Security Strategy, Plan, Budget, Vulnerability Management, Vulnerability Management

Attack Surface Management: Overview | Security Weekly Labs


Though the term Attack Surface Monitoring (ASM) doesn’t specifically refer to external threats, that’s what this market currently focuses on. In short, products in this category aim to catalogue and help manage an organization’s exposed assets. From this simple definition, the players in this space diverge into various subcategories. The core group we’re focused on for the purposes of this group test are products that largely replace the function of an OSINT assessment, an external network vulnerability assessment and some portions of a penetration test.

An independent resource operated by the cybersecurity professionals at Security Weekly and built on the foundation of SC Media’s SC Labs, SW Labs is a clearinghouse for useful and relevant product and services information that enables vendor and buyer to meet on common ground. The aim of this particular report is to share what we’ve learned about the attack surface management space, to clearly define it as a category, and to provide useful context for the individual product reviews that accompany this report.

To see specific methodology used for the reviews in this category, click here.


Below is a list of product reviews conducted under this category. Again, we recommend reading through this overview in its entirety before digging into individual reviews, but knowing which offerings were evaluated may offer helpful perspective as you do so.


Attack Surface Management is a relatively new category. After discussing it with dozens of practitioners, analysts and founders, it seems clear that this space was born out of a need to fill a gap between vulnerability management tools and penetration testing. At its core, Attack Surface Management is asset discovery and management for exposed assets.

Vulnerability management tools are the most closely related products to ASM and require precise input to give comprehensive output. If we forget to include a website, network segment, API or mobile application - they won’t get scanned. If we’re not aware of Shadow IT or abandoned cloud projects, they won’t be included. Penetration tests will discover some of these gaps, but also have a few shortcomings. First, that penetration tests are periodic in nature: most organizations only have one or two pen tests performed per year. Second, that they are scope and time-limited. Performed on a ‘best effort’ basis, penetration tests will also potentially miss vulnerable assets.

Asset management is a very different challenge when it occurs on networks and in environments we don’t have complete control over. A ‘ping scan’ isn’t going to find an open S3 bucket. An ARP scan isn’t going to discover a legacy domain pointing to forgotten cloud infrastructure. A vulnerability scanner isn’t going to discover enterprise credentials embedded in a personal GitHub project.

New tools and techniques are required to discover, monitor and manage these assets. They began to emerge years ago as open source projects and reconnaissance tools used by penetration testers. Now, ASM products are using these same techniques (and in many cases, using the same open source tools behind the scenes) to discover this additional attack surface most organizations are currently unaware of.

Currently, the asset discovery and management market is largely focused on identifying internal assets, where an asset is defined as anything with an IP address. In the ASM market, every product is 100% focused on external assets (for now). Perhaps an asset management product could be used to catalogue external assets with IP addresses, but IP-based assets are often a tiny fraction of the external exposed surface. It is a bit like comparing a household vacuum cleaner to a Zamboni. Both products are dedicated to cleaning surfaces, but in very different places using very different methods.

High-profile breach examples: could ASM have helped?

A number of high-profile breaches have occurred due to exposures an organization wasn’t aware of. The Buffer breach occurred because a MongoHQ engineer reused a password that was exposed in an Adobe breach. The Columbia Casualty Company sued Cottage Health System to recover a payout for a cyber breach insurance claim. Why? The insurance company found out that the breach occurred because patient data was stored on an FTP server with anonymous access enabled.

The infamous Equifax breach occurred, not because Equifax was unaware of the danger, but (in part) because they failed to find struts in their own environment before attackers did. There was no software asset inventory that listed Struts as a component of a legacy system exposed to the public Internet. Additionally, dynamic and static code analysis tools failed to identify Struts, despite employees’ best efforts.

Each of these examples share the same pattern. There’s a risky public exposure that organizations weren’t aware of or failed to discover in time. Attackers know what works, so to them, the attack path is clear. Defenders are working with tools literally telling them that there are hundreds of thousands of paths the attack could come from! Many of the attack surface management tools we’ll be reviewing would have identified and drawn attention to each of these problems and aim to make the most likely attack paths as clear as possible.

While testing these ASM products, two questions kept popping up: how does this differ from existing asset management or vulnerability management offerings, and why aren’t those existing vendors active in this space yet? We explore both these questions a bit more below.

How is ASM different from external network vulnerability scans?

In the past two decades, vulnerability scanners competed over how much data they could create. More recently, these same vendors are beginning to compete over how much data they can safely ignore. ASM products have emerged in an alert-fatigue-aware era. This awareness is evident in most products we tested.

