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.


The following examples help to illustrate the nature of this weakness and describe methods or techniques which can be used to mitigate the risk.

Note that the examples here are by no means exhaustive and any given weakness may have many subtle varieties, each of which may require different detection methods or runtime controls.

Example One

This code generates a unique random identifier for a user's session.

function generateSessionID($userID){
  return rand();

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.

This example also exhibits a Small Seed Space (CWE-339).

See Also

Random Number Issues

Weaknesses in this category are related to a software system's random number generation.

Authorize Actors

Weaknesses in this category are related to the design and architecture of a system's authorization components. Frequently these deal with enforcing that agents have th...

SFP Primary Cluster: Predictability

This category identifies Software Fault Patterns (SFPs) within the Predictability cluster.

Comprehensive CWE Dictionary

This view (slice) covers all the elements in CWE.

Weaknesses without Software Fault Patterns

CWE identifiers in this view are weaknesses that do not have associated Software Fault Patterns (SFPs), as covered by the CWE-888 view. As such, they represent gaps in...

CWE Cross-section

This view contains a selection of weaknesses that represent the variety of weaknesses that are captured in CWE, at a level of abstraction that is likely to be useful t...

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