEASURE-2.7, MANAGE-3.1
nist_csf
ID.RA-01, ID.RA-02, ID.IM-02, ID.RA-06
mitre_attack
T1190, T1203, T1068, T1078.004, T1530

Performing Agentless Vulnerability Scanning

Overview

Agentless vulnerability scanning assesses systems for security weaknesses without requiring endpoint agent installation. This approach leverages existing network protocols (SSH for Linux, WMI for Windows), cloud provider APIs for snapshot-based analysis, and authenticated remote checks. Modern cloud platforms like Microsoft Defender for Cloud, Wiz, Datadog, and Tenable perform out-of-band analysis by taking disk snapshots and examining OS configurations and installed packages offline. The open-source tool Vuls provides agentless scanning based on NVD and OVAL data for Linux/FreeBSD systems. This skill covers configuring agentless scans across on-premises, cloud, and containerized environments.

When to Use

  • When conducting security assessments that involve performing agentless vulnerability scanning
  • When following incident response procedures for related security events
  • When performing scheduled security testing or auditing activities
  • When validating security controls through hands-on testing

Prerequisites

  • SSH key-based authentication configured on Linux/Unix targets
  • WMI/WinRM access on Windows targets with appropriate credentials
  • Cloud provider API credentials (AWS IAM, Azure RBAC, GCP IAM)
  • Network access from scanner to target systems on required ports
  • Service account with read-only access to target system configurations
  • Python 3.8+ for custom scanning automation

Core Concepts

Agentless vs Agent-Based Scanning
AspectAgentlessAgent-Based
DeploymentNo software installation neededAgent install on every endpoint
Network dependencyRequires network connectivityWorks offline with cloud sync
Performance impactMinimal on target systemsLight continuous overhead
Coverage depthDepends on protocol/credentialsDeep local access
Cloud snapshot analysisNative capabilityNot applicable
Ideal forCloud VMs, IoT, legacy systems, OTManaged endpoints, laptops
Agentless Scanning Methods
MethodProtocolTarget OSPortUse Case
SSH Remote CommandsSSHLinux/Unix22Package enumeration, config audit
WMI Remote QueryWMI/DCOMWindows135, 445Hotfix enumeration, registry checks
WinRM PowerShellWS-ManWindows5985/5986Remote command execution
SNMP CommunitySNMP v2c/v3Network devices161Device fingerprinting, firmware check
Cloud SnapshotProvider APICloud VMsN/ADisk image analysis
Container RegistryHTTPSContainer images443Image vulnerability scanning
API-BasedREST/HTTPSSaaS/Cloud443Configuration assessment
Show full SKILL.md (184 more words)Show less
Cloud Snapshot Analysis Flow
1. Scanner requests disk snapshot via cloud API
2. Cloud provider creates snapshot of VM root + data disks
3. Scanner mounts snapshot in isolated analysis environment
4. Scanner examines OS packages, configurations, file system
5. Snapshot is deleted after analysis (no persistent copies)
6. Results sent to central management console

Workflow

Step 1: SSH-Based Agentless Scanning (Linux)
bash
# Create dedicated scan SSH key pair
ssh-keygen -t ed25519 -f /opt/scanner/.ssh/scan_key -N "" \
  -C "vuln-scanner@security.local"

# Deploy public key to targets via Ansible
# ansible-playbook deploy_scan_key.yml

# Test connectivity to target
ssh -i /opt/scanner/.ssh/scan_key -o ConnectTimeout=10 \
  scanner@target-host "cat /etc/os-release && dpkg -l 2>/dev/null || rpm -qa"
python
import paramiko
import json

class AgentlessLinuxScanner:
    """SSH-based agentless vulnerability scanner for Linux systems."""