One of the classic issues with vulnerability management products is their historical close ties to the CVE vulnerability database and CVSS scoring system. Penetration testers know well that some of the most vulnerable findings don’t even receive scores – they’re often simply listed as “informational”, never to be noticed by most organizations. This is especially the case in regulated industries required to remediate all vulnerabilities with a certain score or higher.

The ASM products that aim to prioritize findings (not all do) don’t rely on vulnerability databases or CVSS scores. Rather, they look at how relevant a finding is from an attacker’s perspective (e.g. Is this something I can use to break in?). They also look at customer-provided and environmental context. For example, has it been marked as a critical asset or is it adjacent to a critical asset. It’s worth noting that a market for vulnerability prioritization already exists. Some of these prioritization products already integrate with ASM products.

Here are a few other attributes we found to be unique to ASM products:

  • ASM products can start with minimal input – as little as a company name and nothing more. From that starting point, or seed, ASM products will discover and explore other, related properties, subsidiaries, and assets. For example, if you start with a parent company, it’s possible an ASM product will discover a one-off project abandoned and forgotten by a subsidiary company three years ago. This concept of ‘seed discovery’ happens through a variety of methods: website scraping, subdomain guessing, business record lookups, domains with common WHOIS information, information in certificate metadata and many more.
  • Several ASM vendors will score findings based on how ‘attractive’ they are to attackers. While the source for this attractiveness score is part of their secret sauce, it is presumably the product of penetration testing experience and breach analysis (e.g. what gets attacked during actual breaches?).
  • Many ASM products gather additional data that an analyst would typically have to enrich through manual processes. For example, an analyst might not recognize the IP address attached to a finding. Is it ours? Is it something we have hosted somewhere? Does it belong to a third party? They’ll open another tab to check the ownership records for the IP. Many ASM products do this work for you, automatically tagging assets as Linode or AWS if they are owned by these public cloud providers.
  • Most ASM products continuously search for new findings and assets. For example, acquire a new subsidiary or register a new domain and the ASM product will likely begin collecting assets from them on some point, with zero input from the operator (at least, in theory – see the individual product reviews for more information). Keep in mind, this continuous search is doing more than checking existing seeds for new assets, it’s looking for new seeds entirely. In theory, if your company acquired another company, some of these ASM products will automatically pick up on this and catalogue the new acquisition’s assets as well.

Why aren’t vulnerability management vendors active in this space?

Our best guess is that, right now, they don’t have to be. The “big three” (Qualys, Rapid7 and Tenable, often referred to collectively as ‘QRT’) are all large, public companies these days, with the resources to acquire innovation. They could build ASM in-house, or they could decide to wait and see what the market comes up with. Either approach is a valid business strategy. This is an evolutionary, not revolutionary market and we wouldn’t be surprised to see vulnerability management vendors make some acquisitions in this space.

One possible reason we haven’t seen established vendors step into this space (with the exception of Palo Alto Networks’ $800m acquisition of Expanse) is that it isn’t well defined yet. There are so many fringe use cases and techniques to discover and explore assets that hardly any of the vendors currently in this space are even close to feature parity. It is worth mentioning that integrations for ASM vendors already exist on asset management platforms (e.g. Axonius, JupiterOne), in vulnerability prioritization products (e.g. Kenna Security) and in the SOAR space (e.g. Palo Alto Cortex XSOAR).

Scanning the entire internet versus on-demand scans

Some competitors perform regular full scans of the entire Internet, so it’s worth exploring any potential drawbacks of an ASM product that doesn’t. We don’t expect this to be a deal killer for most customers unless: 1) the customer needs results within hours (perhaps they’re in the midst of an incident) or 2) the customer needs historical data, which are only guaranteed to exist in data sets belonging to ASM vendors that scan the entire Internet on a regular basis and store it indefinitely. It’s also worth noting that these vendors tend to scan for different types of attack surface data, so none will be direct apples-to-apples comparisons. Most are also missing large chunks of the Internet, as many organizations don’t like being scanned and will automatically send cease-and-desist notices.

There’s a debate within this market as to whether ASM vendors will be able to continue scanning the entire Internet as regulatory situations and legal precedents change. Currently, ASM vendors appear to respect requests to stop scanning certain IP ranges, which seems to have kept potential lawsuits at bay. If this changes, we’ll likely see these ASM vendors move to an on-demand model, which would break the following use cases:

  • Statistical research on the frequency of technology use and exposed vulnerabilities
  • Historical research on the same
  • The third party risk monitoring (aka Cyber “Scorecard”) business model

Defining the market

To further define this market, what it is and what it isn’t, we’ll need to dive further into features and use cases. Finally, we’ll define some subcategories and touch on adjacent categories that are related, but not part of the core market.


