Organizations map their attack surface—endpoints, cloud infrastructure, applications—yet breaches keep happening. The problem isn't visibility into assets. Email remains the foundation of business communications and one of the primary entry points for cyberattacks, yet most attack surface management (ASM) programs treat it as infrastructure rather than the dominant attack vector. Over 90% of successful cyberattacks begin with a phishing email. Until security teams treat the inbox as a critical attack surface, gaps will persist.

Attack surface management continuously discovers, analyzes, and secures all potential entry points an attacker could exploit, with email often representing the most overlooked critical surface. Unlike traditional vulnerability management approaches focused on known weaknesses, ASM adopts an attacker's perspective across the entire organizational footprint.

ASM extends beyond vulnerability scanning to include unknown assets: unauthorized shadow IT systems, abandoned infrastructure, and third-party connections security teams may not know exist. Attackers don't constrain themselves to documented inventories and this path increasingly leads through email-based social engineering and business email compromise (BEC).

Security teams must account for three distinct attack surface categories, yet most programs focus heavily on digital and physical assets while underweighting the social engineering surface where attackers increasingly succeed.

The digital attack surface includes all internet-facing assets that attackers can enumerate through reconnaissance techniques:

• Public-facing IP addresses and domains

• Web applications and APIs that provide entry points when misconfigured

• Cloud storage buckets with overly permissive access controls

• Third-party software integrations that create potential lateral movement paths

These assets require continuous monitoring because configurations change frequently and new exposures emerge as organizations deploy additional services.

The physical attack surface encompasses tangible devices and infrastructure that attackers can exploit through direct access. Key components include desktop and mobile endpoints with corporate access, IoT devices connected to networks often running outdated firmware, data centers and network equipment requiring physical security controls, and removable media that can introduce malware through USB-based attacks.

Physical security controls complement technical safeguards by preventing unauthorized access to infrastructure that could enable broader compromise. Organizations often underestimate physical security's role in comprehensive attack surface management, particularly as hybrid work expands the physical perimeter beyond traditional office boundaries.

The social engineering attack surface represents vulnerabilities stemming from human behavior and trust exploitation. Phishing attack techniques, BEC, and email impersonation attack methods all target human judgment rather than technical weaknesses. The FBI's 2024 IC3 report shows BEC resulted in $2.77 billion in losses across more than 21,000 incidents in 2024 alone.

Email serves as a primary delivery mechanism for social engineering, providing attackers with direct access to employees across the organization—making it among the most externally accessible and frequently exploited components of the human attack surface.

Unlike digital and physical assets that security teams can scan and inventory, the human attack surface requires fundamentally different detection approaches. Communication patterns, trust relationships, and organizational hierarchies represent distinct human-targeted attack vectors when attackers exploit them through social engineering.

Different ASM approaches address different visibility requirements, yet all three established categories share a critical blind spot around human-targeted threats.

External attack surface management (EASM) provides an outside-in view of internet-facing assets, simulating the perspective an attacker would have when conducting reconnaissance. EASM solutions continuously scan and enumerate publicly accessible resources:

• Domains and IP addresses

• Cloud services and exposed APIs

• Unauthorized SaaS applications

• Abandoned infrastructure like decommissioned servers still connected to networks

This approach helps organizations discover misconfigured assets that security teams may not realize are publicly visible. However, EASM's external scanning methodology creates limitations for internal network assets.

Internal attack surface management (IASM) addresses risks within an organization's private network, focusing on devices and systems behind firewalls that attackers could exploit if they gain initial access. IASM coverage includes internal servers and databases, network segmentation configurations, employee workstations and privileged access systems, and identity infrastructure.

IASM is the only category among the three that explicitly acknowledges human assets vulnerable to social engineering, positioning it conceptually closer to comprehensive attack surface coverage.

Cyber asset attack surface management (CAASM) aggregates asset data from existing security tools through API integrations to create a unified inventory spanning both internal and external environments. Rather than performing active discovery scans, CAASM normalizes and deduplicates data from configuration databases, endpoint agents and cloud platforms, and identity management systems.

This integration eliminates data silos and provides security teams with a single source of truth for asset inventory. However, CAASM's effectiveness depends entirely on the capabilities of integrated source tools.