    def __init__(self, key_path):
        self.key_path = key_path

    def connect(self, hostname, username="scanner", port=22):
        """Establish SSH connection to target."""
        client = paramiko.SSHClient()
        client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
        key = paramiko.Ed25519Key.from_private_key_file(self.key_path)
        client.connect(hostname, port=port, username=username, pkey=key,
                       timeout=30, banner_timeout=30)
        return client

    def get_os_info(self, client):
        """Detect OS type and version."""
        _, stdout, _ = client.exec_command("cat /etc/os-release", timeout=10)
        os_release = stdout.read().decode()
        info = {}
        for line in os_release.strip().split("\n"):
            if "=" in line:
                key, val = line.split("=", 1)
                info[key] = val.strip('"')
        return info

    def get_installed_packages(self, client):
        """Enumerate installed packages."""
        # Try dpkg (Debian/Ubuntu)
        _, stdout, _ = client.exec_command(
            "dpkg-query -W -f='${Package}|${Version}|${Architecture}\\n'",
            timeout=30
        )
        output = stdout.read().decode().strip()
        if output:
            packages = []
            for line in output.split("\n"):
                parts = line.split("|")
                if len(parts) >= 2:
                    packages.append({
                        "name": parts[0],
                        "version": parts[1],
                        "arch": parts[2] if len(parts) > 2 else "",
                        "manager": "dpkg"
                    })
            return packages

        # Try rpm (RHEL/CentOS/Fedora)
        _, stdout, _ = client.exec_command(
            "rpm -qa --queryformat '%{NAME}|%{VERSION}-%{RELEASE}|%{ARCH}\\n'",
            timeout=30
        )
        output = stdout.read().decode().strip()
        packages = []
        for line in output.split("\n"):
            parts = line.split("|")
            if len(parts) >= 2:
                packages.append({
                    "name": parts[0],
                    "version": parts[1],
                    "arch": parts[2] if len(parts) > 2 else "",
                    "manager": "rpm"
                })
        return packages

    def check_kernel_version(self, client):
        """Get running kernel version."""
        _, stdout, _ = client.exec_command("uname -r", timeout=10)
        return stdout.read().decode().strip()

    def check_listening_ports(self, client):
        """Enumerate listening network services."""
        _, stdout, _ = client.exec_command(
            "ss -tlnp 2>/dev/null || netstat -tlnp 2>/dev/null",
            timeout=10
        )
        return stdout.read().decode().strip()

    def scan_host(self, hostname, username="scanner"):
        """Perform full agentless scan of a host."""
        print(f"[*] Scanning {hostname}...")
        client = self.connect(hostname, username)

        result = {
            "hostname": hostname,
            "os_info": self.get_os_info(client),
            "kernel": self.check_kernel_version(client),
            "packages": self.get_installed_packages(client),
            "listening_ports": self.check_listening_ports(client),
        }

        client.close()
        print(f"  [+] Found {len(result['packages'])} packages on {hostname}")
        return result
Step 2: WinRM-Based Agentless Scanning (Windows)
python
import winrm

class AgentlessWindowsScanner:
    """WinRM-based agentless vulnerability scanner for Windows."""

    def __init__(self, username, password, domain=None):
        self.username = username
        self.password = password
        self.domain = domain

    def connect(self, hostname, use_ssl=True):
        """Create WinRM session."""
        port = 5986 if use_ssl else 5985
        transport = "ntlm"
        user = f"{self.domain}\\{self.username}" if self.domain else self.username
        session = winrm.Session(
            f"{'https' if use_ssl else 'http'}://{hostname}:{port}/wsman",
            auth=(user, self.password),
            transport=transport,
            server_cert_validation="ignore"
        )
        return session

    def get_installed_hotfixes(self, session):
        """Get installed Windows updates/hotfixes."""
        cmd = "Get-HotFix | Select-Object HotFixID,InstalledOn,Description | ConvertTo-Json"
        result = session.run_ps(cmd)
        if result.status_code == 0:
            return json.loads(result.std_out.decode())
        return []

    def get_installed_software(self, session):
        """Enumerate installed software from registry."""
        cmd = """
        $paths = @(
            'HKLM:\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Uninstall\\*',
            'HKLM:\\SOFTWARE\\WOW6432Node\\Microsoft\\Windows\\CurrentVersion\\Uninstall\\*'
        )
        Get-ItemProperty $paths -ErrorAction SilentlyContinue |
            Where-Object {$_.DisplayName} |
            Select-Object DisplayName, DisplayVersion, Publisher |
            ConvertTo-Json
        """
        result = session.run_ps(cmd)
        if result.status_code == 0:
            return json.loads(result.std_out.decode())
        return []

