Java 随机数生成器 Random & SecureRandom_make sure that using this pseudorandom number gene

作者：菜鸟追梦旅行 | 2024-04-13 00:00:15

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make sure that using this pseudorandom number generator is safe here.

Java 里提供了一些用于生成随机数的工具类，这里分析一下其实现原理，以及他们之间的区别、使用场景。

java.util.Random

Random 是比较常用的随机数生成类，它的基本信息在类的注释里都写到了，下面是 JDK8 里该类的注释：


/**
 * An instance of this class is used to generate a stream of
 * pseudorandom numbers. The class uses a 48-bit seed, which is
 * modified using a linear congruential formula. (See Donald Knuth,
 * <i>The Art of Computer Programming, Volume 2</i>, Section 3.2.1.)
 * <p>
 * If two instances of {@code Random} are created with the same
 * seed, and the same sequence of method calls is made for each, they
 * will generate and return identical sequences of numbers. In order to
 * guarantee this property, particular algorithms are specified for the
 * class {@code Random}. Java implementations must use all the algorithms
 * shown here for the class {@code Random}, for the sake of absolute
 * portability of Java code. However, subclasses of class {@code Random}
 * are permitted to use other algorithms, so long as they adhere to the
 * general contracts for all the methods.
 * <p>
 * The algorithms implemented by class {@code Random} use a
 * {@code protected} utility method that on each invocation can supply
 * up to 32 pseudorandomly generated bits.
 * <p>
 * Many applications will find the method {@link Math#random} simpler to use.
 *
 * <p>Instances of {@code java.util.Random} are threadsafe.
 * However, the concurrent use of the same {@code java.util.Random}
 * instance across threads may encounter contention and consequent
 * poor performance. Consider instead using
 * {@link java.util.concurrent.ThreadLocalRandom} in multithreaded
 * designs.
 *
 * <p>Instances of {@code java.util.Random} are not cryptographically
 * secure.  Consider instead using {@link java.security.SecureRandom} to
 * get a cryptographically secure pseudo-random number generator for use
 * by security-sensitive applications.
 *
 * @author  Frank Yellin
 * @since   1.0
 */

翻译一下，主要有以下几点：

Random 类使用线性同余法 linear congruential formula 来生成伪随机数。
两个 Random 实例，如果使用相同的种子 seed，那他们产生的随机数序列也是一样的。
Random 是线程安全的，你的程序如果对性能要求比较高的话，推荐使用 ThreadLocalRandom。
Random 不是密码学安全的，加密相关的推荐使用 SecureRandom。
Random 的基本用法如下所示：


Random random = new Random();
int r = random.nextInt(); // 生成一个随机数

从下面的源码中可以看到，Random 的默认使用当前系统时钟来生成种子 seed。


    private static final AtomicLong seedUniquifier = new AtomicLong(8682522807148012L);
    public Random() {
        this(seedUniquifier() ^ System.nanoTime());
    }
 
    public Random(long seed) {
        if (getClass() == Random.class)
            this.seed = new AtomicLong(initialScramble(seed));
        else {
            // subclass might have overriden setSeed
            this.seed = new AtomicLong();
            setSeed(seed);
        }
    }
 
    private static long seedUniquifier() {
        for (;;) {
            long current = seedUniquifier.get();
            long next = current * 181783497276652981L;
            if (seedUniquifier.compareAndSet(current, next))
                return next;
        }
    }

