CVE-2026-11702
Received Received - Intake
Predictable PRNG in Bytes::Random::Secure::Tiny

Publication date: 2026-06-26

Last updated on: 2026-06-26

Assigner: CPANSec

Description
Bytes::Random::Secure::Tiny versions through 1.011 for Perl share internal state across forked processes. When an object is initialised before forking, then the internal state for the PRNG is shared across processes and identical random streams will be produced. Secrets generated in multiprocess applications are predictable across processes.
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Published
2026-06-26
Last Modified
2026-06-26
Generated
2026-06-26
AI Q&A
2026-06-26
EPSS Evaluated
N/A
NVD
EUVD
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
daoswald bytes_random_secure_tiny 1.011
Helpful Resources
Exploitability
CWE
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KEV
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CWE ID Description
CWE-335 The product uses a Pseudo-Random Number Generator (PRNG) but does not correctly manage seeds.
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Executive Summary

The vulnerability exists in the Bytes::Random::Secure::Tiny Perl module versions through 1.011, where the internal state of the pseudo-random number generator (PRNG) is shared across forked processes.

When an object is initialized before a process forks, the child process inherits the parent's PRNG state without reinitialization. This causes both parent and child processes to produce identical random streams.

As a result, secrets generated in multiprocess applications become predictable across these processes, which undermines the security of any cryptographic or random-based operations relying on this module.

Impact Analysis

This vulnerability can lead to predictable random values in applications that use the Bytes::Random::Secure::Tiny module in a multiprocess environment.

If your application generates secrets, tokens, or cryptographic keys using this module before forking, an attacker who can observe the output from one process could predict the secrets generated by other forked processes.

This predictability compromises the confidentiality and security of sensitive data, potentially allowing unauthorized access or other security breaches.

Detection Guidance

This vulnerability involves the internal PRNG state being shared across forked processes in the Bytes::Random::Secure::Tiny Perl module, causing identical random streams. Detection would involve checking if your application uses this Perl module version 1.011 or earlier and whether it initializes the PRNG before forking.

Since the issue is related to predictable random streams after forking, you can attempt to detect it by running a test script that generates random values before and after a fork and comparing the outputs for identical sequences.

Example commands in Perl to detect the issue might include:

  • Write a Perl script that initializes the Bytes::Random::Secure::Tiny object before forking.
  • Fork the process using Perl's fork function.
  • Generate random numbers in both parent and child processes.
  • Compare the random outputs; if they are identical, the vulnerability is present.
Mitigation Strategies

To mitigate this vulnerability, you should update the Bytes::Random::Secure::Tiny Perl module to a version that includes the fix for CVE-2026-11702.

The fix involves reinitializing the PRNG state after a fork by checking the process ID and reseeding the RNG in the child process to ensure independent random streams.

If updating is not immediately possible, as a temporary workaround, avoid initializing the PRNG object before forking or reinitialize the PRNG state manually in child processes after forking.

Refer to the patch or pull request that fixes the issue for implementation details.

Compliance Impact

This vulnerability causes the internal state of the pseudo-random number generator (PRNG) to be shared across forked processes, resulting in predictable random streams and secrets in multiprocess applications.

Predictable secrets can lead to weakened cryptographic protections, which may compromise the confidentiality and integrity of sensitive data.

Such weaknesses could potentially impact compliance with standards and regulations like GDPR and HIPAA, which require adequate protection of personal and sensitive information through strong cryptographic controls.

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