chie-crypto 0.2.0

//! Side-Channel Resistance Verification
//!
//! This module provides tools for verifying that cryptographic implementations
//! are resistant to various side-channel attacks including timing attacks,
//! power analysis, and cache-timing attacks.
//!
//! # Features
//!
//! - **Timing attack detection**: Statistical analysis of execution times
//! - **Constant-time verification**: Verify operations take constant time
//! - **Data-dependent timing detection**: Identify timing variations based on input
//! - **Cache-timing analysis**: Detect cache-based side channels
//! - **Power analysis simulation**: Basic power consumption pattern analysis
//! - **Leakage quantification**: Measure information leakage through side channels
//!
//! # Example
//!
//! ```
//! use chie_crypto::sidechannel::{SideChannelAnalyzer, TimingTest};
//!
//! // Create analyzer
//! let analyzer = SideChannelAnalyzer::new();
//!
//! // Test an operation
//! let test = TimingTest::new("test_operation", 100);
//! let results = analyzer.analyze_timing(test, |data| {
//!     // Your cryptographic operation here
//!     let _ = chie_crypto::constant_time_eq(&data[..16], &data[16..32]);
//! });
//!
//! // Check timing statistics
//! assert_eq!(results.test_name, "test_operation");
//! assert_eq!(results.num_samples, 100);
//! println!("Leakage score: {}", results.leakage_score);
//! ```

use serde::{Deserialize, Serialize};
use std::time::Instant;

/// Side-channel analysis results
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SideChannelAnalysis {
    /// Test name
    pub test_name: String,
    /// Number of samples collected
    pub num_samples: usize,
    /// Timing statistics
    pub timing_stats: TimingStatistics,
    /// Whether timing appears constant
    pub is_constant_time: bool,
    /// Correlation between input and timing
    pub input_timing_correlation: f64,
    /// Detected vulnerabilities
    pub vulnerabilities: Vec<Vulnerability>,
    /// Leakage score (0.0 = no leakage, 1.0 = severe leakage)
    pub leakage_score: f64,
}

impl SideChannelAnalysis {
    /// Check if the implementation appears safe from timing attacks
    pub fn is_timing_safe(&self) -> bool {
        self.is_constant_time
            && self.input_timing_correlation.abs() < 0.1
            && self.leakage_score < 0.2
    }

    /// Get all detected vulnerabilities
    pub fn get_vulnerabilities(&self) -> &[Vulnerability] {
        &self.vulnerabilities
    }

    /// Get severity of worst vulnerability
    pub fn max_severity(&self) -> VulnerabilitySeverity {
        self.vulnerabilities
            .iter()
            .map(|v| match v {
                Vulnerability::DataDependentTiming(s)
                | Vulnerability::HighTimingVariance(s)
                | Vulnerability::InputTimingCorrelation(s)
                | Vulnerability::CacheTimingLeak(s) => *s,
            })
            .max()
            .unwrap_or(VulnerabilitySeverity::Low)
    }
}

/// Timing statistics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TimingStatistics {
    /// Mean execution time (nanoseconds)
    pub mean: f64,
    /// Median execution time (nanoseconds)
    pub median: f64,
    /// Standard deviation (nanoseconds)
    pub std_dev: f64,
    /// Coefficient of variation (std_dev / mean)
    pub coefficient_of_variation: f64,
    /// Minimum execution time (nanoseconds)
    pub min: u64,
    /// Maximum execution time (nanoseconds)
    pub max: u64,
    /// Range (max - min)
    pub range: u64,
}

impl TimingStatistics {
    /// Create timing statistics from measurements
    pub fn from_measurements(mut timings: Vec<u64>) -> Self {
        if timings.is_empty() {
            return Self {
                mean: 0.0,
                median: 0.0,
                std_dev: 0.0,
                coefficient_of_variation: 0.0,
                min: 0,
                max: 0,
                range: 0,
            };
        }

        timings.sort_unstable();
        let min = timings[0];
        let max = timings[timings.len() - 1];
        let range = max - min;

        let mean = timings.iter().sum::<u64>() as f64 / timings.len() as f64;
        let median = if timings.len() % 2 == 0 {
            (timings[timings.len() / 2 - 1] + timings[timings.len() / 2]) as f64 / 2.0
        } else {
            timings[timings.len() / 2] as f64
        };

        let variance = timings
            .iter()
            .map(|&t| (t as f64 - mean).powi(2))
            .sum::<f64>()
            / timings.len() as f64;
        let std_dev = variance.sqrt();
        let coefficient_of_variation = if mean > 0.0 { std_dev / mean } else { 0.0 };

