# Ruchy Aerospace-Grade Security Specification

## Executive Summary

Ruchy achieves defense-in-depth security through compile-time verification, runtime sandboxing, and cryptographic proof of correctness. By transpiling to Rust, we inherit memory safety while adding formal verification layers impossible in traditional scripting languages.

## Response to Architectural Review

### Addressing Implementation Complexity
The reviewer correctly identifies the scope as monumental. Our mitigation strategy:
- **Phased Delivery**: Ship capability system (Q1), add SMT verification (Q3), defer FHE to v2.0
- **Library Integration**: Leverage existing tools (Z3, TFHE-rs) rather than reimplementing
- **Optional Features**: Core language ships without advanced crypto; teams opt-in as needed
- **Community Expertise**: Partner with formal methods researchers for verification components

### Performance Reality Check
The 100-1000x FHE overhead is accurate but misleading—it's for specialized regulatory compliance, not general computation. Real performance profile:
- **Capabilities**: Zero runtime cost (compile-time analysis only)
- **Taint Tracking**: Zero cost via phantom types (erased at compilation)
- **SMT Verification**: Compile-time only, with 100ms timeout and graceful degradation
- **Code Signing**: One-time 10ms verification at module load
- **FHE/ZK**: Opt-in for specific functions, not system-wide

### Verifier Correctness Strategy
The "quis custodiet" problem is real. Our approach:
- **Differential Testing**: Run multiple SMT solvers, compare results
- **Proof Certificates**: Generate machine-checkable proofs for external validation
- **Gradual Trust**: Start with runtime assertions, progressively move to static proofs
- **Open Verification**: All security components open-source for community audit

## Implementation Roadmap

### Phase 1: Core Security (Q1 2025)
1. **Capability System** - 4 weeks
   - Leverage Deno's existing implementation patterns
   - Generate seccomp-bpf filters at compile time
   - Zero runtime overhead via static analysis

2. **Taint Tracking** - 3 weeks
   - Phantom type implementation (zero-cost)
   - Integrate with OWASP patterns
   - Automatic sanitizer insertion

3. **Code Signing** - 1 week
   - Ed25519 via ring crate
   - Merkle tree for incremental verification
   - Git integration for provenance

### Phase 2: Verification (Q2 2025)
4. **SMT Integration** - 6 weeks
   - Z3 via rust-z3 bindings
   - Bounded verification (100ms timeout)
   - Counterexample generation

5. **Mathematical Diff** - 2 weeks
   - AST structural comparison
   - Security impact scoring
   - CVSS-like metrics

### Phase 3: Advanced Crypto (Q3 2025)
6. **ZK Proofs** - 8 weeks (partner with external team)
   - Circom integration for circuits
   - Groth16 proving system
   - Developer-friendly abstractions

7. **Supply Chain** - 2 weeks
   - SPDX/CycloneDX generation
   - OSV vulnerability scanning
   - Reproducible build system

### Deferred to v2.0
- Fully Homomorphic Encryption (research partnership required)
- Time-travelling debugger (complex but non-critical)
- Chaos engineering (better as external tool)

## 1. Capability-Based Security System (Deno++Enhanced)

### Architecture
```rust
// Compile-time capability tracking
#[capabilities(read="/data/*", write="./output", net="api.internal:443")]
fun process_secure_data(input: SecureFile) -> Result<Output> {
    // Compiler proves no capability escape
    let data = input.read()?;  // Static verification of read permission
    fetch("https://api.internal/process")?  // Compile-time URL validation
}

// Runtime enforcement via Linux seccomp-bpf
struct SecurityContext {
    capabilities: CapabilitySet,
    seccomp_filter: BpfProgram,  // Generated from capabilities
    landlock_rules: LandlockRuleset,  // Filesystem sandboxing
}
```

### Implementation
- **Compile-time**: AST annotation with capability requirements
- **Transpilation**: Generate Rust code with embedded seccomp filters
- **Runtime**: Automatic sandbox activation before main()
- **Innovation**: Capabilities flow through type system, preventing ambient authority

## 2. Cryptographic Code Provenance Chain

### Design
```rust
// Every function carries its provenance
#[signed(author="alice@example.com", key="ED25519:abc...")]
#[reviewed(by="bob@example.com", at="2024-01-15", hash="sha3:def...")]
fun critical_operation() {
    // Compiler embeds signature in binary
}

// Automatic verification at import
import signed_module from "./critical.ruchy"  // Fails if signature invalid

// Git-like blame but cryptographic
$ ruchy blame --crypto main.ruchy
Line 42: alice@example.com (verified) 2024-01-10 SHA3:abc123...
Line 43: bob@example.com (verified) 2024-01-12 SHA3:def456...
```

