What is an Autonomous System Number (ASN)?

An Autonomous System Number (ASN) is a unique global identifier assigned to an Autonomous System (AS), which is a large network or group of networks that has a single, unified routing policy. Internet Service Providers (ISPs), tech companies, and universities each have their own ASN to manage their corner of the internet.

The internet is not a single entity. It is a massive ‘network of networks’ connected together. An ASN is like a postal code for these huge networks, allowing them to find each other and exchange data efficiently.

Without ASNs, routing traffic across the globe would be chaotic and unmanageable. They provide the structure needed for the internet’s core routing protocol to function. Each AS uses this number to announce its presence and the IP addresses it controls to the rest of the internet.

The concept originated in the early days of the internet’s precursor, ARPANET. As the network grew, a more scalable system was needed to manage how different networks communicated. This led to the development of the Autonomous System framework.

Initially, ASNs were 16-bit numbers, allowing for about 65,536 unique identifiers. As the internet expanded rapidly, it became clear this would not be enough. To prevent exhaustion, a 32-bit ASN format was introduced, creating over 4 billion possible numbers and ensuring room for future growth.

How ASNs Technically Work

The technical process behind ASNs is managed by the Border Gateway Protocol (BGP). BGP is the routing protocol that connects the internet’s independent networks together. It is responsible for finding the best paths for data to travel from its source to its destination.

When an Autonomous System connects to the internet, its routers use BGP to announce the IP address prefixes it controls. These announcements are sent to its neighboring ASes. Think of it like a network saying, “To reach these specific IP addresses, send your traffic through me, using my ASN.”

These neighboring networks then process this information and pass it along to their own neighbors. This chain of announcements propagates across the internet, building a massive, constantly updated map of network reachability. Every router running BGP holds a table of these paths.

The path itself is recorded as a sequence of ASNs, known as an AS-PATH. For example, a path might look like ASN1-ASN2-ASN3. This tells a router that to reach a destination in ASN3, it must first go through ASN1 and then ASN2.

BGP routers use the AS-PATH attribute to determine the shortest path to a destination. A shorter AS-PATH is generally preferred, as it implies fewer network hops. This is a primary factor in how routing decisions are made on the internet’s backbone.

These connections between Autonomous Systems fall into two main categories: peering and transit. Peering is typically a settlement-free agreement between two networks of similar size to exchange traffic directly. This is common between large ISPs or content providers.

Transit, on the other hand, is a commercial relationship. A smaller network pays a larger network (a transit provider) for access to the entire internet. The smaller network sends all its outbound traffic to the transit provider, who then routes it to its final destination.

The allocation of ASNs is managed by the Internet Assigned Numbers Authority (IANA), which delegates the responsibility to five Regional Internet Registries (RIRs). Each RIR is responsible for a specific geographic region of the world. An organization must apply to its corresponding RIR to be assigned an ASN, demonstrating a clear need for unique routing policies and a set of IP addresses.

The Five Regional Internet Registries (RIRs)

• ARIN (American Registry for Internet Numbers): Manages ASNs and IP addresses for the United States, Canada, and parts of the Caribbean.
• RIPE NCC (Réseaux IP Européens Network Coordination Centre): Serves Europe, the Middle East, and parts of Central Asia.
• APNIC (Asia-Pacific Network Information Centre): Covers East Asia, Australia, South Asia, and the Pacific nations.
• LACNIC (Latin America and Caribbean Network Information Centre): Responsible for Latin America and parts of the Caribbean.
• AFRINIC (African Network Information Centre): Manages resources for the entire African continent.

ASN Use Cases: Three Scenarios

Understanding ASNs is not just for network engineers. The data provides valuable context for security, marketing, and fraud detection. Here are three distinct scenarios showing how ASN information is applied.

Case Study 1: E-commerce DDoS Mitigation

An online fashion retailer, “Luxe Threads,” was launching a highly anticipated seasonal collection. Minutes into the launch, their website slowed to a crawl and became completely unresponsive. The company was losing thousands of dollars in sales with every passing minute of downtime.

Their IT team quickly identified the issue as a distributed denial-of-service (DDoS) attack. A massive flood of fake traffic was overwhelming their servers. The attack was coming from tens of thousands of unique IP addresses, making traditional IP-based blocking ineffective.

By analyzing the traffic, the security team found a pattern. A significant portion of the malicious requests, over 70%, originated from IPs belonging to just four specific ASNs. These ASNs were known in the security community for hosting compromised devices and botnet command-and-control servers.

Instead of trying to block an endless list of IPs, the team implemented a new rule in their Web Application Firewall (WAF). The rule was simple: challenge and then block all incoming traffic originating from the four malicious ASNs. This was a much broader but more effective approach.

The effect was immediate. The attack traffic dropped by over 70%, and the website’s servers were no longer overwhelmed. Legitimate customers could access the site again, and the sale was salvaged. By using ASN data, Luxe Threads turned an impossible situation into a manageable one, protecting their revenue and reputation.

Case Study 2: B2B Lead Qualification and Prioritization

“CloudCorp,” a B2B software company selling enterprise cloud solutions, had a lead generation problem. Their marketing team was successful at getting form fills on their website, but the sales team was struggling. They spent too much time chasing leads that turned out to be students, small businesses, or competitors doing research.

The core issue was a lack of context. A lead from a generic email address like ‘user@gmail.com’ gave no indication of the person’s company or potential value. The sales team needed a way to instantly identify high-value prospects from their target account list.

