wifi-densepose/vendor/ruvector/examples/delta-behavior/docs/SECURITY-AUDIT.md

Security Audit Report: Delta-Behavior Implementations

Audit Date: 2026-01-28 Auditor: V3 Security Architect Scope: /workspaces/ruvector/examples/delta-behavior/ Classification: Security Assessment

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Executive Summary

This security audit analyzes the delta-behavior implementations for potential vulnerabilities including unsafe code, denial of service vectors, integer overflow, memory safety issues, race conditions, and containment bypass risks. The codebase demonstrates generally sound security practices with several areas requiring attention.

Overall Risk Assessment: MEDIUM

Severity	Count
Critical	1
High	4
Medium	8
Low	6
Informational	5

---

Table of Contents

1. Core Library (lib.rs)
2. Application 01: Self-Limiting Reasoning
3. Application 02: Computational Event Horizon
4. Application 03: Artificial Homeostasis
5. Application 04: Self-Stabilizing World Model
6. Application 05: Coherence-Bounded Creativity
7. Application 06: Anti-Cascade Financial
8. Application 07: Graceful Aging
9. Application 08: Swarm Intelligence
10. Application 09: Graceful Shutdown
11. Application 10: Pre-AGI Containment
12. Cross-Cutting Concerns
13. Hardening Recommendations

---

1. Core Library (lib.rs)

File: /workspaces/ruvector/examples/delta-behavior/src/lib.rs

1.1 Findings

MEDIUM: Potential Panic in Coherence::new()

Location: Lines 306-311

pub fn new(value: f64) -> Result<Self, &'static str> {
    if value < 0.0 || value > 1.0 {
        Err("Coherence out of range")
    } else {
        Ok(Self(value))
    }
}

Issue: While this returns a Result, the test code uses .unwrap() on line 257:

Coherence::new((self.coherence.value() - loss).max(0.0)).unwrap()

Risk: If floating-point edge cases (NaN, infinity) occur, the .max(0.0) may not protect against invalid values.

Recommendation:

pub fn new(value: f64) -> Result<Self, &'static str> {
    if !value.is_finite() || value < 0.0 || value > 1.0 {
        Err("Coherence out of range or invalid")
    } else {
        Ok(Self(value))
    }
}

LOW: Missing Documentation on Thread Safety

Location: enforcement::SimpleEnforcer (lines 362-409)

Issue: The enforcer maintains mutable state (energy_budget) but there are no synchronization primitives. In a multi-threaded context, this could lead to race conditions.

Recommendation: Document thread-safety requirements or wrap in Mutex<SimpleEnforcer>.

---

2. Application 01: Self-Limiting Reasoning

File: /workspaces/ruvector/examples/delta-behavior/applications/01-self-limiting-reasoning.rs

2.1 Findings

MEDIUM: Potential Infinite Loop in reason()

Location: Lines 142-173

loop {
    if ctx.depth >= ctx.max_depth {
        return ReasoningResult::Collapsed { ... };
    }
    if ctx.coherence < 0.2 {
        return ReasoningResult::Collapsed { ... };
    }
    ctx.depth += 1;
    ctx.coherence *= 0.95;
    // ...
}

Issue: While coherence degradation provides an eventual exit, if reasoner function modifies ctx.coherence to increase it, this could create an infinite loop.

Risk: Denial of Service

Recommendation: Add a hard iteration limit:

const MAX_ITERATIONS: usize = 10000;
for _ in 0..MAX_ITERATIONS {
    // existing loop body
}
ReasoningResult::Collapsed { depth_reached: ctx.depth, reason: CollapseReason::IterationLimitReached }

HIGH: Integer Overflow in Atomic Operations

Location: Lines 216-222

fn f64_to_u64(f: f64) -> u64 {
    (f * 1_000_000_000.0) as u64
}

fn u64_to_f64(u: u64) -> f64 {
    (u as f64) / 1_000_000_000.0
}

Issue: For values > 18.446744073 (u64::MAX / 1_000_000_000), this will overflow. While coherence is bounded 0.0-1.0, the conversion functions are public and could be misused.

Risk: Incorrect state representation leading to bypass of coherence checks.

