CWE Landscape, Patterns, Correlations

Introduction

Security vulnerabilities are rarely isolated incidents. In real-world systems, weaknesses tend to cluster, cascade, and compound, often stemming from the same underlying design or validation failures.

As part of our research to build models that can detect and remediate vulnerabilities automatically, we analyzed the Top 25 CWEs, their scope, parent–child relationships, and correlations across languages and technologies.

This blog breaks down what the data tells us about:

  • Which weaknesses dominate modern software
  • How CWEs are structurally related
  • Why fixing root causes matters more than chasing individual bugs

CWE Distribution: A Small Set Causes Most Damage

The Top 25 CWE list shows published by MITRE shows a clear concentration of risk:

Most Frequent CWEs

  • CWE-787 – Out-of-Bounds Write
  • CWE-79 – Cross-Site Scripting (XSS)
  • CWE-89 – SQL Injection
  • CWE-416 – Use After Free
  • CWE-78 – OS Command Injection

These vulnerabilities directly impact Integrity, Confidentiality, and Availability, making them both high-impact and high-exploitability.

What’s notable is that these are not new problems, they are recurring failures in memory handling, input validation, and access control.

Scope Analysis: What Security Properties Are Most at Risk?

When mapping CWEs to security scope, the ranking is telling as shown in the figure above. We map security scope vs the number of vulnerable occurrences that we observed.

Integrity and Confidentiality dominate, meaning most vulnerabilities allow:

  • Unauthorized data modification
  • Data leakage or exposure
  • Privilege escalation chains

This reinforces that data safety and trust boundaries remain the weakest points in modern applications.


CWE Fanout: Why Parent CWEs Matter More Than Individual Bugs

Some CWEs act as root causes for many others. Fanout analysis highlights this clearly:

Example: Memory Safety Cascade

  • CWE-119 (Improper Restriction of Operations within the Bounds of a Memory Buffer) leads to:
    CWE-787 (Write),
    – CWE-125 (Read)
    CWE-416 (Use After Free)

Fixing CWE-119-style issues eliminates entire classes of vulnerabilities, not just individual findings.

Correlated Weaknesses: Injection Is a Family, Not a Single Bug

Injection vulnerabilities show some of the strongest correlations:

  • CWE-74 (Improper Neutralization)
    – CWE-79 (XSS)
    – CWE-89 (SQL Injection)
    – CWE-78 (Command Injection)
    – CWE-94 (Code Injection)

Despite different exploit surfaces, they all stem from the same fundamental failure:

Trusting unvalidated or improperly sanitized input

This insight is critical for automated remediation, fixes must be context-aware, not pattern-based.


Mapping CWE Findings to the OWASP Top 10

Our CWE analysis strongly aligns with the OWASP Top 10, validating that these weaknesses translate directly into real-world web application risk.

Note on OWASP Mapping: OWASP Top 10 categories are risk groupings, not technical vulnerabilities.While MITRE prohibits using OWASP identifiers to label real-world vulnerabilities, CWE-to-OWASP mappings are widely used for analysis, prioritization, and education. In this work, OWASP Top 10 is used strictly as a risk abstraction layer, grounded in underlying CWE patterns.

OWASP A01: Broken Access Control

  • CWE-284, CWE-862, CWE-863, CWE-269, CWE-306
    Access control weaknesses show the highest fanout, enabling privilege escalation, data exposure, and unauthorized actions.

OWASP A02: Cryptographic Failures

  • CWE-798 (Hard-coded Credentials)
  • CWE-276 (Incorrect Default Permissions)
    Mismanagement of secrets and permissions continues to undermine otherwise secure systems.

OWASP A03: Injection

  • CWE-89 (SQL Injection)
  • CWE-79 (XSS)
  • CWE-78 (OS Command Injection)
  • CWE-94 (Code Injection)
    Injection flaws remain among the most prevalent and exploitable weaknesses.

OWASP A04: Insecure Design

  • CWE-710 (Improper Coding Standards)
  • CWE-668 (Exposure of Resource to Wrong Sphere)
    Many vulnerabilities originate from architectural decisions rather than implementation bugs.

OWASP A05: Security Misconfiguration

  • CWE-276 (Incorrect Default Permissions)
  • CWE-434 (Unrestricted File Upload)
  • CWE-732 (Incorrect Permission Assignment)

OWASP A06: Vulnerable and Outdated Components

  • CWE-502 (Deserialization of Untrusted Data)
    Often exploited through insecure libraries and dependencies.

OWASP A07: Identification and Authentication Failures

  • CWE-287 (Improper Authentication)
  • CWE-306 (Missing Authentication)
  • CWE-862 (Missing Authorization)

OWASP A08: Software and Data Integrity Failures

  • CWE-345 (Insufficient Verification)
  • CWE-494 (Download of Code Without Integrity Check)

OWASP A09: Security Logging and Monitoring Failures

  • CWE-778 (Insufficient Logging) (indirectly implied through exploit chains)

OWASP A10: Server-Side Request Forgery (SSRF)

  • CWE-918 A modern, cloud-amplified vulnerability with growing impact.

Conclusion

  1. Most vulnerabilities share common root causes
  2. Parent CWEs explain exploit clusters
  3. Input handling and access control failures dominate
  4. Security scope skews heavily toward Integrity and Confidentiality
  5. Effective remediation requires structural understanding, not rule matching
  6. CWE analysis strongly validates the OWASP Top 10

This research forms the foundation for how we, at Pervaziv AI designed our vulnerability dataset and model training strategy. Instead of treating vulnerabilities as isolated labels, we focus on:

  • Root causes
  • Correlated weaknesses
  • Real-world exploit patterns

References 

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