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Insecure design refers to risks related to flaws in the design and architecture of an application, as distinguished from implementation bugs. This includes missing or ineffective threat modeling, insecure design patterns, and insufficient security controls at the design level.
CodeAnt AI detects Insecure Design vulnerabilities across 14 languages: Python, Java, JavaScript, TypeScript, Go, C#, C, Ruby, Scala, Swift, Terraform, Dockerfile, YAML, Apex.

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Detected Vulnerabilities

Severity: Medium

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Description

The application generates error messages that include sensitive information such as stack traces, database queries, file paths, or system configuration details.

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Impact

Attackers gain reconnaissance information about the application’s internals, technology stack, and potential vulnerabilities that can be used to craft more targeted attacks.

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Remediation

Use generic error messages for end users. Log detailed errors server-side only. Implement custom error handlers. Disable debug mode in production. Never expose stack traces or internal paths to clients.
Severity: Critical

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Description

The application stores passwords in plaintext without any form of hashing or encryption, making them immediately usable if the storage medium is compromised.

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Impact

If the database or file system is breached, all user passwords are immediately exposed and can be used for account takeover across multiple services.

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Remediation

Always hash passwords using adaptive algorithms like bcrypt, scrypt, or Argon2id with proper salt. Never store passwords in plaintext, reversible encryption, or weak hashes like MD5/SHA1.
Severity: High

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Description

The application mixes trusted and untrusted data within the same data structure or storage location, making it difficult to distinguish between validated and unvalidated data.

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Impact

Untrusted data may be treated as trusted, leading to security bypasses, privilege escalation, or injection attacks that circumvent validation logic.

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Remediation

Clearly separate trusted and untrusted data. Validate all data at trust boundaries. Use separate data structures for user input and internal state. Apply defense-in-depth with validation at multiple layers.
Severity: High

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Description

The application does not implement sufficient anti-automation controls to prevent brute-force attacks against authentication endpoints.

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Impact

Attackers can systematically try large numbers of credentials to guess valid usernames and passwords, especially when combined with leaked credential databases.

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Remediation

Implement account lockout after a fixed number of failed attempts. Use progressive delays (exponential backoff). Deploy CAPTCHA after repeated failures. Monitor and alert on brute-force patterns.
Severity: High

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Description

The application relies on client-side validation or checks for security decisions that should be enforced on the server, making them easily bypassable.

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Impact

Attackers can bypass all client-side security controls using browser developer tools, proxy tools, or direct API calls, negating any protection they were intended to provide.

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Remediation

Always enforce security controls server-side. Treat client-side validation as a UX convenience only. Validate all inputs, permissions, and business rules on the server.
Severity: High

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Description

The application contains flaws in its business logic that allow users to manipulate processes in unintended ways, bypassing expected workflows or constraints.

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Impact

Attackers can exploit business logic flaws to gain unauthorized benefits, bypass payment processes, manipulate pricing, or circumvent intended application workflows.

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Remediation

Implement thorough threat modeling during design. Validate business rules at every step. Use state machines for multi-step processes. Test edge cases and negative scenarios extensively.