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Utils generate a predictable / zero-UUID on crypto/rand failure

Critical
ReneWerner87 published GHSA-68rr-p4fp-j59v Feb 7, 2026

Package

gomod github.com/gofiber/fiber/v2 (Go)

Affected versions

< v2.52.11

Patched versions

2.52.11

Description

Fiber v2 contains an internal vendored copy of gofiber/utils, and its functions UUIDv4() and UUID() inherit the same critical weakness described in the upstream advisory. On Go versions prior to 1.24, the underlying crypto/rand implementation can return an error if secure randomness cannot be obtained. In such cases, these Fiber v2 UUID functions silently fall back to generating predictable values — the all-zero UUID 00000000-0000-0000-0000-000000000000.

On Go 1.24+, the language guarantees that crypto/rand no longer returns an error (it will block or panic instead), so this vulnerability primarily affects Fiber v2 users running Go 1.23 or earlier, which Fiber v2 officially supports.

Because no error is returned by the Fiber v2 UUID functions, application code may unknowingly rely on predictable, repeated, or low-entropy identifiers in security-critical pathways. This is especially impactful because many Fiber v2 middleware components (session middleware, CSRF, rate limiting, request-ID generation, etc.) default to using utils.UUIDv4().

Impact includes, but is not limited to:

  • Session fixation or hijacking (predictable session IDs)
  • CSRF token forgery or bypass
  • Authentication replay / token prediction
  • Potential denial-of-service (DoS): if the zero UUID is generated, key-based structures (sessions, rate-limits, caches, CSRF stores) may collapse into a single shared key, causing overwrites, lock contention, or state corruption
  • Request-ID collisions, undermining logging and trace integrity
  • General compromise of confidentiality, integrity, and authorization logic relying on UUIDs for uniqueness or secrecy

All Fiber v2 versions containing the internal utils.UUIDv4() / utils.UUID() implementation are affected when running on Go <1.24. No patched Fiber v2 release currently exists.

Suggested Mitigations / Workarounds

Update to the latest version of Fiber v2.

Likelihood / Environmental Factors

It’s important to note that entropy exhaustion on modern Linux systems is extremely rare, as the kernel’s CSPRNG is resilient and non-blocking. However, entropy-source failures — where crypto/rand cannot read from its underlying provider — are significantly more likely in certain environments.

This includes containerized deployments, restricted sandboxes, misconfigured systems lacking read access to /dev/urandom or platform-equivalent sources, chrooted or jailed environments, embedded devices, or systems with non-standard or degraded randomness providers. On Go <1.24, such failures cause crypto/rand to return an error, which the Fiber v2 UUID functions currently treat as a signal to silently generate predictable UUIDs, including the zero UUID. This silent fallback is the root cause of the vulnerability.

References

  • Upstream advisory for gofiber/utils: GHSA-m98w-cqp3-qcqr

  • Source repositories:

    • github.com/gofiber/fiber
    • github.com/gofiber/utils

Credits / Reporter

Reported by @sixcolors (Fiber Maintainer / Security Team)

Severity

Critical

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity High
Attack Requirements Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:H/AT:P/PR:N/UI:N/VC:H/VI:H/VA:L/SC:N/SI:N/SA:N

CVE ID

CVE-2025-66630

Weaknesses

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

The product uses a Pseudo-Random Number Generator (PRNG) in a security context, but the PRNG's algorithm is not cryptographically strong. Learn more on MITRE.

Credits