For the sake of simplicity, we’ll refer to the components that make up an ‘attack surface’ as assets. Servers, subdomains, API endpoints, certificates, code repositories, accounts, S3 buckets and much more will all be referred to as assets. The best reason for doing this is simply that nearly every vendor and open source project we explore throughout this group test uses the term asset in the same consistent way. JQuery 2.3.4 is an asset. A subsidiary’s Github account is an asset. The IP address of a web server, the web server software running on it and the application hosted on it are all separate assets nested within one another and directly associated with one another.

Attack Surface Management is the primary term we’ll use for this space, though we’ve also seen mapping and monitoring as variations for the Management piece of ASM. Both terms work, but we’ll stick with Management as it’s most commonly used and best describes how the core tools in this market are intended to be used – for managing assets exposed to the public Internet, which can also be described as ‘attack surface’.

Common market challenges

  • False positives
    • Assets related to, but not owned by the customer (asset attribution)
    • Lookalikes – similar domains and company names, but different organizations
  • Completeness
    • Breadth – finding all the attack surface
    • Depth – collecting all the details and metadata related to each entity or asset
    • Types – continually adding new types of assets that can be collected (e.g. checking for GitHub accounts associated with a company, mobile apps, etc)
  • Prioritization
    • The more complete these scans are, the bigger the organizational problem becomes. Prioritization is already a key challenge with the products that aim to surface issues in the asset data they collect
    • Assigning risk scores – can be done without customer input, but can be much more accurate once asset importance and sensitivity is known
  • Validation
    • Less effective validation methods leading to high false positives (Banner grabbing, keyword searches)
    • A few ASM products separate “confirmed” issues from “potential” ones, even providing the proof of confirmed findings. This makes for considerably less work for the analyst tasked with validating these findings.


The technical approaches and features across vendors in this market vary enough that we felt compelled to break it into a few subcategories. Simply, they can be expressed in terms of how deep they go in terms of discovering assets, prioritizing the results and providing the ability to manage the findings. It is tempting to assign greater value to vendors that go deeper, but the value of greater breadth shouldn’t be discounted. Depending on individual needs, use cases and pricing, we wouldn’t be surprised to find our readers choosing favorites from more than one category. For example, the historical research use case may not be supported by vendors more focused on prioritization, as most of these vendors don’t perform full Internet scans.

Internet Asset Research: The simplest category can be described as a scan of the Internet with an interface allowing the database of assets to be queried. In its simplest form, routable IPv4 address ranges and a limited number of interesting ports are scanned. Services are enumerated and metadata collected. Shodan, SecurityTrails, SpySe, RiskIQ and Censys are examples of these, which tend to have freemium offerings. These tools are widely used by researchers and journalists to explore Internet-wide trends. The results could give an idea of the size and breadth of a zero day vulnerability, for example.

For those more interested in specific assets (perhaps just the assets they own), these tools are less useful, as results are often missing, incomplete or outdated.

Use Cases:

  1. Internet Patterns Research
  2. Historical Research
  3. Asset Discovery
  4. 3rd Party or M&A Due Diligence
  5. Attack surface reduction


  1. Detailed asset information
  2. Tagging
  3. Metadata search
  4. Complex queries
  5. API


  • Quick and easy to perform Internet research or a quick targeted assessment
  • Historical data in some cases
  • Freemium or low-cost options


  • Relatively few use cases
  • Gaps in coverage due to requests not to scan some networks or dropped probes

External Asset Monitoring: At the next level, vendors have stepped up to also collecting additional, related assets like certificates, DNS records and ‘technologies’ (e.g. software libraries, software frameworks, network software).

They’ll also monitor for new assets or changes to existing assets. These tools are tailor built for the long-term monitoring of specific groups of assets. Importantly, they aren’t restricted to these groups – it is still possible to use these tools for broad Internet discovery and research outside the customer’s organization (something that largely goes away in other categories). BitDiscovery, Shodan Monitor, RiskIQ Digital Footprint, SecurityTrails SurfaceBrowser and BinaryEdge are examples at this level. Most of these vendors can also be classified as Internet Asset Research as well.

Use Cases:

  • Internet patterns research
  • Historical research
  • Asset discovery and monitoring
  • Third party asset discovery and monitoring
  • M&A due diligence
  • Certificate monitoring
  • Competitive intelligence gathering
  • Attack surface reduction


  • Detailed asset information
  • Tagging
  • Metadata search
  • Alerts on new findings
  • Alert on expiring certificates
  • Detailed software composition analysis (SCA)
  • API


  • Supports both Internet research use case and asset management use case
  • Generally return the most complete dataset on IP-based assets


  • Large amounts of data to validate with no prioritization
  • Missing a some non-IP-based assets

External Asset Management platforms: The major differentiator at this level is a focus on prioritization and management. Prioritization requires performing some level of risk analysis to separate out risky asset features from the benign. Management functionality adds features like active monitoring, team collaboration, ticketing and commenting.

