Every time a new endpoint or third-party service gets added to your application, its attack surface grows. With 73% of organizations experiencing cyberattacks due to unmanaged or unknown assets, this is a daily reality for development teams.
Most developers don’t usually think in terms of “attack surface management” when they’re deploying features, because their focus is more on whether the functionality is working and how it’s performing (and on making sure it’s delivered on time).
Security concerns often come later, usually when a scanner reports an issue or something goes wrong in production. But by then, the attack surface has already grown, and it becomes much harder to sort out.
What Attack Surface Management Means for Developers
Attack surface management (ASM) is about understanding how your code and architecture can be interacted with, intentionally or otherwise.
An attack surface includes all internet-connected assets, such as web applications, APIs, and cloud environments.
The attack surface grows when teams:
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Add new routes, endpoints, or controllers.
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Introduce APIs for mobile apps or partners.
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Connect services together.
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Trust identity tokens, roles, or network boundaries.
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Expose configuration or metadata endpoints.
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Use third-party services or open-source components.
Rather than focusing solely on individual vulnerabilities, attack surface management looks at what an attacker can reach or exploit based on how the system is designed and deployed.
To sum up, it’s important to consider your organization’s entire attack surface, including digital assets and security vulnerabilities, as well as internet-facing, third-party, supply chain, and cloud-connected assets.
Why the Attack Surface Keeps Growing
The reason that the attack surface continues to increase is that applications are:
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Highly distributed: Includes microservices, cloud resources, and managed services.
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Constantly changing: Frequent releases, infrastructure-as-code, and the addition of new assets.
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Integration-heavy: Connects with APIs, SaaS platforms, and event-driven systems.
Gartner suggests that 90% of organizations will use a hybrid cloud approach through 2027, and each of these cloud environments adds new entry points, leading to potential exposure.
When a single feature is deployed, it can also introduce new data flows and permission sets. On their own, these changes seem harmless, but together they define the attack surface.
Attack surface management helps developers see the system as attackers do, a map of potential entry points.
Internal vs. External Attack Surface
Developers often focus on what’s exposed to the internet, but that’s only part of the picture, because an organization’s attack surface includes internal and external attack surfaces.
Essentially, an attack surface is made up of both internal assets and external attack assets. For attack surface management to be successful, all the organization’s assets need to be monitored for vulnerabilities.
External Attack Surface
This includes anything reachable from outside:
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Public APIs
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Mobile backend endpoints
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Authentication flows
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Cloud services
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Webhooks and callbacks
These are the obvious entry points and often the first place attackers look.
Internal Attack Surface
Internal attack surfaces are created through:
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Service-to-service communication
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Internal APIs
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Message queues and event streams
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Overly permissive roles and identities
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On-premises infrastructure
If an attacker gains access to one component, the internal attack surface determines the damage they can cause and the resources they can access.
For developers, it’s about how services authenticate with each other, and if there are strong permission checks in place, as well as how data is validated as it moves between services.
Asset Discovery and Classification
When it comes to attack surface management, one of the hardest parts is knowing what’s running.
Over time, systems collect assets that aren’t always seen from the codebase alone. For example, services get deployed, environments are created for testing, and integrations are added to meet short-term needs. Some of these assets are well-documented and actively maintained, so their purpose and use are clear.
Other assets, such as unknown or forgotten assets, can slowly fade from view and may be overlooked, increasing the potential attack surface. Third-party assets, managed by external vendors or partners, should also be identified and inventoried as part of the asset discovery process.
Asset Discovery
Asset discovery is about maintaining visibility into those moving parts as the system changes. For developers, this means having a good view of:
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The services and APIs that currently exist.
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The environments that are reachable.
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Integrations that are active.
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Components that are still in use versus those that are effectively abandoned.
Asset Classification
When assets are visible, classification adds the missing context that developers need to understand how each asset is used, who can access it, and how it contributes to overall risk. Classification helps answer:
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Is it meant to be public or internal?
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If it processes sensitive data.
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What other components depend on it?
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How much trust is placed on it by default?
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Which exposed assets could show vulnerabilities if not properly managed?
This context is important because not all assets carry the same risk. For instance, an internal service that’s hardly used and has limited access will be different from a public-facing API relied on by multiple systems.
For developers, asset discovery and classification reduce hidden risks in the system and make it easier to track how new features, integrations, and services change over time. This way, the attack surface doesn’t grow unnoticed.
Understanding Attack Vectors
When we talk about attack vectors, we mean the specific paths or methods that threat actors use to exploit vulnerabilities and gain access to systems and data.
