CWE-335 Base Draft

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

This vulnerability occurs when a Pseudo-Random Number Generator (PRNG) is used, but its initial seed value is not handled securely or predictably, compromising the randomness of its output.

Definition

What is CWE-335?

This vulnerability occurs when a Pseudo-Random Number Generator (PRNG) is used, but its initial seed value is not handled securely or predictably, compromising the randomness of its output.
PRNGs are not truly random; they are deterministic algorithms that produce a sequence of numbers based on an initial seed. If an attacker can discover or guess this seed, they can predict the entire output stream, which is catastrophic for security functions like encryption keys, session tokens, or cryptographic nonces. Therefore, the seed must be treated with the same secrecy as a cryptographic key and should be generated from a robust, unpredictable source. Secure seed management involves two critical practices. First, protect the seed itself as sensitive material—never hard-code it, log it, or transmit it insecurely. Second, source the seed from a cryptographically secure random number generator (CSPRNG) provided by the operating system or trusted library to ensure sufficient entropy. Avoid using predictable values like the current time, process IDs, or static strings, as these drastically reduce the number of possible seeds an attacker would need to guess.
Real-world impact

Real-world CVEs caused by CWE-335

  • CVE-2020-7010

    Cloud application on Kubernetes generates passwords using a weak random number generator based on deployment time.

  • CVE-2019-11495

    server uses erlang:now() to seed the PRNG, which results in a small search space for potential random seeds

  • CVE-2018-12520

    Product's PRNG is not seeded for the generation of session IDs

  • CVE-2016-10180

    Router's PIN generation is based on rand(time(0)) seeding.

How attackers exploit it

Step-by-step attacker path

  1. 1

    The following code uses a statistical PRNG to generate account IDs.

  2. 2

    Because the program uses the same seed value for every invocation of the PRNG, its values are predictable, making the system vulnerable to attack.

  3. 3

    Both of these examples use a statistical PRNG seeded with the current value of the system clock to generate a random number:

  4. 4

    An attacker can easily predict the seed used by these PRNGs, and so also predict the stream of random numbers generated. Note these examples also exhibit CWE-338 (Use of Cryptographically Weak PRNG).

  5. 5

    This code grabs some random bytes and uses them for a seed in a PRNG, in order to generate a new cryptographic key.

Vulnerable code example

Vulnerable Java

The following code uses a statistical PRNG to generate account IDs.

Vulnerable Java 
private static final long SEED = 1234567890;
  public int generateAccountID() {
  	Random random = new Random(SEED);
  	return random.nextInt();
  }
Secure code example

Secure pseudo

Secure pseudo 
// Validate, sanitize, or use a safe API before reaching the sink.
function handleRequest(input) {
  const safe = validateAndEscape(input);
  return executeWithGuards(safe);
}
What changed: the unsafe sink is replaced (or the input is validated/escaped) so the same payload no longer triggers the weakness.
Prevention checklist

How to prevent CWE-335

  • Architecture Use safe-by-default frameworks and APIs that prevent the unsafe pattern from being expressible.
  • Implementation Validate input at trust boundaries; use allowlists, not denylists.
  • Implementation Apply the principle of least privilege to credentials, file paths, and runtime permissions.
  • Testing Cover this weakness in CI: SAST rules + targeted unit tests for the data flow.
  • Operation Monitor logs for the runtime signals listed in the next section.
Detection signals

How to detect CWE-335

SAST High

Run static analysis (SAST) on the codebase looking for the unsafe pattern in the data flow.

DAST Moderate

Run dynamic application security testing against the live endpoint.

Runtime Moderate

Watch runtime logs for unusual exception traces, malformed input, or authorization bypass attempts.

Code review Moderate

Code review: flag any new code that handles input from this surface without using the validated framework helpers.

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Frequently asked questions

Frequently asked questions

What is CWE-335?

This vulnerability occurs when a Pseudo-Random Number Generator (PRNG) is used, but its initial seed value is not handled securely or predictably, compromising the randomness of its output.

How serious is CWE-335?

MITRE has not published a likelihood-of-exploit rating for this weakness. Treat it as medium-impact until your threat model proves otherwise.

What languages or platforms are affected by CWE-335?

MITRE has not specified affected platforms for this CWE — it can apply across most application stacks.

How can I prevent CWE-335?

Use safe-by-default frameworks, validate untrusted input at trust boundaries, and apply the principle of least privilege. Cover the data-flow signature in CI with SAST.

How does Plexicus detect and fix CWE-335?

Plexicus's SAST engine matches the data-flow signature for CWE-335 on every commit. When a match is found, our Codex Remedium agent opens a fix PR with the corrected code, tests, and a one-line summary for the reviewer.

Where can I learn more about CWE-335?

MITRE publishes the canonical definition at https://cwe.mitre.org/data/definitions/335.html. You can also reference OWASP and NIST documentation for adjacent guidance.

Related weaknesses

Weaknesses related to CWE-335

CWE-330 Parent

Use of Insufficiently Random Values

This vulnerability occurs when an application uses random values that are not sufficiently unpredictable in security-sensitive operations,…

CWE-1204 Sibling

Generation of Weak Initialization Vector (IV)

This vulnerability occurs when software uses a weak or predictable Initialization Vector (IV) for cryptographic operations. Many…

CWE-1241 Sibling

Use of Predictable Algorithm in Random Number Generator

This vulnerability occurs when a device or application relies on a predictable algorithm to generate pseudo-random numbers, making the…

CWE-331 Sibling

Insufficient Entropy

This vulnerability occurs when a system's random number generator or algorithm lacks sufficient unpredictability, creating patterns or…

CWE-334 Sibling

Small Space of Random Values

This vulnerability occurs when a system uses a random number generator that produces too few possible values. Attackers can easily predict…

CWE-338 Sibling

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

This vulnerability occurs when software uses a pseudo-random number generator (PRNG) that is not cryptographically strong for…

CWE-340 Sibling

Generation of Predictable Numbers or Identifiers

This vulnerability occurs when a system creates numbers or identifiers that are too easy to guess, undermining security mechanisms that…

CWE-344 Sibling

Use of Invariant Value in Dynamically Changing Context

This vulnerability occurs when code uses a fixed, unchanging value (like a hardcoded string, number, or reference) in a situation where…

CWE-336 Child

Same Seed in Pseudo-Random Number Generator (PRNG)

This vulnerability occurs when a Pseudo-Random Number Generator (PRNG) is repeatedly initialized with the same starting seed value.

Resources

Further reading

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