Recommendation:

fn f64_to_u64(f: f64) -> u64 {
    let clamped = f.clamp(0.0, 1.0);
    (clamped * 1_000_000_000.0) as u64
}

LOW: Race Condition in update_coherence()

Location: Lines 176-180

pub fn update_coherence(&self, delta: f64) {
    let current = self.coherence();
    let new = (current + delta).clamp(0.0, 1.0);
    self.coherence.store(f64_to_u64(new), Ordering::Release);
}

Issue: This is a classic read-modify-write race condition. Between load and store, another thread could modify the value.

Recommendation: Use compare_exchange loop or fetch_update:

pub fn update_coherence(&self, delta: f64) {
    loop {
        let current = self.coherence.load(Ordering::Acquire);
        let current_f64 = u64_to_f64(current);
        let new = (current_f64 + delta).clamp(0.0, 1.0);
        let new_u64 = f64_to_u64(new);
        if self.coherence.compare_exchange(current, new_u64,
            Ordering::AcqRel, Ordering::Acquire).is_ok() {
            break;
        }
    }
}

---

3. Application 02: Computational Event Horizon

File: /workspaces/ruvector/examples/delta-behavior/applications/02-computational-event-horizon.rs

3.1 Findings

HIGH: Resource Exhaustion in Binary Search

Location: Lines 130-147

for _ in 0..50 { // 50 iterations for precision
    let mid = (low + high) / 2.0;
    let interpolated: Vec<f64> = self.current_position.iter()
        .zip(target)
        .map(|(a, b)| a + mid * (b - a))
        .collect();
    // ...
}

Issue: Creates a new Vec allocation on every iteration (50 allocations per move). For high-dimensional state spaces, this could cause memory pressure.

Risk: Memory exhaustion DoS

Recommendation: Pre-allocate buffer:

let mut interpolated = vec![0.0; self.current_position.len()];
for _ in 0..50 {
    for (i, (a, b)) in self.current_position.iter().zip(target).enumerate() {
        interpolated[i] = a + mid * (b - a);
    }
    // ...
}

MEDIUM: Division by Zero Potential

Location: Lines 100-101

let horizon_factor = E.powf(
    self.steepness * proximity_to_horizon / (1.0 - proximity_to_horizon)
);

Issue: When proximity_to_horizon equals exactly 1.0, this divides by zero.

Note: The code checks if proximity_to_horizon >= 1.0 before this, so this is protected. However, floating-point precision could create edge cases.

Recommendation: Add epsilon guard:

let denominator = (1.0 - proximity_to_horizon).max(f64::EPSILON);

LOW: Unbounded Vec Growth

Location: Line 167 (improvements vector)

let mut improvements = Vec::new();

Issue: No capacity limit on improvements vector.

Recommendation: Use Vec::with_capacity(max_iterations) or bounded collection.

---

4. Application 03: Artificial Homeostasis

File: /workspaces/ruvector/examples/delta-behavior/applications/03-artificial-homeostasis.rs

4.1 Findings

CRITICAL: Unsafe Static Mutable Variable

Location: Lines 399-406

fn rand_f64() -> f64 {
    // Simple LCG for reproducibility in tests
    static mut SEED: u64 = 12345;
    unsafe {
        SEED = SEED.wrapping_mul(1103515245).wrapping_add(12345);
        ((SEED >> 16) & 0x7fff) as f64 / 32768.0
    }
}

Issue: This is undefined behavior in Rust. Multiple threads accessing SEED simultaneously causes a data race, which is UB even with unsafe.

Risk: Undefined behavior, potential memory corruption, unpredictable system state.

Recommendation: Use thread-safe RNG:

use std::sync::atomic::{AtomicU64, Ordering};

static SEED: AtomicU64 = AtomicU64::new(12345);

fn rand_f64() -> f64 {
    let mut current = SEED.load(Ordering::Relaxed);
    loop {
        let next = current.wrapping_mul(1103515245).wrapping_add(12345);
        match SEED.compare_exchange_weak(current, next, Ordering::Relaxed, Ordering::Relaxed) {
            Ok(_) => return ((next >> 16) & 0x7fff) as f64 / 32768.0,
            Err(c) => current = c,
        }
    }
}

Or use rand crate with thread_rng().

MEDIUM: Panic in Memory Sorting

Location: Lines 212-213

self.memory.sort_by(|a, b| b.importance.partial_cmp(&a.importance).unwrap());

Issue: partial_cmp returns None for NaN values. The .unwrap() will panic.