    def get_os_info(self, session):
        """Get Windows OS details."""
        cmd = "Get-CimInstance Win32_OperatingSystem | Select-Object Caption,Version,BuildNumber,OSArchitecture | ConvertTo-Json"
        result = session.run_ps(cmd)
        if result.status_code == 0:
            return json.loads(result.std_out.decode())
        return {}

    def scan_host(self, hostname):
        """Perform full agentless scan of Windows host."""
        print(f"[*] Scanning {hostname} via WinRM...")
        session = self.connect(hostname)

        result = {
            "hostname": hostname,
            "os_info": self.get_os_info(session),
            "hotfixes": self.get_installed_hotfixes(session),
            "software": self.get_installed_software(session),
        }

        print(f"  [+] Found {len(result['hotfixes'])} hotfixes, "
              f"{len(result['software'])} software entries")
        return result
Step 3: Cloud Snapshot Scanning (AWS)
python
import boto3
import time

class AWSSnapshotScanner:
    """AWS EC2 agentless snapshot-based vulnerability scanner."""

    def __init__(self, region="us-east-1"):
        self.ec2 = boto3.client("ec2", region_name=region)

    def create_snapshot(self, volume_id, description="Security scan snapshot"):
        """Create EBS snapshot for analysis."""
        snapshot = self.ec2.create_snapshot(
            VolumeId=volume_id,
            Description=description,
            TagSpecifications=[{
                "ResourceType": "snapshot",
                "Tags": [
                    {"Key": "Purpose", "Value": "VulnScan"},
                    {"Key": "AutoDelete", "Value": "true"},
                ]
            }]
        )
        snapshot_id = snapshot["SnapshotId"]
        print(f"  [*] Creating snapshot {snapshot_id} from {volume_id}...")

        waiter = self.ec2.get_waiter("snapshot_completed")
        waiter.wait(SnapshotIds=[snapshot_id])
        print(f"  [+] Snapshot {snapshot_id} ready")
        return snapshot_id

    def delete_snapshot(self, snapshot_id):
        """Clean up snapshot after analysis."""
        self.ec2.delete_snapshot(SnapshotId=snapshot_id)
        print(f"  [+] Deleted snapshot {snapshot_id}")

    def scan_instance(self, instance_id):
        """Scan an EC2 instance via snapshot analysis."""
        print(f"[*] Agentless scan of instance {instance_id}")

        instance = self.ec2.describe_instances(
            InstanceIds=[instance_id]
        )["Reservations"][0]["Instances"][0]

        root_volume = None
        for bdm in instance.get("BlockDeviceMappings", []):
            if bdm["DeviceName"] == instance.get("RootDeviceName"):
                root_volume = bdm["Ebs"]["VolumeId"]
                break

        if not root_volume:
            print("  [!] No root volume found")
            return None

        snapshot_id = self.create_snapshot(root_volume)
        try:
            # Analysis would be performed here
            # Mount snapshot, examine packages, check configs
            result = {
                "instance_id": instance_id,
                "snapshot_id": snapshot_id,
                "root_volume": root_volume,
                "platform": instance.get("Platform", "linux"),
                "state": instance["State"]["Name"],
            }
            return result
        finally:
            self.delete_snapshot(snapshot_id)
Step 4: Vuls Open-Source Agentless Scanner
toml
# /etc/vuls/config.toml - Vuls configuration for agentless scanning

[servers]

[servers.web-server-01]
host = "192.168.1.10"
port = "22"
user = "vuls"
keyPath = "/opt/vuls/.ssh/scan_key"
scanMode = ["fast"]

[servers.db-server-01]
host = "192.168.1.20"
port = "22"
user = "vuls"
keyPath = "/opt/vuls/.ssh/scan_key"
scanMode = ["fast-root"]
[servers.db-server-01.optional]
  [servers.db-server-01.optional.sudo]
    password = ""

