Cryptographically secure random number generator
A cryptographically secure random number generator produces computationally unpredictable values while resisting prediction and recovery of its internal state by feasible adversaries.
Hacking Cryptography
A cryptographically secure pseudorandom number generator is a pseudorandom number generator whose output and state-recovery properties satisfy security requirements against computationally bounded adversaries.
- How it is used
- Supplies fast cryptographic randomness from entropy-derived seeds for keys, nonces, and related operations.
- How deep it goes
- Explains the Init, Next, and Output state-machine model, then tests it against seed guessing, state recovery, and backdoored constants.
- Examples
- Uses time-based seed guessing, MT19937 state cloning, DUAL_EC_DRBG constants, and a 1 GB video keystream scenario.
- What you can do after
- Operate/configure it by selecting a CSPRNG, seeding from health-tested entropy, and periodically reseeding it.
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Software Security for Developers
A cryptographically secure random number generator produces values that are computationally unpredictable and suitable for cryptographic keys and initialization vectors.
- How it is used
- Generates unpredictable keys and initialization vectors for AES and other cryptographic operations.
- How deep it goes
- Defines the security requirement and Java implementation, but defers randomness theory and mathematical proofs.
- Examples
- Uses Java SecureRandom byte generation and fresh 96-bit IVs for AES-GCM encryption.
- What you can do after
- Apply it via java.security.SecureRandom to generate cryptographic keys and fresh AES-GCM IVs.
Real-World Cryptography
A cryptographically secure pseudorandom number generator is a pseudorandom number generator whose outputs are computationally indistinguishable from uniform random values and whose state resists recovery from observed outputs.
- How it is used
- Supplies fast security randomness when collecting unpredictable entropy is slow.
- How deep it goes
- Explains seeds, deterministic expansion, uniform indistinguishability, state resistance, and secrecy properties without implementation detail.
- Examples
- Uses a seed-to-sequence diagram and contrasts observed outputs with uniform choices.
- What you can do after
- Evaluate/understand when a fast pseudorandom generator can replace slow entropy collection for security randomness.
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Related concepts
- pseudo-random number generatorkind of · A pseudorandom number generator is a deterministic computational process that uses an initial seed or internal state to produce a sequence with random-like statistical properties.
- random_passwordused by · random_password is a Terraform resource type from the hashicorp/random provider that generates a random password value and treats it as sensitive.
- keystreamproduces · A keystream is a sequence of cryptographic bits or symbols generated for combination with plaintext or ciphertext in a stream cipher.
- true random number generatoruses · A true random number generator produces unpredictable values by sampling nondeterministic physical phenomena rather than relying solely on deterministic algorithms.
- Dual ECincludes · Dual EC is an elliptic-curve-based deterministic pseudorandom number generator whose design permits state recovery if its generator points have a hidden mathematical relation.
- generatorkind of · A generator is a computational component or construct that produces data or values from inputs, representations, context, or specified constraints.
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