Effective ASM operates as a continuous cycle with four core phases that security teams must execute systematically to maintain comprehensive visibility.

Automated scanning identifies known, unknown, and shadow IT assets across the organizational footprint. Discovery processes enumerate both sanctioned infrastructure and unauthorized systems deployed outside IT governance. Per CISA guidance, an asset inventory is foundational to designing a modern defensible architecture because organizations cannot secure what they don't know exists.

Security teams must categorize assets by criticality and business value to focus remediation efforts appropriately. Classification considers data sensitivity, regulatory requirements, business function dependencies, and exposure level. Prioritization frameworks weight these factors to rank assets by risk.

Teams address identified vulnerabilities through patching, configuration changes, or decommissioning unnecessary systems. Effective remediation requires clear ownership assignments and integration with change management processes.

Ongoing scanning detects changes and emerging threats in real time. Environments evolve constantly as new assets deploy and configurations change. Integration with threat intelligence feeds enhances monitoring by correlating discovered assets against known attack patterns.

Traditional ASM tools can discover email infrastructure but struggle to assess whether employees will recognize social engineering attempts, creating a critical gap where most breaches originate. Email presents a unique risk because it is externally accessible and directly reaches employees.

Signature-based email security tools often struggle to detect BEC attacks because these attacks exploit legitimate infrastructure and human trust rather than malicious payloads. Endpoint Protection Platforms and EDR solutions face similar challenges.

Socially-engineered attacks succeed because they contain nothing technically malicious. BEC and vendor impersonation emails include only legitimate-looking text requesting financial transfers or sensitive information—no malware, no malicious URLs, and they originate from accounts that pass authentication checks.

Comprehensive attack surface coverage requires organizations to monitor human communication patterns with the same rigor applied to infrastructure assets. Abnormal's behavioral AI platform extends traditional asset discovery to include behavioral baselines, identity monitoring, and communication pattern analysis.

Abnormal applies behavioral AI to the email attack surface, detecting threats through identity awareness, context analysis, and risk signals that traditional ASM may not see. This approach gives Abnormal a complete understanding of how people normally communicate—so it can identify what doesn’t belong across three core dimensions:

• Identity Awareness: Builds detailed profiles of employees, vendors, and applications from directories, sign-in patterns, and communication histories

• Context Awareness: Maps relationships among identities and analyzing the tone, cadence, and frequency of their interactions

• Risk Awareness: Applies natural language models and content analysis to identify suspicious requests or anomalous content patterns

Unlike traditional ASM tools requiring weeks of deployment, Abnormal's API-native architecture integrates directly with Microsoft 365 and Google Workspace in minutes, continuously adapting as behaviors evolve without disrupting mail flow.

Abnormal's VendorBase™ provides federated intelligence across thousands of customers to baseline normal vendor communication patterns and identify supply chain compromise attempts.

These systems understand normal request types, approval workflows, and financial processes, enabling detection of deviations indicating compromise. As human-targeted attacks continue to dominate breach statistics, Abnormal's behavioral AI solutions have become necessary for comprehensive protection.

Attack surface management programs that ignore email and human-targeted threats leave the primary breach vector unprotected. Extending ASM to include behavioral detection addresses the gap where most attacks succeed.

Request a demo to see how behavioral AI detects email threats, including BEC, vendor impersonation, and executive fraud, that infrastructure-focused ASM programs and signature-based email security miss.

• Email is among the most exploited attack vectors: With over 90% of successful cyberattacks beginning with a phishing email, organizations must treat the inbox as a critical attack surface rather than an infrastructure afterthought.

• Traditional ASM creates dangerous blind spots: External, internal, and cyber asset attack surface management solutions focus on technical assets while overlooking the human-targeted threats where attackers increasingly succeed.

• Signature-based security often fails against BEC: Business email compromise attacks contain no malware or malicious URLs—they exploit human trust and legitimate infrastructure, bypassing many traditional detection methods.

• The human attack surface demands behavioral analysis: Communication patterns, trust relationships, and organizational hierarchies represent distinct attack vectors requiring fundamentally different detection approaches than asset scanning.

• Comprehensive protection requires behavioral AI: Closing the gap between infrastructure-focused ASM and email security demands AI that establishes behavioral baselines and detects anomalies in real time.