java.Security.SecureRandom

介绍 Random 类时提到过，要生成加密基本的随机数应该使用 SecureRandom 类，该类信息如下所示：


/**
 * This class provides a cryptographically strong random number
 * generator (RNG).
 *
 * <p>A cryptographically strong random number
 * minimally complies with the statistical random number generator tests
 * specified in <a href="http://csrc.nist.gov/cryptval/140-2.htm">
 * <i>FIPS 140-2, Security Requirements for Cryptographic Modules</i></a>,
 * section 4.9.1.
 * Additionally, SecureRandom must produce non-deterministic output.
 * Therefore any seed material passed to a SecureRandom object must be
 * unpredictable, and all SecureRandom output sequences must be
 * cryptographically strong, as described in
 * <a href="http://www.ietf.org/rfc/rfc1750.txt">
 * <i>RFC 1750: Randomness Recommendations for Security</i></a>.
 *
 * <p>A caller obtains a SecureRandom instance via the
 * no-argument constructor or one of the {@code getInstance} methods:
 *
 * <pre>
 *      SecureRandom random = new SecureRandom();
 * </pre>
 *
 * <p> Many SecureRandom implementations are in the form of a pseudo-random
 * number generator (PRNG), which means they use a deterministic algorithm
 * to produce a pseudo-random sequence from a true random seed.
 * Other implementations may produce true random numbers,
 * and yet others may use a combination of both techniques.
 *
 * <p> Typical callers of SecureRandom invoke the following methods
 * to retrieve random bytes:
 *
 * <pre>
 *      SecureRandom random = new SecureRandom();
 *      byte bytes[] = new byte[20];
 *      random.nextBytes(bytes);
 * </pre>
 *
 * <p> Callers may also invoke the {@code generateSeed} method
 * to generate a given number of seed bytes (to seed other random number
 * generators, for example):
 * <pre>
 *      byte seed[] = random.generateSeed(20);
 * </pre>
 *
 * Note: Depending on the implementation, the {@code generateSeed} and
 * {@code nextBytes} methods may block as entropy is being gathered,
 * for example, if they need to read from /dev/random on various Unix-like
 * operating systems.
 */

主要有以下几点：

该类提供了能满足加密要求的强随机数生成器。
传递给 SecureRandom 种子必须是不可预测的，seed 使用不当引发的安全漏洞可以看看比特币电子钱包漏洞。
一般使用默认的种子生成策略就行，对应 Linux 里面就是 /dev/random 和 /dev/urandom。其实现原理是：操作系统收集了一些随机事件，比如鼠标点击，键盘点击等等，SecureRandom 使用这些随机事件作为种子。
使用 /dev/random 来生成种子时，可能会因为熵不够而阻塞，性能比较差。
SecureRandom 用法如下所示：


SecureRandom random = new SecureRandom();
byte[] data = random.nextBytes(16);

下面我们看看其内部实现：


    synchronized public void nextBytes(byte[] bytes) {
        secureRandomSpi.engineNextBytes(bytes);
    }
    public SecureRandom() {
        super(0);
        getDefaultPRNG(false, null);
    }
    private void getDefaultPRNG(boolean setSeed, byte[] seed) {
        String prng = getPrngAlgorithm();
        if (prng == null) {
            // bummer, get the SUN implementation
            prng = "SHA1PRNG";
            this.secureRandomSpi = new sun.security.provider.SecureRandom();
            this.provider = Providers.getSunProvider();
            if (setSeed) {
                this.secureRandomSpi.engineSetSeed(seed);
            }
        } else {
            try {
                SecureRandom random = SecureRandom.getInstance(prng);
                this.secureRandomSpi = random.getSecureRandomSpi();
                this.provider = random.getProvider();
                if (setSeed) {
                    this.secureRandomSpi.engineSetSeed(seed);
                }
            } catch (NoSuchAlgorithmException nsae) {
                // never happens, because we made sure the algorithm exists
                throw new RuntimeException(nsae);
            }
        }
        if (getClass() == SecureRandom.class) {
            this.algorithm = prng;
        }
    }

在 mac 环境下使用 JDK8 测试时发现，默认使用了 NativePRNG 而非 SHA1PRNG，但是 NativePRNG 其实还是在 sun.security.provider.SecureRandom 的基础上做了一些封装。

在 sun.security.provider.SeedGenerator 类里，可以看到 seed 是利用 /dev/random 或 /dev/urandom 来生成的，启动应用程序时可以通过参数 -Djava.security.egd=file:/dev/urandom 来指定 seed 源。


    static {
        String var0 = SunEntries.getSeedSource();
        if (!var0.equals("file:/dev/random") && !var0.equals("file:/dev/urandom")) {
            if (var0.length() != 0) {
                try {
                    instance = new SeedGenerator.URLSeedGenerator(var0);
                    if (debug != null) {
                        debug.println("Using URL seed generator reading from " + var0);
                    }
                } catch (IOException var2) {
                    if (debug != null) {
                        debug.println("Failed to create seed generator with " + var0 + ": " + var2.toString());
                    }
                }
            }
        } else {
            try {
                instance = new NativeSeedGenerator(var0);
                if (debug != null) {
                    debug.println("Using operating system seed generator" + var0);
                }
            } catch (IOException var3) {
                if (debug != null) {
                    debug.println("Failed to use operating system seed generator: " + var3.toString());
                }
            }
        }
 