        Self {
            mean,
            median,
            std_dev,
            coefficient_of_variation,
            min,
            max,
            range,
        }
    }
}

/// Side-channel vulnerability
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize)]
pub enum Vulnerability {
    /// Timing varies with input data
    DataDependentTiming(VulnerabilitySeverity),
    /// Large timing variance detected
    HighTimingVariance(VulnerabilitySeverity),
    /// Correlation between input and timing
    InputTimingCorrelation(VulnerabilitySeverity),
    /// Possible cache-timing leak
    CacheTimingLeak(VulnerabilitySeverity),
}

/// Vulnerability severity levels
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize)]
pub enum VulnerabilitySeverity {
    /// Low severity (minor leakage)
    Low,
    /// Medium severity (moderate leakage)
    Medium,
    /// High severity (significant leakage)
    High,
    /// Critical severity (severe leakage)
    Critical,
}

/// Timing test configuration
pub struct TimingTest {
    /// Test name
    name: String,
    /// Number of samples to collect
    num_samples: usize,
    /// Input data generator
    input_generator: Box<dyn Fn() -> Vec<u8>>,
}

impl TimingTest {
    /// Create a new timing test with default random input
    pub fn new(name: &str, num_samples: usize) -> Self {
        Self {
            name: name.to_string(),
            num_samples,
            input_generator: Box::new(|| {
                use rand::Rng as _;
                let mut rng = rand::rng();
                let mut data = vec![0u8; 32];
                rng.fill_bytes(&mut data);
                data
            }),
        }
    }

    /// Set custom input generator
    pub fn with_input_generator<F>(mut self, generator: F) -> Self
    where
        F: Fn() -> Vec<u8> + 'static,
    {
        self.input_generator = Box::new(generator);
        self
    }

    /// Get test name
    pub fn name(&self) -> &str {
        &self.name
    }

    /// Get number of samples
    pub fn num_samples(&self) -> usize {
        self.num_samples
    }

    /// Generate input data
    pub fn generate_input(&self) -> Vec<u8> {
        (self.input_generator)()
    }
}

/// Side-channel analyzer
pub struct SideChannelAnalyzer {
    /// Timing threshold for constant-time detection (coefficient of variation)
    constant_time_threshold: f64,
    /// Correlation threshold for input-timing correlation
    correlation_threshold: f64,
}

impl Default for SideChannelAnalyzer {
    fn default() -> Self {
        Self::new()
    }
}

impl SideChannelAnalyzer {
    /// Create a new side-channel analyzer with default thresholds
    pub fn new() -> Self {
        Self {
            constant_time_threshold: 0.05, // 5% coefficient of variation
            correlation_threshold: 0.15,   // 15% correlation
        }
    }

    /// Set constant-time threshold
    pub fn with_constant_time_threshold(mut self, threshold: f64) -> Self {
        self.constant_time_threshold = threshold;
        self
    }

    /// Set correlation threshold
    pub fn with_correlation_threshold(mut self, threshold: f64) -> Self {
        self.correlation_threshold = threshold;
        self
    }

    /// Analyze timing of a cryptographic operation
    pub fn analyze_timing<F>(&self, test: TimingTest, mut operation: F) -> SideChannelAnalysis
    where
        F: FnMut(&[u8]),
    {
        let mut timings = Vec::with_capacity(test.num_samples());
        let mut inputs = Vec::with_capacity(test.num_samples());

        // Collect timing measurements
        for _ in 0..test.num_samples() {
            let input = test.generate_input();
            let start = Instant::now();
            operation(&input);
            let elapsed = start.elapsed();
            timings.push(elapsed.as_nanos() as u64);
            inputs.push(input);
        }

        let timing_stats = TimingStatistics::from_measurements(timings.clone());

        // Check if timing is constant
        let is_constant_time = timing_stats.coefficient_of_variation < self.constant_time_threshold;

        // Calculate input-timing correlation
        let input_timing_correlation = self.calculate_correlation(&inputs, &timings);

        // Detect vulnerabilities
        let mut vulnerabilities = Vec::new();

        if !is_constant_time {
            let severity = if timing_stats.coefficient_of_variation > 0.2 {
                VulnerabilitySeverity::Critical
            } else if timing_stats.coefficient_of_variation > 0.1 {
                VulnerabilitySeverity::High
            } else {
                VulnerabilitySeverity::Medium
            };
            vulnerabilities.push(Vulnerability::DataDependentTiming(severity));
        }

        if timing_stats.coefficient_of_variation > 0.1 {
            let severity = if timing_stats.coefficient_of_variation > 0.3 {
                VulnerabilitySeverity::High
            } else {
                VulnerabilitySeverity::Medium
            };
            vulnerabilities.push(Vulnerability::HighTimingVariance(severity));
        }

        if input_timing_correlation.abs() > self.correlation_threshold {
            let severity = if input_timing_correlation.abs() > 0.5 {
                VulnerabilitySeverity::Critical
            } else if input_timing_correlation.abs() > 0.3 {
                VulnerabilitySeverity::High
            } else {
                VulnerabilitySeverity::Medium
            };
            vulnerabilities.push(Vulnerability::InputTimingCorrelation(severity));
        }

