Comprehensive Categorization: Randomness

A category in the Common Weakness Enumeration published by The MITRE Corporation.


Categories in the Common Weakness Enumeration (CWE) group entries based on some common characteristic or attribute.

Weaknesses in this category are related to randomness.


Generation of Predictable IV with CBC Mode

The product generates and uses a predictable initialization Vector (IV) with Cipher Block Chaining (CBC) Mode, which causes algorithms to be susceptible to dictionary ...

Generation of Predictable Numbers or Identifiers

The product uses a scheme that generates numbers or identifiers that are more predictable than required.

Generation of Weak Initialization Vector (IV)

The product uses a cryptographic primitive that uses an Initialization Vector (IV), but the product does not generate IVs that are sufficiently unpredictable or ...

Improper Handling of Insufficient Entropy in TRNG

True random number generators (TRNG) generally have a limited source of entropy and therefore can fail or block.

Incorrect Usage of Seeds in Pseudo-Random Number Generator (PRNG)

The product uses a Pseudo-Random Number Generator (PRNG) but does not correctly manage seeds.

Insufficient Entropy

The product uses an algorithm or scheme that produces insufficient entropy, leaving patterns or clusters of values that are more likely to occur than others.

Insufficient Entropy in PRNG

The lack of entropy available for, or used by, a Pseudo-Random Number Generator (PRNG) can be a stability and security threat.

J2EE Misconfiguration: Insufficient Session-ID Length

The J2EE application is configured to use an insufficient session ID length.

Predictable Exact Value from Previous Values

An exact value or random number can be precisely predicted by observing previous values.

Predictable from Observable State

A number or object is predictable based on observations that the attacker can make about the state of the system or network, such as time, process ID, etc.

Predictable Seed in Pseudo-Random Number Generator (PRNG)

A Pseudo-Random Number Generator (PRNG) is initialized from a predictable seed, such as the process ID or system time.

Predictable Value Range from Previous Values

The product's random number generator produces a series of values which, when observed, can be used to infer a relatively small range of possibilities for the next val...

Reusing a Nonce, Key Pair in Encryption

Nonces should be used for the present occasion and only once.

Same Seed in Pseudo-Random Number Generator (PRNG)

A Pseudo-Random Number Generator (PRNG) uses the same seed each time the product is initialized.

Small Seed Space in PRNG

A Pseudo-Random Number Generator (PRNG) uses a relatively small seed space, which makes it more susceptible to brute force attacks.

Small Space of Random Values

The number of possible random values is smaller than needed by the product, making it more susceptible to brute force attacks.

Use of Cryptographically Weak Pseudo-Random Number Generator (PRNG)

The product uses a Pseudo-Random Number Generator (PRNG) in a security context, but the PRNG's algorithm is not cryptographically strong.

Use of Insufficiently Random Values

The product uses insufficiently random numbers or values in a security context that depends on unpredictable numbers.

Use of Invariant Value in Dynamically Changing Context

The product uses a constant value, name, or reference, but this value can (or should) vary across different environments.

Use of Predictable Algorithm in Random Number Generator

The device uses an algorithm that is predictable and generates a pseudo-random number.


Comprehensive Categorization for Software Assurance Trends

This view organizes weaknesses around categories that are of interest to large-scale software assurance research to support the elimination of weaknesses using ta...

See Also

  1. CVE --> CWE Mapping Guidance - Quick Tips


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