Recommendation:

self.memory.sort_by(|a, b| {
    b.importance.partial_cmp(&a.importance).unwrap_or(std::cmp::Ordering::Equal)
});

LOW: Integer Overflow in ID Generation

Location: Lines 288-289

let offspring_id = self.id * 1000 + self.age;

Issue: For organisms with id > u64::MAX/1000, this will overflow.

Recommendation: Use wrapping arithmetic or a proper ID generator:

let offspring_id = self.id.wrapping_mul(1000).wrapping_add(self.age);

---

5. Application 04: Self-Stabilizing World Model

File: /workspaces/ruvector/examples/delta-behavior/applications/04-self-stabilizing-world-model.rs

5.1 Findings

MEDIUM: Unbounded History Growth

Location: Lines 232-237

self.coherence_history.push(self.coherence);

// Trim history
if self.coherence_history.len() > 100 {
    self.coherence_history.remove(0);
}

Issue: remove(0) on a Vec is O(n) - inefficient for bounded buffers.

Recommendation: Use VecDeque for O(1) operations:

use std::collections::VecDeque;

// In struct:
coherence_history: VecDeque<f64>,

// In code:
self.coherence_history.push_back(self.coherence);
if self.coherence_history.len() > 100 {
    self.coherence_history.pop_front();
}

LOW: Unbounded rejected_updates Vector

Location: Lines 187, 206, 218-224

Issue: No limit on rejected updates storage - potential memory exhaustion under attack.

Recommendation: Add capacity limit or use ring buffer.

---

6. Application 05: Coherence-Bounded Creativity

File: /workspaces/ruvector/examples/delta-behavior/applications/05-coherence-bounded-creativity.rs

6.1 Findings

HIGH: Unsafe Static Mutable in pseudo_random()

Location: Lines 372-378

fn pseudo_random() -> usize {
    static mut SEED: usize = 42;
    unsafe {
        SEED = SEED.wrapping_mul(1103515245).wrapping_add(12345);
        (SEED >> 16) & 0x7fff
    }
}

Issue: Same UB issue as Application 03.

Risk: Data race UB

Recommendation: Same fix as Application 03 - use AtomicUsize.

MEDIUM: Integer Overflow in Musical Variation

Location: Lines 258-259

let delta = ((pseudo_random() % 7) as i8 - 3) * (magnitude * 2.0) as i8;
new_notes[idx] = (new_notes[idx] as i8 + delta).clamp(36, 96) as u8;

Issue: If magnitude is large, (magnitude * 2.0) as i8 will overflow/truncate.

Recommendation:

let delta_f64 = ((pseudo_random() % 7) as f64 - 3.0) * magnitude * 2.0;
let delta = delta_f64.clamp(-127.0, 127.0) as i8;

---

7. Application 06: Anti-Cascade Financial

File: /workspaces/ruvector/examples/delta-behavior/applications/06-anti-cascade-financial.rs

7.1 Findings

MEDIUM: Position Index Validation

Location: Lines 333-344

TransactionType::ClosePosition { position_id } => {
    if *position_id < self.positions.len() {
        let pos = self.positions.remove(*position_id);
        // ...
    }
}

Issue: After removing a position, all subsequent indices shift. If multiple ClosePosition transactions reference later indices, they become invalid.

Recommendation: Use stable identifiers instead of indices, or process in reverse order:

// Use HashMap<PositionId, Position> instead of Vec<Position>

MEDIUM: Margin Call Index Shifting

Location: Lines 357-370

TransactionType::MarginCall { participant } => {
    let to_close: Vec<usize> = self.positions.iter()
        .enumerate()
        .filter(|(_, p)| &p.holder == participant && p.leverage > 5.0)
        .map(|(i, _)| i)
        .collect();

    for (offset, idx) in to_close.iter().enumerate() {
        if idx - offset < self.positions.len() {
            self.positions.remove(idx - offset);
        }
    }
}

Issue: The idx - offset pattern is correct but fragile. An underflow would occur if offset > idx, though this shouldn't happen with sequential indices.

Recommendation: Use saturating_sub for safety:

if let Some(adjusted_idx) = idx.checked_sub(offset) {
    if adjusted_idx < self.positions.len() {
        self.positions.remove(adjusted_idx);
    }
}

---

8. Application 07: Graceful Aging

File: /workspaces/ruvector/examples/delta-behavior/applications/07-graceful-aging.rs

8.1 Findings

LOW: Clone in Loop

Location: Line 216

for threshold in &self.age_thresholds.clone() {

Issue: Unnecessary clone - creates allocation overhead.

