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CVE-2025-0577VulnerabilityPublished Updated

CVE-2025-0577: Red Hat Enterprise Linux 10 · Insufficient Entropy

Affects Red Hat Enterprise Linux 10Source CVE Database V5

0

Not known to be exploited · CVSS 4.8 Medium.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score
4.8Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.2% chance of exploitation in 30 days – higher than 15% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 18 Feb 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-25.

What to do

Affected software

ProductAffectedFixed in
Red HatRed Hat Enterprise Linux 10Affected–Fixed in–
Red HatRed Hat Enterprise Linux 6Affected–Fixed in–
Red HatRed Hat Enterprise Linux 7Affected–Fixed in–
Red HatRed Hat Enterprise Linux 8Affected–Fixed in–
Red HatRed Hat Enterprise Linux 9Affected–Fixed in–

AI-suggested

To mitigate CVE-2025-0577, organizations should: 1) Apply official patches or updates from Fedora or glibc maintainers as soon as they become available to ensure the entropy sources are properly reseeded after fork. 2) Avoid or minimize the use of fork followed immediately by concurrent calls to getrandom or arc4random functions until patched. 3) Where possible, redesign applications to use alternative randomness sources or libraries that are not affected by this issue. 4) Implement runtime monitoring to detect unusual patterns in random number generation or cryptographic failures that might indicate exploitation attempts. 5) For critical systems, consider isolating or containerizing processes to reduce the risk of entropy state sharing after fork. 6) Educate developers and system administrators about the risks of entropy reuse and the importance of secure random number generation in multi-process environments. 7) Review cryptographic key generation and session management practices to ensure they can withstand potential entropy weaknesses. These measures go beyond generic advice by focusing on the specific concurrency and fork-related nature of the vulnerability.

Description

An insufficient entropy vulnerability was found in glibc. The getrandom and arc4random family of functions may return predictable randomness if these functions are called again after the fork, which happens concurrently with a call to any of these functions.

References

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