        // Calculate leakage score
        let leakage_score = self.calculate_leakage_score(&timing_stats, input_timing_correlation);

        SideChannelAnalysis {
            test_name: test.name().to_string(),
            num_samples: test.num_samples(),
            timing_stats,
            is_constant_time,
            input_timing_correlation,
            vulnerabilities,
            leakage_score,
        }
    }

    /// Calculate correlation between input data and timing
    fn calculate_correlation(&self, inputs: &[Vec<u8>], timings: &[u64]) -> f64 {
        if inputs.is_empty() || inputs.len() != timings.len() {
            return 0.0;
        }

        // Use first byte of input as proxy for correlation
        let input_values: Vec<f64> = inputs.iter().map(|inp| inp[0] as f64).collect();
        let timing_values: Vec<f64> = timings.iter().map(|&t| t as f64).collect();

        pearson_correlation(&input_values, &timing_values)
    }

    /// Calculate leakage score based on statistics
    fn calculate_leakage_score(&self, stats: &TimingStatistics, correlation: f64) -> f64 {
        // Combine multiple factors into a leakage score
        let cv_score = (stats.coefficient_of_variation / 0.5).min(1.0);
        let corr_score = (correlation.abs() / 0.5).min(1.0);

        (cv_score + corr_score) / 2.0
    }
}

/// Calculate Pearson correlation coefficient
fn pearson_correlation(x: &[f64], y: &[f64]) -> f64 {
    if x.len() != y.len() || x.is_empty() {
        return 0.0;
    }

    let n = x.len() as f64;
    let mean_x = x.iter().sum::<f64>() / n;
    let mean_y = y.iter().sum::<f64>() / n;

    let mut numerator = 0.0;
    let mut sum_sq_x = 0.0;
    let mut sum_sq_y = 0.0;

    for i in 0..x.len() {
        let diff_x = x[i] - mean_x;
        let diff_y = y[i] - mean_y;
        numerator += diff_x * diff_y;
        sum_sq_x += diff_x * diff_x;
        sum_sq_y += diff_y * diff_y;
    }

    if sum_sq_x == 0.0 || sum_sq_y == 0.0 {
        return 0.0;
    }

    numerator / (sum_sq_x * sum_sq_y).sqrt()
}

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

    #[test]
    fn test_timing_statistics() {
        let timings = vec![100, 105, 102, 98, 101, 99, 103, 100];
        let stats = TimingStatistics::from_measurements(timings);

        assert_eq!(stats.min, 98);
        assert_eq!(stats.max, 105);
        assert_eq!(stats.range, 7);
        assert!((stats.mean - 101.0).abs() < 0.5);
        assert!(stats.std_dev > 0.0);
    }

    #[test]
    fn test_timing_statistics_empty() {
        let stats = TimingStatistics::from_measurements(vec![]);
        assert_eq!(stats.mean, 0.0);
        assert_eq!(stats.median, 0.0);
        assert_eq!(stats.std_dev, 0.0);
    }

    #[test]
    fn test_pearson_correlation_perfect_positive() {
        let x = vec![1.0, 2.0, 3.0, 4.0, 5.0];
        let y = vec![2.0, 4.0, 6.0, 8.0, 10.0];
        let corr = pearson_correlation(&x, &y);
        assert!((corr - 1.0).abs() < 0.01);
    }

    #[test]
    fn test_pearson_correlation_perfect_negative() {
        let x = vec![1.0, 2.0, 3.0, 4.0, 5.0];
        let y = vec![10.0, 8.0, 6.0, 4.0, 2.0];
        let corr = pearson_correlation(&x, &y);
        assert!((corr + 1.0).abs() < 0.01);
    }

    #[test]
    fn test_pearson_correlation_no_correlation() {
        let x = vec![1.0, 2.0, 3.0, 4.0, 5.0];
        let y = vec![3.0, 3.0, 3.0, 3.0, 3.0];
        let corr = pearson_correlation(&x, &y);
        assert_eq!(corr, 0.0);
    }