The concept of seed discovery is significant and worth watching in this market. Simply proving a company name could lead to a news article about an acquisition, which leads the ASM engine to begin collecting assets from both the acquired and the acquirer.

Products in this category more commonly scan for assets on demand and do not retain an Internet-wide asset database (with a few exceptions – see the feature matrix for a detailed list of product features). Randori’s Recon product, CyCognito, AlphaWave, Immuniweb, RiskIQ Illuminate, SecurityTrails ASR and Intrigue are the products at this level.

Use Cases:

  • Asset discovery and monitoring
  • Third party vendor discovery
  • External asset management
  • Risk prioritization
  • Risk validation (via either automated or manual penetration testing)


  • Detailed asset information
  • Seed discovery
  • Tagging (manual and automated)
  • Metadata search
  • Alerts on new findings
  • Detailed software composition analysis (SCA)
  • Built for teams with support for commenting
  • Issue management with ability to set status, asset importance
  • Broad integration support
  • API


  • Identifies issues with assets and prioritizes them
  • Discovers risks related to third party vendors
  • Issue tracking and management interfaces
  • Broad integration support


  • Generally don’t support Internet or Historical research use cases
  • False positives are a natural consequence of dynamic asset crawling

Managed External Asset Management Platforms: The primary difference between this category and External Asset Management Platforms is that humans are on staff to validate findings, remove false positives and otherwise ensure the signal to noise ratio is as favorable as possible. While this saves time and effort for the customer, it comes at a price. Bishop Fox’s CAST and Randori’s Attack product are the only examples here (though they differ greatly in goals, pricing. and execution; as such, aren’t likely to see each other in many bakeoffs – see individual reviews for more details).

Use Cases:

  • Everything in the previous category


  • Everything in the previous category, plus
  • Outsourced staff to perform validation on any findings


  • All signal, no noise (in theory – note we did not directly test either of these products)


  • Higher cost

Notable adjacent categories

Third party risk monitoring vendors use similar techniques to gather open intelligence on an organization. However, they use this data to generate risk scores, intended to indicate how safe or risky a business is to work with. The use case is different enough that we’ve decided to evaluate these vendors (BitSight, RiskRecon, Security Scorecard and a few others) in a separate group test.

The Data Loss Detection category scours the Internet for any evidence that a company’s private data (credentials, documents, etc) might be exposed to the public Internet. Examples include Digital Shadows, Terbium Labs and Intelliagg.

Vendors in the Digital Risk Protection category aim to spot any attempts to impersonate an organization, brand or individual. They often also assist with attempts to take down or disrupt these impersonation attempts. Examples include ZeroFOX, PhishLabs, Constella Intelligence and Digital Shadows.

Asset Reputation is a category that catalogues and reports on the behavior of various assets exposed to the public Internet.

GreyNoise, one example in this category, uses a global sensor network to observe the behavior of assets aggressively scanning the Internet. The most common use case for this data is to separate non-malicious noise from potentially malicious actors. Another use case is related to ASM, however. It is possible for customers to use GreyNoise’s database to monitor the behavior of their own assets, or those of subsidiaries or key third-party vendors. If the customer receives an alert that an asset is suddenly behaving maliciously, they can take action.

Also in this category would be services that monitor email and IP blacklists.


There is an immediate need for these products. Nearly every product we tested discovered assets and issues we weren’t previously aware of. Additionally, these were assets and issues that traditional vulnerability management products did not alert us to. The dilemma here is that nearly every product we tested surprised us in different ways with different results. One product discovered a branded mobile app. The others don’t look for mobile apps. Two spotted an old version of JQuery. None of the others did. One found a few domain names the others didn’t find.

Many products had their own niche abilities to discover attack surface that set them apart from the competition. While we can’t recommend buying half a dozen ASM products, this is fairly common in new markets and we do believe the market will more or less achieve feature parity over the next year or two.

With respect to adjacent asset and vulnerability management categories, we don’t expect to see the market to remain fragmented for long. In the next three years, we’ll either see traditional vulnerability management products acquire ASM vendors, or we’ll see ASM vendors begin to challenge and even replace external vulnerability scans. We’ve seen the same trend play out in the endpoint market over the last six years. A simpler, more effective approach, even if incomplete in terms of features, can challenge the incumbents and steal away market share.

After all, we know that complexity is the enemy of security – shouldn’t this principle apply to security products as well?

Adrian Sanabria

Adrian is an outspoken researcher that doesn’t shy away from uncomfortable truths. He loves to write about the security industry, tell stories, and still sees the glass as half full.

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