### Features
- Ed25519 signatures embedded in AST nodes
- Merkle tree of function dependencies
- Reproducible builds with signed manifests
- Integration with corporate PKI systems

## 3. Mathematical Code Diff Engine

### Core Algorithm
```rust
// AST-based semantic diff
$ ruchy mdiff v1.ruchy v2.ruchy

SEMANTIC CHANGES:
✓ Function 'process': Added bounds check (SAFER)
⚠ Function 'validate': Relaxed input constraint from i32 > 0 to i32 >= 0
✗ Function 'auth': Removed authentication check (CRITICAL)

DEPENDENCY CHANGES:
+ tokio v1.35 (async runtime)
- openssl v0.10 (REMOVED: reduces attack surface)

SECURITY IMPACT:
- Attack surface: -15% (removed OpenSSL)
- Cyclomatic complexity: +2 (slightly more complex)
- Information flow: No new data exfiltration paths
```

### Analysis Dimensions
- **AST Structural Diff**: Beyond text, understand semantic changes
- **Type Flow Analysis**: Track how type changes affect safety
- **Dependency Graph**: Visualize transitive dependency changes
- **Security Metrics**: CVSS-like scoring for code changes

## 4. Information Flow Control System

### Taint Tracking
```rust
#[tainted(source="user_input")]
fun process_request(data: String) -> Response {
    let clean = sanitize(data);  // Compiler tracks taint removal
    
    // Compile error: Cannot write tainted data to disk
    // fs::write("log.txt", data)?;  // ❌ Blocked at compile time
    
    fs::write("log.txt", clean)?;  // ✓ Sanitized data allowed
}

// Lattice-based security levels
type Secret<T> = T;  // High security
type Public<T> = T;  // Low security

// Compiler prevents information leakage
fun leak(s: Secret<String>) -> Public<String> {
    s  // Compile error: Cannot downgrade Secret to Public
}
```

### Implementation
- Static taint analysis via abstract interpretation
- Dynamic taint tracking for runtime values
- Automatic sanitizer insertion at security boundaries
- Integration with OWASP security patterns

## 5. Formal Verification via SMT Integration

### Specification
```rust
#[verify(z3)]
#[invariant("balance >= 0")]
#[invariant("sum(accounts) == total_supply")]
contract TokenContract {
    balance: Map<Address, u64>,
    total_supply: u64,
    
    #[ensures("balance[to] == old(balance[to]) + amount")]
    #[ensures("balance[from] == old(balance[from]) - amount")]
    fun transfer(from: Address, to: Address, amount: u64) {
        require(balance[from] >= amount);
        balance[from] -= amount;
        balance[to] += amount;
    }
}

// Compiler output:
// ✓ Invariant 'balance >= 0' verified
// ✓ Transfer preserves total_supply
// ✓ No integer overflow possible
// Proof certificate: QED-2024-abc123.smt2
```

### Verification Stack
- **SMT Backend**: Z3/CVC5 for constraint solving
- **Proof Certificates**: Machine-checkable correctness proofs
- **Gradual Verification**: Start dynamic, progressively add proofs
- **Counterexample Generation**: Show exact inputs that break invariants

## 6. Zero-Knowledge Execution Proofs

### Architecture
```rust
#[zk_provable]
fun compute_private(secret: Secret<Data>) -> Proof<Result> {
    // Function executes in ZK-SNARK circuit
    let result = complex_computation(secret);
    
    // Generate proof without revealing secret
    zk::prove(result)
}

// Verifier can check result without seeing input
fun verify_computation(proof: Proof<Result>) -> bool {
    zk::verify(proof, public_parameters)
}
```

### Applications
- Regulatory compliance without data exposure
- Multi-party computation protocols
- Blockchain smart contract verification
- Privacy-preserving analytics

## 7. Supply Chain Integrity System

### SBOM Generation
```rust
// Auto-generated at build time
$ ruchy sbom generate --format=spdx

{
  "spdxVersion": "SPDX-2.3",
  "packages": [
    {
      "name": "ruchy-stdlib",
      "version": "1.0.0",
      "verificationCode": "sha3-256:abc...",
      "licenseConcluded": "MIT",
      "vulnerabilities": []
    }
  ],
  "relationships": [
    {
      "type": "DEPENDS_ON",
      "element": "main.ruchy",
      "relatedElement": "ruchy-stdlib"
    }
  ]
}
```

### Features
- Automatic SBOM generation in SPDX/CycloneDX format
- Vulnerability scanning via OSV database
- License compliance checking
- Reproducible build attestations

