Architectural Invariant Design: Server-Side Request Forgery (SSRF) & DNS Rebinding Mitigation Standard
Server-Side Request Forgery (SSRF) & DNS Rebinding Mitigation Standard defines an industrial-grade behavioral standard for security engineering. Production network security standard (CWE-918 / OWASP A10:2021). Mandates strict validation of user-supplied URLs before outbound HTTP requests, resolves DNS to target IP, rejects private/internal RFC 1918 ranges (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16, 127.0.0.1, 169.254.169.254), and prevents DNS Rebinding attacks by pinning resolved IPs. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.
Hazard Analysis: What Breaks Without This Rule
The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:
| Failure Mode | AI Symptom (The Anti-Pattern) | Severity | Production Impact & Remedy |
|---|---|---|---|
| AI Hallucination & Deprecation Drift | AI fetches user-provided URLs with fetch(req.body.url) without IP resolution or private range filtering, allowing attackers to access internal cloud metadata and databases. | Critical | Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production. Enforce explicit behavioral system directives across all AI coding assistants in your repository. |
| Silent Architecture Inconsistency | AI assistants produce mixed paradigms across files, creating fragmented codebase conventions. | Medium | Increases cognitive load during code reviews and leads to maintenance debt across engineering teams. Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails. |
Step-by-Step Production Directives
Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:
MUST resolve DNS hostnames before issuing outbound HTTP requests using dns.promises.lookup().
MUST resolve DNS hostnames before issuing outbound HTTP requests using dns.promises.lookup().
MUST reject requests targeting loopback (127.0.0.0/8,
MUST reject requests targeting loopback (127.0.0.0/8, ::1), private networks (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16), and cloud metadata (169.254.169.254).
MUST connect directly to the resolved IP address to eliminate DNS Rebinding (Time-of-Check to Time-of-Use) attacks.
MUST connect directly to the resolved IP address to eliminate DNS Rebinding (Time-of-Check to Time-of-Use) attacks.
MUST restrict allowed protocols strictly to ['http
MUST restrict allowed protocols strictly to ['http:', 'https:'] (reject file://, gopher://, dict://).
MUST disable automatic redirect following (redirect
MUST disable automatic redirect following (redirect: 'manual') or re-validate redirect target URLs against the same IP filter.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is Server-Side Request Forgery (SSRF) & DNS Rebinding Mitigation Standard critical for AI coding assistants?
Production network security standard (CWE-918 / OWASP A10:2021). Mandates strict validation of user-supplied URLs before outbound HTTP requests, resolves DNS to target IP, rejects private/internal RFC 1918 ranges (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16, 127.0.0.1, 169.254.169.254), and prevents DNS Rebinding attacks by pinning resolved IPs. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.
Q:How does adopting this rule prevent AI hallucinations?
This rule explicitly declares what the AI must avoid (AI fetches user-provided URLs with fetch(req.body.url) without IP resolution or private range filtering, allowing attackers to access internal cloud metadata and databases.) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.
Q:Which AI coding environments are supported?
This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).
Q:Can I combine this rule with other technology stacks?
Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.