The Granularity Gap

For years, blocking traffic based on Autonomous System Numbers (ASNs) was the de facto standard for mitigating automated threats. If traffic originated from a data center ASN (e.g., AWS, DigitalOcean, or Hetzner), logic dictated it was likely a bot. If it came from a residential ISP (e.g., Comcast or AT&T), it was assumed to be a human.

This binary logic is no longer viable. Relying solely on ASN blocking introduces two critical failures:

High False Positives: Blocking ASNs associated with cloud providers indiscriminately prevents legitimate B2B traffic, webhooks, and SaaS integrations from reaching your endpoints.
High False Negatives: Sophisticated attackers now utilize residential proxy networks, routing malicious traffic through legitimate ISP ASNs that you cannot afford to block.

The Residential Proxy Vector

The commercialization of residential proxy networks (ResIPs) has rendered ASN-based whitelisting obsolete for fraud detection. Threat actors route traffic through devices located in residential households—often unknowingly participating in botnets.

From a network layer perspective, a credential stuffer utilizing a residential proxy appears indistinguishable from a legitimate user. They share the same ASN (e.g., AS7922 for Comcast) and often the same geographic region.

The Consequence: If you rely on ASN blocking, you are defenseless against ResIPs. You cannot block the entire ISP without severing access for your actual customer base.

BYOIP and Infrastructure Obfuscation

Further complicating the landscape is the Bring Your Own IP (BYOIP) protocol. Sophisticated actors can lease clean IP blocks and announce them via hosting providers or cloud networks.

While the underlying infrastructure might be a high-risk data center, the ASN broadcasted could be a misleading or newly registered entity with no negative reputation history. Static ASN blocklists react too slowly to these routing changes.

Implementing Granular Detection

To effectively mitigate threats without destroying user experience, engineers must move from routing-based decisions to intelligence-based decisions.

Below is a comparison of a naive ASN check versus a contextual check using the IPASIS API. The goal is to detect the usage type (VPN, Proxy, Tor) rather than just the network owner.

Python Implementation

import requests

IPASIS_ENDPOINT = "https://api.ipasis.com/json/"
API_KEY = "YOUR_API_KEY"

def assess_risk(ip_address):
    """
    Evaluates IP risk based on behavior and type, not just ASN.
    """
    try:
        response = requests.get(f"{IPASIS_ENDPOINT}{ip_address}?key={API_KEY}")
        data = response.json()

        # 1. Naive ASN check (Insufficient)
        # if data['asn'] == 16509: return "BLOCK" 
        # This would block legitimate AWS hosted webhooks.

        # 2. Granular Risk Assessment (Recommended)
        security = data.get('security', {})
        
        # Block if it is a known residential proxy or malicious crawler
        if security.get('is_res_proxy'):
            return False, "Blocked: Residential Proxy Detected"
            
        if security.get('is_crawler') and not security.get('is_verified_bot'):
            return False, "Blocked: Unverified Crawler"

        # Allow data center traffic if it's not a VPN/Proxy
        if data.get('is_datacenter') and not security.get('is_proxy'):
             return True, "Allowed: Clean Data Center Traffic"

        return True, "Allowed"

    except Exception as e:
        # Fail open or closed depending on risk appetite
        return True, "Allowed (API Error)"

# usage
is_allowed, reason = assess_risk("192.168.1.1")
print(f"Decision: {reason}")

Frequently Asked Questions

Q: Should I stop using ASN blocking entirely?
A: Not necessarily. ASN blocking is useful as a coarse filter for sanctioned entities or specific geolocations where you do no business. However, it should not be your primary logic for bot mitigation or fraud prevention.

Q: Can IPASIS detect proxies hosted on residential ASNs?
A: Yes. We utilize real-time behavioral analysis and global sensor networks to identify IPs acting as exit nodes for residential proxy networks, regardless of the ASN reputation.

Q: How does this impact API latency?
A: IPASIS is built for real-time applications. Our average response time is optimized to ensure that adding granular IP intelligence adds negligible overhead to your request pipeline.

Stop Guessing, Start Detecting

Static lists and ASN rules are blunt instruments in a precision game. To protect your infrastructure from modern threats like residential proxies and VPN hopping, you need real-time intelligence.

Integrate IPASIS today to gain visibility into the true nature of your traffic.

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The Limits of ASN Blocking: Moving Beyond Coarse-Grained Access Control