[servers.container-host-01]
host = "192.168.1.30"
port = "22"
user = "vuls"
keyPath = "/opt/vuls/.ssh/scan_key"
scanMode = ["fast"]
containersIncluded = ["${running}"]
bash
# Run Vuls agentless scan
vuls scan

# Generate report
vuls report -format-json -to-localfile

# View results
vuls tui

Best Practices

  1. Use SSH key-based authentication instead of passwords for Linux scanning
  2. Create dedicated service accounts with minimal read-only privileges for scanning
  3. Always clean up cloud snapshots after analysis to avoid storage costs and data exposure
  4. Combine agentless scanning with agent-based for comprehensive coverage
  5. Schedule scans during low-activity periods to minimize any performance impact
  6. Rotate scanning credentials regularly and store in a secrets vault
  7. Test scanner connectivity before scheduling production scans
  8. Use SNMPv3 with authentication and encryption for network device scanning

Common Pitfalls

  • Using shared credentials across multiple environments without proper segmentation
  • Not cleaning up temporary snapshots in cloud environments
  • Assuming agentless scanning has zero performance impact (network and CPU are used)
  • Missing WinRM/SSH firewall rules causing scan failures on new deployments
  • Not accounting for SSH host key changes causing authentication failures
  • Scanning OT/ICS devices with protocols they cannot safely handle
  • implementing-rapid7-insightvm-for-scanning
  • implementing-wazuh-for-vulnerability-detection
  • deploying-osquery-for-endpoint-monitoring
  • performing-remediation-validation-scanning

© 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 7 other files (scripts, references, assets) in skills/performing-agentless-vulnerability-scanning of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • assets/template.md
  • references/api-reference.md
  • references/standards.md
  • references/workflows.md
  • scripts/agent.py
  • scripts/process.py

Open the folder on GitHubat commit 54a7988

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Works with

Categories

Questions about Performing Agentless Vulnerability Scanning

What does Performing Agentless Vulnerability Scanning do?

Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents. Performing Agentless Vulnerability Scanning is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Configure and execute agentless vulnerability scanning using network protocols, cloud snapshot analysis, and API-based discovery to assess systems without installing endpoint agents.

When should I use Performing Agentless Vulnerability Scanning?

Performing Agentless Vulnerability Scanning fits situations like: tasks that involve Vulnerability scanning.

How do I install Performing Agentless Vulnerability Scanning in Claude Code?

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

How do I install Performing Agentless Vulnerability Scanning in Codex?

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

Can I use Performing Agentless Vulnerability Scanning 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-agentless-vulnerability-scanning -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-agentless-vulnerability-scanning, .gemini/skills/performing-agentless-vulnerability-scanning, .github/skills/performing-agentless-vulnerability-scanning and .opencode/skills/performing-agentless-vulnerability-scanning in your project.

What does Performing Agentless Vulnerability Scanning need to run?

Going by SKILL.md and its folder, Performing Agentless Vulnerability Scanning needs Python for the scripts in its folder and the command-line tools its instructions call (ssh). Our summary lists: Python 3.

Does Performing Agentless Vulnerability Scanning access the network?

SKILL.md contains no URLs. Its commands use ssh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Performing Agentless Vulnerability Scanning 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 Agentless Vulnerability Scanning use?

Performing Agentless Vulnerability Scanning 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 Agentless Vulnerability Scanning use?

About 3.8k tokens (SKILL.md is roughly 15k 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 1.7k tokens, read only when the agent opens those files.

What are the alternatives to Performing Agentless Vulnerability Scanning?

Skills that share tags, products or a category with Performing Agentless Vulnerability Scanning: Write Cve Rule (evdenis/cvehound, 138 stars), Host Cve Validator (infometa/workbuddyskills, 346 stars), Kernel Security (mohitmishra786/low-level-dev-skills, 253 stars) and Alibabacloud Ecs Sec Kernel (aliyun/alibabacloud-ecs-troubleshoot-skills, 148 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Performing Agentless Vulnerability Scanning?

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.