performing-agentless-vulnerability-scanning

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-agentless-vulnerability-scanning
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summary

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

skill.md
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

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

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)

# Create dedicated scan SSH key pair
ssh-keygen -t ed25519 -f /opt/scanner/.ssh/scan_key -N "" \
  -C "[email protected]"

# 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"
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)

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)

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

# /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}"]
# 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

Related Skills

  • implementing-rapid7-insightvm-for-scanning
  • implementing-wazuh-for-vulnerability-detection
  • deploying-osquery-for-endpoint-monitoring
  • performing-remediation-validation-scanning
how to use performing-agentless-vulnerability-scanning

How to use performing-agentless-vulnerability-scanning on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add performing-agentless-vulnerability-scanning
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/performing-agentless-vulnerability-scanning

The skills CLI fetches performing-agentless-vulnerability-scanning from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/performing-agentless-vulnerability-scanning

Reload or restart Cursor to activate performing-agentless-vulnerability-scanning. Access the skill through slash commands (e.g., /performing-agentless-vulnerability-scanning) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.737 reviews
  • Pratham Ware· Dec 28, 2024

    I recommend performing-agentless-vulnerability-scanning for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Liam Chen· Dec 28, 2024

    Registry listing for performing-agentless-vulnerability-scanning matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ira Bansal· Dec 20, 2024

    Solid pick for teams standardizing on skills: performing-agentless-vulnerability-scanning is focused, and the summary matches what you get after install.

  • Ishan Dixit· Dec 16, 2024

    Keeps context tight: performing-agentless-vulnerability-scanning is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Dec 4, 2024

    We added performing-agentless-vulnerability-scanning from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Piyush G· Nov 23, 2024

    performing-agentless-vulnerability-scanning fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Kofi Chen· Nov 23, 2024

    I recommend performing-agentless-vulnerability-scanning for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Michael Tandon· Nov 19, 2024

    Solid pick for teams standardizing on skills: performing-agentless-vulnerability-scanning is focused, and the summary matches what you get after install.

  • Li Dixit· Nov 7, 2024

    performing-agentless-vulnerability-scanning is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Li Sethi· Oct 26, 2024

    Useful defaults in performing-agentless-vulnerability-scanning — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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