Recommendation:

let thresholds = self.age_thresholds.clone();
for threshold in &thresholds {

Or restructure to avoid the borrow conflict.

INFO: Time-Based Testing Fragility

Location: Multiple tests using Instant::now()

Issue: Tests using real time may be flaky on slow/overloaded systems.

Recommendation: Use mock time for deterministic testing.

---

9. Application 08: Swarm Intelligence

File: /workspaces/ruvector/examples/delta-behavior/applications/08-swarm-intelligence.rs

9.1 Findings

HIGH: Race Condition in Shared Swarm State

Location: Throughout file

Issue: The CoherentSwarm struct contains mutable state (agents, coherence, history) but provides no synchronization. In a concurrent swarm simulation, multiple agent updates could race.

Risk: Data corruption, incorrect coherence calculations, missed updates.

Recommendation: For concurrent use:

use std::sync::{Arc, RwLock};

pub struct CoherentSwarm {
    agents: RwLock<HashMap<String, SwarmAgent>>,
    coherence: AtomicF64, // Or use parking_lot's atomic float
    // ...
}

Or document that the struct is not thread-safe and must be externally synchronized.

MEDIUM: O(n^2) Neighbor Calculation

Location: Lines 297-317

fn update_neighbors(&mut self) {
    let positions: Vec<(String, (f64, f64))> = self.agents
        .iter()
        .map(|(id, a)| (id.clone(), a.position))
        .collect();

    for (id, agent) in self.agents.iter_mut() {
        agent.neighbor_count = positions.iter()
            .filter(|(other_id, pos)| { ... })
            .count();
    }
}

Issue: For n agents, this is O(n^2). With large swarms, this becomes a performance bottleneck.

Risk: DoS via large swarm creation

Recommendation: Use spatial data structures (quadtree, k-d tree) for O(n log n) neighbor queries, or limit swarm size:

const MAX_AGENTS: usize = 1000;
pub fn add_agent(&mut self, id: &str, position: (f64, f64)) -> Result<(), &'static str> {
    if self.agents.len() >= MAX_AGENTS {
        return Err("Swarm at capacity");
    }
    // ...
}

MEDIUM: Clone Heavy in predict_coherence()

Location: Lines 320-358

fn predict_coherence(&self, agent_id: &str, action: &SwarmAction) -> f64 {
    let mut agents_copy = self.agents.clone();
    // ...
}

Issue: Full clone of agents HashMap for every prediction. For large swarms with frequent predictions, this causes significant allocation pressure.

Recommendation: Consider copy-on-write or differential state tracking.

---

10. Application 09: Graceful Shutdown

File: /workspaces/ruvector/examples/delta-behavior/applications/09-graceful-shutdown.rs

10.1 Findings

LOW: Potential Hook Execution Order Non-Determinism

Location: Lines 261-268

self.shutdown_hooks.sort_by(|a, b| b.priority().cmp(&a.priority()));

for hook in &self.shutdown_hooks {
    println!("[SHUTDOWN] Executing hook: {}", hook.name());
    if let Err(e) = hook.execute() {
        println!("[SHUTDOWN] Hook failed: {} - {}", hook.name(), e);
    }
}

Issue: Hooks with equal priority have undefined order due to unstable sort.

Recommendation: Use sort_by_key with secondary sort on name, or use stable sort:

self.shutdown_hooks.sort_by(|a, b| {
    match b.priority().cmp(&a.priority()) {
        std::cmp::Ordering::Equal => a.name().cmp(b.name()),
        other => other,
    }
});

INFO: Hook Errors Silently Logged

Location: Lines 265-267

Issue: Failed shutdown hooks only print to stdout; no structured error handling.

Recommendation: Return errors from progress_shutdown() or maintain failed hook list.

---

11. Application 10: Pre-AGI Containment

File: /workspaces/ruvector/examples/delta-behavior/applications/10-pre-agi-containment.rs

11.1 Security-Critical Findings

This module is the most security-critical as it implements containment for bounded intelligence growth.