## 8. Time-Travelling Debugger with Audit Trail

### Recording System
```rust
#[record_execution]
fun process_transaction(tx: Transaction) {
    // Every state change recorded with:
    // - Timestamp (NTP synchronized)
    // - Call stack hash
    // - Input hash
    // - Output hash
}

// Replay any execution
$ ruchy replay --transaction-id=abc123 --time="2024-01-15T10:30:00Z"
> Replaying execution...
> Step 1: validate_input(tx) -> Ok
> Step 2: check_balance(account) -> 1000
> Step 3: deduct_fee(amount) -> 950
```

### Audit Features
- Cryptographic hash chain of all executions
- Tamper-evident logs (append-only)
- Integration with SIEM systems
- Compliance with SOC2/ISO27001 requirements

## 9. Homomorphic Encryption Support

### Native FHE Operations
```rust
use ruchy::crypto::fhe;

#[homomorphic]
fun compute_on_encrypted(a: Encrypted<i32>, b: Encrypted<i32>) -> Encrypted<i32> {
    // Operations on encrypted data without decryption
    let sum = a + b;  // Homomorphic addition
    let product = a * b;  // Homomorphic multiplication
    
    // Compiler generates FHE circuits
    product + sum
}

// Client never shares private key
let encrypted_result = server.compute_on_encrypted(
    fhe::encrypt(42, public_key),
    fhe::encrypt(10, public_key)
);
let result = fhe::decrypt(encrypted_result, private_key);  // Only client can decrypt
```

### Implementation
- TFHE-rs backend for fully homomorphic encryption
- Automatic circuit optimization
- Noise budget tracking
- GPU acceleration support

## 10. Chaos Engineering & Fault Injection

### Built-in Chaos Testing
```rust
#[chaos_test(probability=0.01)]
fun reliable_service() {
    // Compiler injects failures in test builds
    // - Network timeouts
    // - Memory pressure
    // - CPU throttling
    // - Byzantine failures
}

// Property-based chaos testing
#[property_test]
#[chaos(network_partition, probability=0.1)]
fun test_distributed_consensus() {
    // Verify consensus maintains safety under network partitions
}

// Formal verification of fault tolerance
#[verify_fault_tolerance(max_failures=2)]
actor RaftConsensus {
    // Compiler proves system tolerates 2 failures
}
```

### Chaos Capabilities
- Deterministic fault injection for reproducibility
- Lineage-driven failure analysis
- Automatic failure scenario generation
- Integration with Jepsen for distributed testing

## Pragmatic Security Architecture

### Core Insight
Security features divide into two categories:
1. **Zero-cost abstractions** via type system (capabilities, taint, flow)
2. **Opt-in verification** for critical paths (SMT, ZK, FHE)

The former ships in v1.0, the latter remains modular.

### Addressing Type-Level Complexity
The reviewer correctly identifies taint tracking's compile-time cost. Our mitigation:

```rust
// Type simplification via inference regions
#[taint_region]
fn process_user_data() {
    // Inside region: full taint tracking
    let input: Tainted<String> = get_input();
    let clean = sanitize(input);  // Type: Clean<String>
    
    // Region boundary performs type erasure
    emit(clean)  // External signature: String (taint erased)
}

// Outside region: simple types, no taint propagation
fn caller() {
    let result = process_user_data();  // Type: String, not Clean<String>
}
```

This bounds type complexity to security-critical regions, preventing whole-program type pollution.

### Minimum Viable Security (v1.0)

```rust
// Three primitives that compose
#[capability(fs_read="/app/*")]  // Static permission
#[taint(source="user_input")]     // Type-level tracking  
#[boundary(sanitize="xss")]       // Automatic sanitization

fn handle_request(input: UserData) -> Response {
    // Compiler proves:
    // 1. No filesystem access outside /app
    // 2. User data cannot reach raw SQL
    // 3. XSS sanitization at output boundary
}
```

These compile to phantom types and const assertions—zero runtime cost.

### SMT Solver Determinism Strategy

The timeout non-determinism issue is fundamental. Solution: **proof caching with deterministic replay**.

```rust
// SMT proof cache (content-addressed)
struct ProofCache {
    store: HashMap<Hash, ProofResult>,
}

impl SmtVerifier {
    fn verify(&self, query: Query) -> Result<Proof> {
        let hash = query.structural_hash();
        
        // Deterministic: always returns same result for same query
        if let Some(cached) = self.cache.get(hash) {
            return cached.clone();
        }
        
        // First run: solve with generous timeout
        match self.solve_with_timeout(query, 5000ms) {
            Ok(proof) => {
                self.cache.insert(hash, Ok(proof));
                Ok(proof)
            }
            Timeout => {
                // Cache the timeout as explicit "unverified" state
                self.cache.insert(hash, Unverified);
                warn!("Proof timeout for {query}, add #[trust_me] or simplify");
                Unverified
            }
        }
    }
}
```

Key: timeouts become **reproducible build warnings**, not random failures.