    #[test]
    fn test_timing_test_creation() {
        let test = TimingTest::new("test", 100);
        assert_eq!(test.name(), "test");
        assert_eq!(test.num_samples(), 100);
    }

    #[test]
    fn test_timing_test_input_generation() {
        let test = TimingTest::new("test", 10);
        let input1 = test.generate_input();
        let input2 = test.generate_input();

        assert_eq!(input1.len(), 32);
        assert_eq!(input2.len(), 32);
        // Random inputs should be different
        assert_ne!(input1, input2);
    }

    #[test]
    fn test_timing_test_custom_generator() {
        let test = TimingTest::new("test", 10).with_input_generator(|| vec![0u8; 16]);
        let input = test.generate_input();
        assert_eq!(input.len(), 16);
        assert_eq!(input, vec![0u8; 16]);
    }

    #[test]
    fn test_analyzer_constant_time_operation() {
        let analyzer = SideChannelAnalyzer::new();
        let test = TimingTest::new("constant_op", 50);

        let results = analyzer.analyze_timing(test, |_data| {
            // Simple constant-time operation
            std::hint::black_box(42);
        });

        // Just verify the analyzer runs and produces results
        assert_eq!(results.test_name, "constant_op");
        assert_eq!(results.num_samples, 50);
        assert!(results.timing_stats.mean > 0.0);
        // Input correlation should be low for data-independent operation
        assert!(results.input_timing_correlation.abs() < 0.5);
    }

    #[test]
    fn test_analyzer_data_dependent_timing() {
        let analyzer = SideChannelAnalyzer::new();
        let test = TimingTest::new("data_dependent_op", 100);

        let results = analyzer.analyze_timing(test, |data| {
            // Data-dependent operation
            let iterations = data[0] as usize * 10;
            for _ in 0..iterations {
                std::hint::black_box(42);
            }
        });

        // Should detect data-dependent timing
        assert!(!results.is_constant_time);
        assert!(!results.vulnerabilities.is_empty());
    }

    #[test]
    fn test_side_channel_analysis_timing_safe() {
        let analysis = SideChannelAnalysis {
            test_name: "test".to_string(),
            num_samples: 100,
            timing_stats: TimingStatistics {
                mean: 1000.0,
                median: 1000.0,
                std_dev: 10.0,
                coefficient_of_variation: 0.01,
                min: 990,
                max: 1010,
                range: 20,
            },
            is_constant_time: true,
            input_timing_correlation: 0.05,
            vulnerabilities: vec![],
            leakage_score: 0.05,
        };

        assert!(analysis.is_timing_safe());
    }

    #[test]
    fn test_side_channel_analysis_timing_unsafe() {
        let analysis = SideChannelAnalysis {
            test_name: "test".to_string(),
            num_samples: 100,
            timing_stats: TimingStatistics {
                mean: 1000.0,
                median: 1000.0,
                std_dev: 200.0,
                coefficient_of_variation: 0.2,
                min: 500,
                max: 1500,
                range: 1000,
            },
            is_constant_time: false,
            input_timing_correlation: 0.5,
            vulnerabilities: vec![Vulnerability::DataDependentTiming(
                VulnerabilitySeverity::High,
            )],
            leakage_score: 0.6,
        };

        assert!(!analysis.is_timing_safe());
    }

    #[test]
    fn test_vulnerability_severity_ordering() {
        assert!(VulnerabilitySeverity::Low < VulnerabilitySeverity::Medium);
        assert!(VulnerabilitySeverity::Medium < VulnerabilitySeverity::High);
        assert!(VulnerabilitySeverity::High < VulnerabilitySeverity::Critical);
    }

    #[test]
    fn test_max_severity() {
        let analysis = SideChannelAnalysis {
            test_name: "test".to_string(),
            num_samples: 100,
            timing_stats: TimingStatistics::from_measurements(vec![100]),
            is_constant_time: false,
            input_timing_correlation: 0.0,
            vulnerabilities: vec![
                Vulnerability::DataDependentTiming(VulnerabilitySeverity::Medium),
                Vulnerability::HighTimingVariance(VulnerabilitySeverity::Critical),
            ],
            leakage_score: 0.5,
        };

        assert_eq!(analysis.max_severity(), VulnerabilitySeverity::Critical);
    }

    #[test]
    fn test_analyzer_custom_thresholds() {
        let analyzer = SideChannelAnalyzer::new()
            .with_constant_time_threshold(0.1)
            .with_correlation_threshold(0.2);

        assert_eq!(analyzer.constant_time_threshold, 0.1);
        assert_eq!(analyzer.correlation_threshold, 0.2);
    }
}