They implemented a solution using an IP intelligence API. When a user submitted a demo request form, the system captured their IP address. In the background, the API looked up the IP to find its associated ASN and the organization that owned it.

This new data was added directly into their CRM. Now, a lead from a generic email could be instantly enriched with valuable company information. For example, an IP address belonging to Microsoft’s ASN (AS8075) immediately told the sales team that the lead was from a major enterprise, even if they used a personal email.

Leads from ASNs of Fortune 500 companies were automatically flagged as ‘high-priority’ and routed to senior account executives. Leads from residential ISPs were routed to a nurturing campaign. This ASN-based system allowed CloudCorp to prioritize their efforts, leading to a 50% increase in sales rep efficiency and a significant lift in enterprise sales conversions.

Case Study 3: Publisher Ad Fraud Detection

“AdPlify,” a digital ad network, faced a crisis of confidence. Their advertisers were seeing high click-through rates but low conversion rates. They suspected they were paying for fraudulent clicks generated by bots, not real users, and threatened to pull their ad spend.

AdPlify’s fraud team knew that much of this invalid traffic originated from servers in data centers, not from the devices of actual consumers. Bots are cheap to run on cloud infrastructure. The challenge was to differentiate this server-based traffic from legitimate human traffic.

The solution was to analyze the ASN of every single click. The team built a system that categorized ASNs. ASNs belonging to major residential and mobile ISPs like Comcast (AS7922) or Verizon (AS701) were classified as ‘consumer-grade’. ASNs belonging to hosting providers like Amazon Web Services (AS16509) or DigitalOcean (AS14061) were flagged as ‘non-human’ or ‘data center’ traffic.

They implemented a real-time filter. Clicks originating from the data center ASN list were invalidated and not charged to the advertiser. This provided a clean, transparent view of campaign performance. They could now show advertisers exactly how much fraudulent traffic they were blocking on their behalf.

By using ASN classification, AdPlify cleaned up its traffic supply chain. Advertiser trust was restored, which stopped customer churn and stabilized revenue. The network was able to position itself as a premium, fraud-free platform, attracting higher-paying clients.

The Financial Impact of Using ASN Data

Using ASN data is not just a technical exercise; it has a direct and measurable impact on a company’s bottom line. The insights derived from this data can reduce costs, protect revenue, and improve operational efficiency.

For the e-commerce store Luxe Threads, the financial impact was clear. Let’s assume their flash sale was projected to generate $100,000 per hour. A 4-hour DDoS-induced outage would have resulted in a $400,000 revenue loss, not including the damage to their brand reputation. By using ASN blocking to resolve the issue in minutes, they protected nearly all of that revenue.

In the case of the B2B company CloudCorp, the ROI came from sales team efficiency. Imagine a team of 30 sales reps, each saving an average of 4 hours per week by not chasing bad leads. That’s 120 hours of productive time reclaimed every week. At a loaded cost of $60 per hour per rep, that translates to $7,200 in weekly savings, or over $374,000 annually.

For the ad network AdPlify, the financial benefit was twofold: fraud prevention and customer retention. If they processed $20 million in ad spend per month and 10% of it was fraudulent, they were preventing $2 million in wasted ad spend for their clients. This justification for their fees prevented advertiser churn, which is far more cost-effective than acquiring new customers.

These examples show that ASN data, when applied correctly, is a valuable business asset. It provides a layer of intelligence that can be used to make smarter, faster, and more profitable decisions across different departments.

Strategic Nuance: Advanced ASN Insights

Simply knowing what an ASN is isn’t enough. Gaining a strategic advantage requires understanding its limitations and advanced applications. Many businesses miss opportunities by having a surface-level view of this data.

Myths vs. Reality

A common myth is that an ASN is just another name for an IP address. The reality is that an ASN represents a collection of thousands or even millions of IP addresses that all share the same routing policy. It is a macro-level identifier, while an IP is a micro-level one.

Another dangerous misconception is that blocking an entire ASN is always a smart security move. While effective against attacks from smaller, clearly malicious networks, this is a terrible idea for large, multipurpose ASNs. Blocking an ASN like Amazon’s AWS (AS16509) would block a huge portion of the legitimate web, including countless businesses and services that rely on it.

Effective ASN-based security is not about blanket blocking. It is about using the ASN as a data point to calculate a risk score. An IP from a data center ASN making a high volume of login attempts is more suspicious than one from a residential ASN.

Advanced Tactical Uses

Beyond security, ASN data can be used for competitive intelligence. By identifying the ASNs that host your competitors’ websites and applications, you can learn about their infrastructure choices. Are they using a premium cloud provider for performance, or a budget host to save costs? This can inform your own technology strategy.

Network performance can also be optimized using ASN path analysis. If a large segment of your customers is located in a specific region and you notice that traffic from their ASNs takes a long, inefficient route to your servers, you might decide to partner with a CDN or hosting provider with better connectivity (peering) to those specific networks.

A highly advanced security tactic is monitoring BGP announcements related to your own ASNs and IP prefixes. Sudden, unauthorized changes can be a sign of BGP hijacking, where an attacker falsely announces they control your IP space to intercept your traffic. Early detection is critical to stopping such an attack.

Abisola

Meet Abisola! As the content manager at ClickPatrol, she’s the go-to expert on all things fake traffic. From bot clicks to ad fraud, Abisola knows how to spot, stop, and educate others about the sneaky tactics that inflate numbers but don’t bring real results.

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