Run static analysis (SAST) on the codebase looking for the unsafe pattern in the data flow.
Insufficient Entropy
This vulnerability occurs when a system's random number generator or algorithm lacks sufficient unpredictability, creating patterns or predictable outputs that are easier for attackers to guess.
What is CWE-331?
Real-world CVEs caused by CWE-331
-
Insufficiently random data used to generate session tokens using C rand(). Also, for certificate/key generation, uses a source that does not block when entropy is low.
-
Chain: insufficient precision (CWE-1339) in random-number generator causes some zero bits to be reliably generated, reducing the amount of entropy (CWE-331)
Step-by-step attacker path
- 1
This code generates a unique random identifier for a user's session.
- 2
Because the seed for the PRNG is always the user's ID, the session ID will always be the same. An attacker could thus predict any user's session ID and potentially hijack the session.
- 3
This example also exhibits a Small Seed Space (CWE-339).
- 4
The following code uses a statistical PRNG to create a URL for a receipt that remains active for some period of time after a purchase.
- 5
This code uses the Random.nextInt() function to generate "unique" identifiers for the receipt pages it generates. Because Random.nextInt() is a statistical PRNG, it is easy for an attacker to guess the strings it generates. Although the underlying design of the receipt system is also faulty, it would be more secure if it used a random number generator that did not produce predictable receipt identifiers, such as a cryptographic PRNG.
Vulnerable PHP
This code generates a unique random identifier for a user's session.
function generateSessionID($userID){
srand($userID);
return rand();
} Secure pseudo
// Validate, sanitize, or use a safe API before reaching the sink.
function handleRequest(input) {
const safe = validateAndEscape(input);
return executeWithGuards(safe);
} How to prevent CWE-331
- Implementation Determine the necessary entropy to adequately provide for randomness and predictability. This can be achieved by increasing the number of bits of objects such as keys and seeds.
How to detect CWE-331
Run dynamic application security testing against the live endpoint.
Watch runtime logs for unusual exception traces, malformed input, or authorization bypass attempts.
Code review: flag any new code that handles input from this surface without using the validated framework helpers.
Plexicus auto-detects CWE-331 and opens a fix PR in under 60 seconds.
Codex Remedium scans every commit, identifies this exact weakness, and ships a reviewer-ready pull request with the patch. No tickets. No hand-offs.
Frequently asked questions
What is CWE-331?
This vulnerability occurs when a system's random number generator or algorithm lacks sufficient unpredictability, creating patterns or predictable outputs that are easier for attackers to guess.
How serious is CWE-331?
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-331?
MITRE has not specified affected platforms for this CWE — it can apply across most application stacks.
How can I prevent CWE-331?
Determine the necessary entropy to adequately provide for randomness and predictability. This can be achieved by increasing the number of bits of objects such as keys and seeds.
How does Plexicus detect and fix CWE-331?
Plexicus's SAST engine matches the data-flow signature for CWE-331 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-331?
MITRE publishes the canonical definition at https://cwe.mitre.org/data/definitions/331.html. You can also reference OWASP and NIST documentation for adjacent guidance.
Weaknesses related to CWE-331
Use of Insufficiently Random Values
This vulnerability occurs when an application uses random values that are not sufficiently unpredictable in security-sensitive operations,…
Generation of Weak Initialization Vector (IV)
This vulnerability occurs when software uses a weak or predictable Initialization Vector (IV) for cryptographic operations. Many…
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…
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…
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…
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…
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…
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…
Insufficient Entropy in PRNG
This vulnerability occurs when a Pseudo-Random Number Generator (PRNG) doesn't have enough randomness (entropy) to start with, or isn't…
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