Architectural Invariant Design: eBPF TC Ingress/Egress Pod-Identity Cryptographic Tagging and In-Kernel Microsegmentation
eBPF TC Ingress/Egress Pod-Identity Cryptographic Tagging and In-Kernel Microsegmentation defines an industrial-grade behavioral standard for security engineering. Mandates verified kernel-level tenant identity injection and boundary validation at the Traffic Control (TC) layer via eBPF. Forbids unauthenticated IP-to-identity mappings and missing verifier bounds checks on custom encapsulation headers, ensuring line-rate lateral movement isolation without userspace proxy latency. 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 | Trusting Plaintext L3/L4 Metadata Without Cryptographic Authentication and Missing Packet Boundary Validation in TC Filters | 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:
Engineers MUST ALWAYS validate packet buffer boundaries (`data + sizeof(struct) > data_end`) immediately before dereferencing any network or custom identity header.
Engineers MUST ALWAYS validate packet buffer boundaries (`data + sizeof(struct) > data_end`) immediately before dereferencing any network or custom identity header.
Engineers MUST NOT trust raw IPv4/IPv6 source addresses for tenant authorization
Engineers MUST NOT trust raw IPv4/IPv6 source addresses for tenant authorization; identity must be derived from cryptographically verified encapsulation tokens, security context labels in Geneve/VXLAN TLVs, or IPsec/WireGuard SPI bindings.
Code MUST return `TC_ACT_SHOT` on authentication failure, malformed identity options, or unexpected identity spoofing attempts.
Code MUST return `TC_ACT_SHOT` on authentication failure, malformed identity options, or unexpected identity spoofing attempts.
Services MUST invoke `bpf_l3_csum_replace` and `bpf_l4_csum_replace` when modifying IP/TCP/UDP headers or prepending custom microsegmentation identity shims to preserve transport layer packet integrity.
Services MUST invoke `bpf_l3_csum_replace` and `bpf_l4_csum_replace` when modifying IP/TCP/UDP headers or prepending custom microsegmentation identity shims to preserve transport layer packet integrity.
Components NEVER fall back to userspace daemons for synchronous per-packet identity verification in hot ingress TC paths.
Components NEVER fall back to userspace daemons for synchronous per-packet identity verification in hot ingress TC paths.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is eBPF TC Ingress/Egress Pod-Identity Cryptographic Tagging and In-Kernel Microsegmentation critical for AI coding assistants?
Mandates verified kernel-level tenant identity injection and boundary validation at the Traffic Control (TC) layer via eBPF. Forbids unauthenticated IP-to-identity mappings and missing verifier bounds checks on custom encapsulation headers, ensuring line-rate lateral movement isolation without userspace proxy latency. 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 (Trusting Plaintext L3/L4 Metadata Without Cryptographic Authentication and Missing Packet Boundary Validation in TC Filters) 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.