HIGH: Invariant Check Bypass via Rollback Timing

Location: Lines 346-357

// Final invariant check
let violations = self.check_invariants();
if !violations.is_empty() {
    // Rollback
    self.capabilities.insert(domain.clone(), current_level);
    self.coherence += actual_cost;
    self.intelligence = self.calculate_intelligence();

    return GrowthResult::Blocked { ... };
}

Issue: The rollback restores intelligence by recalculation, but if calculate_intelligence() has side effects or depends on other mutable state, the rollback may be incomplete.

Risk: Partial state corruption allowing containment bypass.

Recommendation: Use a transaction pattern:

struct SubstrateSnapshot {
    capabilities: HashMap<CapabilityDomain, f64>,
    coherence: f64,
    intelligence: f64,
}

impl ContainmentSubstrate {
    fn snapshot(&self) -> SubstrateSnapshot { ... }
    fn restore(&mut self, snapshot: SubstrateSnapshot) { ... }
}

MEDIUM: Function Pointer in SafetyInvariant

Location: Lines 86-89

pub struct SafetyInvariant {
    pub name: String,
    pub check: fn(&ContainmentSubstrate) -> bool,
    pub priority: u8,
}

Issue: Using raw function pointers allows potential injection of malicious check functions if the invariant list is modifiable externally.

Recommendation: Make invariants immutable after construction or use a sealed trait pattern:

pub struct SafetyInvariant {
    name: String,  // Remove pub
    check: fn(&ContainmentSubstrate) -> bool,  // Remove pub
    priority: u8,  // Remove pub
}

impl SafetyInvariant {
    pub(crate) fn new(name: &str, check: fn(&ContainmentSubstrate) -> bool, priority: u8) -> Self {
        Self { name: name.to_string(), check, priority }
    }
}

MEDIUM: Coherence Budget Manipulation

Location: Lines 399-404

fn reverse_coherence_cost(&self, domain: &CapabilityDomain, max_cost: f64) -> f64 {
    // ...
    max_cost / divisor
}

Issue: If divisor approaches zero (though current code prevents this), division could produce infinity, allowing unbounded growth.

Recommendation: Add guard:

fn reverse_coherence_cost(&self, domain: &CapabilityDomain, max_cost: f64) -> f64 {
    // ...
    if divisor < f64::EPSILON {
        return 0.0;
    }
    max_cost / divisor
}

INFO: No Rate Limiting on Growth Attempts

Location: attempt_growth() method

Issue: No limit on how frequently growth can be attempted. Rapid-fire growth attempts could stress the system.

Recommendation: Add cooldown or rate limiting:

last_growth_attempt: Option<Instant>,
min_growth_interval: Duration,

---

12. Cross-Cutting Concerns

12.1 Floating-Point Precision

Affected: All modules using f64 for coherence calculations

Issue: Accumulated floating-point errors in coherence calculations could cause:

• Coherence values drifting outside [0.0, 1.0]
• Comparison edge cases (coherence == threshold)
• Non-deterministic behavior across platforms

Recommendation:

1. Use clamp(0.0, 1.0) after every coherence calculation
2. Consider using fixed-point arithmetic for critical thresholds
3. Use epsilon comparisons: (a - b).abs() < EPSILON

12.2 Error Handling Patterns

Affected: All modules

Issue: Mixed use of Result, Option, and panics. Inconsistent error handling makes security review difficult.

Recommendation: Establish consistent error handling:

#[derive(Debug, thiserror::Error)]
pub enum DeltaError {
    #[error("Coherence out of bounds: {0}")]
    CoherenceOutOfBounds(f64),
    #[error("Transition blocked: {0}")]
    TransitionBlocked(String),
    // ...
}

12.3 Denial of Service Vectors

Module	DoS Vector	Mitigation
01-reasoning	Infinite loop	Add iteration limit
02-horizon	Memory allocation	Pre-allocate buffers
04-world-model	Unbounded history	Use bounded VecDeque
08-swarm	O(n^2) neighbors	Use spatial index
All	Large inputs	Add input validation

12.4 Missing Input Validation

Affected: Most public APIs

Issue: Functions accepting f64 parameters don't validate for NaN, infinity, or reasonable ranges.