Examples of attack vectors include phishing emails, malware, unsecured network ports, weak passwords, and misconfigured cloud services.
During development, it’s a good idea to keep attack vectors in mind, as secure design features and code help limit exposure. Validating inputs, enforcing proper authentication, and securing network-facing endpoints all reduce the ways an attacker could gain entry.
Attack Surface Management vs. Vulnerability Fixing
It’s easy to assume attack surface management is just vulnerability management under a different name, but it’s not.
Vulnerability management deals with finding and fixing known flaws and weaknesses in software components, such as CVEs and misconfigurations.
Attack surface management is more about understanding and reducing what’s exposed and accessible to potential attackers, regardless of whether there are known vulnerabilities.
It includes having good knowledge of the architecture, entry points, trust boundaries, and attack paths.
More than 40,000 security vulnerabilities were published in 2025 alone, and you could fix all of them, but still be exposed if:
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Sensitive endpoints are unnecessarily public.
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Authentication flows are weakly enforced.
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Trust boundaries are unclear.
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Privileges are broader than needed.
Where Developers Directly Control the Attack Surface
This is where attack surface management becomes very practical for developers.
The attack surface changes when you:
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Decide which endpoints are public vs. internal.
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Design authentication and authorization logic.
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Choose how services communicate.
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Define data flows and validation rules.
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Configure default permissions and implement security controls to reduce vulnerabilities.
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Handle errors and responses.
Attack surface reduction is a proactive strategy developers can use to lower the risk of cyberattacks. They can help reduce an organization’s attack surface by lessening possible entry points and continuously monitoring for vulnerabilities.
These controls are defined in the code, environment settings, and infrastructure, not by external security tools.
The Role of Threat Modeling in Developer-First ASM
Threat modeling is one of the best ways for developers to understand and manage the attack surface, especially when it’s done early, when design decisions are still flexible.
Rather than starting with vulnerabilities or tools, threat modeling starts with how the system is built, for example, its components, how data moves between them, trust boundaries, and entry points.
Threat modeling helps developers think like attackers and identify potential vulnerabilities in the system that could be exploited.
Risk Analysis
The next step in the attack surface management process is to analyze assets for security risks. The security posture of each asset needs to be assessed, and also identifying vulnerabilities that could be exploited.
Risk-based prioritization is then used to figure out which vulnerabilities need to be worked on first, based on their severity and the likelihood of exploitation.
Threat Modeling Benefits
Here’s what makes threat modeling a good fit for developer-first attack surface management:
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See the bigger picture: A single endpoint or permission may seem low risk, but when combined with other components, it can create a potential attack path.
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Shift security left: Threat modeling brings security into the design phase, so developers can think about what could go wrong before code is deployed.
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Keep it current: When threat models are kept up to date and treated as living documents, they become a shared reference for developers, architects, and security teams.
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Make decisions easier: A shared, up-to-date threat model makes it easier to prioritize risk and plan mitigation, as well as manage the attack surface as systems change.
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Act proactively: Understand attack paths and exposures so teams can make informed design and configuration choices, not just react to problems.
Most teams have some version of an architecture diagram or threat model, but they’re usually outdated within weeks. Effective attack surface management needs models that update along with the codebase.
Attack Surface Management Across the SDLC
Attack surface management aligns with the different stages of the software development lifecycle (SDLC):
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Design: Think about exposure before any code is written.
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Development: Apply secure coding best practices and safe configurations that keep the attack surface small as features grow
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CI/CD: Automatically detect architectural risks in the pipeline.
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Production: Monitor the attack surface as systems and threats change.
How SecureFlag Supports Attack Surface Management
For developers who want to understand attack surface management principles better, SecureFlag is the answer, with its hands-on learning and threat modeling.
ThreatCanvas, our automated threat modeling solution, enables developers and security teams to model systems in seconds using components, data flows, trust boundaries, and integrations.
As systems change, threat models can be updated automatically, helping teams keep attack surface views aligned with the current architecture.
ThreatCanvas helps developers:
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See what’s exposed: Understand which entry points and trust relationships exist in your system.
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Identify high-risk paths: Find attack paths before they become threats.
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Prioritize risk: Focus on the areas that are most critical, not every small issue.
What’s more, SecureFlag’s practical labs teach developers secure coding in realistic virtualized environments. Developers can then see firsthand how coding choices, like improper input validation or weak authentication, can create exploitable vulnerabilities.
Together with threat modeling, organizations can make attack surface management a developer-friendly practice that aligns with today’s development workflows.