## Performance Impact

| Security Feature | Compile Time | Runtime Overhead | Binary Size |
|-----------------|--------------|------------------|-------------|
| Capabilities | +5ms | 0% (compile-time) | +2KB |
| Code Signing | +10ms | <1% (verification) | +5KB |
| Taint Tracking | +15ms | 0% (types erased) | +0KB |
| SMT Verification | +100ms | 0% (static proof) | +1KB |
| ZK Proofs | +500ms | 10-20% (circuits) | +50KB |
| FHE | +50ms | 100-1000x (encrypted) | +100KB |

### Mathematical Diff Complexity Reduction

The reviewer's concern about AI-complete semantic analysis is valid. Revised approach: **compositional security metrics** rather than holistic understanding.

```rust
// Decompose into measurable, local properties
struct SecurityDelta {
    // Mechanical metrics (deterministic)
    capability_changes: CapabilityDiff,      // +read, -write
    taint_flow_changes: TaintFlowGraph,      // New edges in flow graph
    cyclomatic_delta: i32,                   // McCabe complexity change
    
    // Pattern matching (heuristic but bounded)
    auth_patterns: Vec<PatternChange>,       // Matches against known patterns
    crypto_primitives: Vec<CryptoChange>,    // MD5→SHA256 upgrades
    
    // Dependency analysis (mechanical)
    new_deps: Vec<Crate>,                   // Added dependencies
    removed_deps: Vec<Crate>,               // Removed dependencies
    cve_delta: i32,                        // Change in known CVEs
}

impl SecurityDelta {
    // Don't try to "understand" authentication
    // Just detect structural patterns
    fn detect_auth_changes(&self, ast_diff: &AstDiff) -> Vec<PatternChange> {
        KNOWN_PATTERNS
            .iter()
            .filter_map(|pattern| pattern.match_diff(ast_diff))
            .collect()
    }
}

// Patterns are explicit, reviewable, and extensible
const KNOWN_PATTERNS: &[Pattern] = &[
    Pattern::regex(r"if.*authenticated.*return"),  // Auth guard
    Pattern::ast(IfExpr { cond: Contains("token"), then: Return }),
    Pattern::dataflow(TaintSource("password") → TaintSink("network")),
];
```

This transforms an AI-hard problem into mechanical pattern matching with explicit, auditable rules.

### Partnership Risk Mitigation

External dependencies identified as critical risk. Solution: **interface-first development with reference implementations**.

```rust
// Define stable interfaces that partners implement
trait ZkBackend {
    fn compile_circuit(&self, ast: &ZkAst) -> Circuit;
    fn generate_proof(&self, circuit: &Circuit, witness: &Witness) -> Proof;
    fn verify(&self, proof: &Proof, public: &Public) -> bool;
}

// Ship with basic reference implementation
struct NaiveZkBackend;  // Bulletproofs, unoptimized but functional

// Partners provide optimized implementations
struct CircomBackend;   // From external team
struct Groth16Backend;  // From zkSNARK specialists

// Runtime backend selection
#[zk_provable(backend = "groth16")]  // Optional performance
#[zk_provable]  // Falls back to reference implementation
```

This ensures v1.0 ships with working ZK support, even without partnerships.

### Security Theatre Prevention

Critical issue: developers misusing security primitives. Solution: **compiler-enforced security contracts**.

```rust
// Compiler detects and prevents common misuse patterns
#[zk_provable]
fn broken_zk(secret: i32, public: i32) -> Proof {
    if secret == public {  // Compiler error: Information leak
        //              ^^^ Error: ZK function leaks information about secret
        //                  Help: Secret values must not influence public outputs
        return proof;
    }
}

// Automatic security lint rules
impl SecurityLinter {
    rules: [
        // Key management
        Rule::NoHardcodedKeys,      // Reject: key = "abc123"
        Rule::NoKeysInLogs,         // Reject: log!("{}", private_key)
        
        // Crypto hygiene  
        Rule::NoWeakRandom,          // Reject: rand() for crypto
        Rule::NoECBMode,             // Reject: ECB encryption mode
        Rule::ConstantTimeOps,       // Enforce: timing-safe comparisons
        
        // ZK/FHE safety
        Rule::NoSecretBranching,     // Reject: if secret { ... }
        Rule::NoSecretIndexing,      // Reject: array[secret]
    ]
}

// Compiler generates security documentation
$ ruchy doc --security
WARNING: Function 'auth' uses #[signed] but keys stored insecurely
SUGGEST: Use OS keyring via keyring::get_credential()
EXAMPLE: See docs/security/key-management.md
```

Security becomes a compile-time contract, not documentation.