Recommendation: Create validation wrapper:

fn validate_f64(value: f64, name: &str, min: f64, max: f64) -> Result<f64, DeltaError> {
    if !value.is_finite() {
        return Err(DeltaError::InvalidInput(format!("{} is not finite", name)));
    }
    if value < min || value > max {
        return Err(DeltaError::OutOfRange(format!("{} must be in [{}, {}]", name, min, max)));
    }
    Ok(value)
}

---

13. Hardening Recommendations

13.1 Immediate Actions (Critical/High)

1. Fix Unsafe Static Mutables

   • Files: 03-artificial-homeostasis.rs, 05-coherence-bounded-creativity.rs
   • Action: Replace static mut with AtomicU64/AtomicUsize
   • Timeline: Immediate

2. Add Iteration Limits

   • Files: 01-self-limiting-reasoning.rs
   • Action: Add hard caps on loop iterations
   • Timeline: Within 1 week

3. Thread Safety for Swarm

   • Files: 08-swarm-intelligence.rs
   • Action: Add synchronization or document single-threaded requirement
   • Timeline: Within 2 weeks

4. Atomic Update Coherence

   • Files: 01-self-limiting-reasoning.rs
   • Action: Use compare-exchange for coherence updates
   • Timeline: Within 1 week

13.2 Short-Term Actions (Medium)

5. Replace Vec with VecDeque for Bounded History

   • Files: 04-self-stabilizing-world-model.rs, 06-anti-cascade-financial.rs
   • Timeline: Within 1 month

6. Add Floating-Point Validation

   • Files: All
   • Action: Validate NaN/Infinity on all f64 inputs
   • Timeline: Within 1 month

7. Fix Integer Overflow Potential

   • Files: 01-self-limiting-reasoning.rs, 03-artificial-homeostasis.rs, 05-coherence-bounded-creativity.rs
   • Action: Use wrapping/saturating arithmetic or proper bounds checks
   • Timeline: Within 1 month

8. Improve Containment Rollback

   • Files: 10-pre-agi-containment.rs
   • Action: Implement transaction/snapshot pattern
   • Timeline: Within 2 weeks

13.3 Long-Term Actions (Low/Informational)

9. Consistent Error Handling

   • Action: Adopt thiserror crate and standardize error types
   • Timeline: Within 3 months

10. Performance Optimization

    • Action: Implement spatial indexing for swarm neighbor calculations
    • Timeline: Within 3 months

11. Test Coverage for Edge Cases

    • Action: Add property-based testing for floating-point edge cases
    • Timeline: Within 3 months

12. Security Testing Suite

    • Action: Implement fuzz testing for all public APIs
    • Timeline: Within 6 months

---

Appendix A: Security Test Cases

The following test cases should be added to validate security properties:

#[cfg(test)]
mod security_tests {
    use super::*;

    #[test]
    fn test_nan_coherence_rejected() {
        let result = Coherence::new(f64::NAN);
        assert!(result.is_err());
    }

    #[test]
    fn test_infinity_coherence_rejected() {
        let result = Coherence::new(f64::INFINITY);
        assert!(result.is_err());
    }

    #[test]
    fn test_negative_infinity_coherence_rejected() {
        let result = Coherence::new(f64::NEG_INFINITY);
        assert!(result.is_err());
    }

    #[test]
    fn test_containment_invariants_always_hold() {
        let mut substrate = ContainmentSubstrate::new();

        // Attempt aggressive growth
        for _ in 0..10000 {
            substrate.attempt_growth(CapabilityDomain::SelfModification, 100.0);
            substrate.attempt_growth(CapabilityDomain::Agency, 100.0);

            // Invariants must always hold
            assert!(substrate.coherence >= substrate.min_coherence);
            assert!(substrate.intelligence <= substrate.intelligence_ceiling);
        }
    }

    #[test]
    fn test_swarm_coherence_cannot_go_negative() {
        let mut swarm = CoherentSwarm::new(0.5);
        for i in 0..100 {
            swarm.add_agent(&format!("agent_{}", i), (i as f64 * 100.0, 0.0));
        }
        // Even with dispersed agents, coherence must be >= 0
        assert!(swarm.coherence() >= 0.0);
    }
}

---

Appendix B: Secure Coding Checklist

• No unsafe blocks without security review
• No static mut variables
• All unwrap() calls audited for panic safety
• All loops have termination guarantees
• All floating-point operations handle NaN/Infinity
• All public APIs have input validation
• Thread safety documented or enforced
• Memory allocations are bounded
• Error handling is consistent
• Security-critical invariants are enforced atomically

---

Report Prepared By: V3 Security Architect Review Status: Initial Audit Complete Next Review: After remediation of Critical/High findings