        if (instance == null) {
            if (debug != null) {
                debug.println("Using default threaded seed generator");
            }
 
            instance = new SeedGenerator.ThreadedSeedGenerator();
        }
 
    }

在 Random 类里，多个实例设置相同的seed，产生的随机数序列也是一样的。而 SecureRandom 则不同，运行下面的代码：


public class RandomTest {
    public static void main(String[] args) {
        byte[] seed = "hello".getBytes();
        for (int i = 0; i < 10; ++i) {
            SecureRandom secureRandom = new SecureRandom(seed);
            System.out.println(secureRandom.nextInt());
        }
    }
}

输出如下所示，每次运行产生的随机数都不一样。


-2105877601
1151182748
1329080810
-617594950
2094315881
-1649759687
-1360561033
-653424535
-927058354
-1577199965

为什么呢？因为 engineSetSeed 方法设置 seed 时调用的是静态实例 INSTANCE 的 implSetSeed 方法，该方法通过 getMixedRandom 得到的 SecureRandom 来设置 seed，而这个 SecureRandom 初始化种子是系统的。


    private static final NativePRNG.RandomIO INSTANCE;
	// in NativePRNG
    protected void engineSetSeed(byte[] var1) {
        INSTANCE.implSetSeed(var1);
    }
		
        private void implSetSeed(byte[] var1) {
            Object var2 = this.LOCK_SET_SEED;
            synchronized(this.LOCK_SET_SEED) {
                if (!this.seedOutInitialized) {
                    this.seedOutInitialized = true;
                    this.seedOut = (OutputStream)AccessController.doPrivileged(new PrivilegedAction<OutputStream>() {
                        public OutputStream run() {
                            try {
                                return new FileOutputStream(RandomIO.this.seedFile, true);
                            } catch (Exception var2) {
                                return null;
                            }
                        }
                    });
                }
 
                if (this.seedOut != null) {
                    try {
                        this.seedOut.write(var1);
                    } catch (IOException var5) {
                        throw new ProviderException("setSeed() failed", var5);
                    }
                }
 
                this.getMixRandom().engineSetSeed(var1);
            }
        }
 
        private SecureRandom getMixRandom() {
            SecureRandom var1 = this.mixRandom;
            if (var1 == null) {
                Object var2 = this.LOCK_GET_BYTES;
                synchronized(this.LOCK_GET_BYTES) {
                    var1 = this.mixRandom;
                    if (var1 == null) {
                        var1 = new SecureRandom();
 
                        try {
                            byte[] var3 = new byte[20];
                            readFully(this.nextIn, var3);
                            var1.engineSetSeed(var3);
                        } catch (IOException var5) {
                            throw new ProviderException("init failed", var5);
                        }
 
                        this.mixRandom = var1;
                    }
                }
            }
 
            return var1;
        }

在 sun.security.provider.SecureRandom.engineSetSeed 方法里，新种子的生成不仅和刚设置的 seed 有关，也和原来的种子（系统产生的 seed）有关。


	// in sun.security.provider.SecureRandom 
    public synchronized void engineSetSeed(byte[] var1) {
        if (this.state != null) {
            this.digest.update(this.state);
 
            for(int var2 = 0; var2 < this.state.length; ++var2) {
                this.state[var2] = 0;
            }
        }
 
        this.state = this.digest.digest(var1);
    }

/dev/random 与 /dev/urandom
在 Linux 操作系统中，有一个特殊的设备文件 /dev/random，可以用作随机数发生器或伪随机数发生器。

在读取时，/dev/random 设备会返回小于熵池噪声总数的随机字节。/dev/random 可生成高随机性的公钥或一次性密码本。若熵池空了，对/dev/random的读操作将会被阻塞，直到从别的设备中收集到了足够的环境噪声为止。

当然你也可以设置成不堵塞，当你在 open 的时候设置参数 O_NONBLOCK，但是当你read 的时候，如果熵池空了，会返回 -1。

/dev/random 的一个副本是 /dev/urandom （“unlocked”，非阻塞的随机数发生器），它会重复使用熵池中的数据以产生伪随机数据。这表示对/dev/urandom的读取操作不会产生阻塞，但其输出的熵可能小于 /dev/random 的。它可以作为生成较低强度密码的伪随机数生成器，不建议用于生成高强度长期密码。

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