Raw vector
CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-68704 is a high-severity Use of Insufficiently Random Values (CWE-330) vulnerability in Samrocketman Jervis. Its CVSS base score is 8.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Forge Web Credentials (T1606); ranked at the 15th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SC-12 (Cryptographic Key Establishment and Management) and SC-13 (Cryptographic Protection) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2025-68704 affects Jervis, a library used for Job DSL plugin scripts and shared Jenkins pipeline libraries. In versions prior to 2.2, Jervis relies on java.util.Random(), which is not cryptographically secure, for timing attack mitigation. This flaw, classified under CWE-330 (Use of Insufficiently Random Values), carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N), indicating high confidentiality impact with no requirements for privileges or user interaction.
Remote attackers can exploit this vulnerability over the network with low complexity. By leveraging the predictable randomness from java.util.Random(), adversaries may conduct timing attacks to infer sensitive information processed or protected by Jervis in Jenkins environments, potentially disclosing confidential data without impacting integrity or availability.
The vulnerability is addressed in Jervis version 2.2, where the insecure random number generator is replaced. Security practitioners should upgrade to 2.2 or later, as detailed in the GitHub security advisory (GHSA-c9q6-g3hr-8gww) and the fixing commit (c3981ff71de7b0f767dfe7b37a2372cb2a51974a).
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-2024
Vulnerability Data
Jervis is a library for Job DSL plugin scripts and shared Jenkins pipeline libraries. Prior to 2.2, Jervis uses java.util.Random() which is not cryptographically secure for timing attack mitigation. This vulnerability is fixed in 2.2.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 8 hardening rules · 4 OS baselines
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Mitigating Controls (NIST 800-53 r5) AI
SC-12 requires proper cryptographic key establishment and management, which structurally mandates use of sufficient randomness for key generation.
SC-13 requires selection and implementation of approved cryptographic algorithms and methods, which inherently depend on and enforce sufficiently random values.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly enforce use of cryptographically strong RNGs and catch insufficient randomness during design, coding, and testing.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Cryptographic controls require use of approved, sufficiently random values for keys and nonces.
Security testing can detect weak randomness but does not prescribe the control itself.
Secure SDLC processes include verification steps that can catch insufficient randomness but do not directly specify RNG requirements.
Secure coding standards explicitly prohibit use of weak or predictable random number generators.
Secure authentication mechanisms depend on unpredictable values (nonces, salts, session tokens) to resist guessing.
Hardening callouts derived
Configuration rules from DISA STIG baselines that bear on weaknesses of the type cited by this CVE. Each rule is shown with the relationship its mapping actually records, against the CWE it was authored against. Derived via CVE→CWE over `controls_xwalks` (authoritative rows only; rows rated `none` are excluded).
Oracle Linux 8 (3 rules)
- V-248563 The OL 8 SSH server must be configured to use strong entropy. prevents CWE-330
- V-248599 OL 8 must enable the hardware random number generator entropy gatherer service. prevents CWE-330
- V-248600 OL 8 must have the packages required to use the hardware random number generator entropy gatherer service. prevents CWE-330
Oracle Linux 9 (1 rule)
- V-271511 OL 9 must enable the hardware random number generator entropy gatherer service. prevents CWE-330
RHEL 8 (3 rules)
- V-244527 RHEL 8 must have the packages required to use the hardware random number generator entropy gatherer service. prevents CWE-330
- V-230253 RHEL 8 must ensure the SSH server uses strong entropy. prevents CWE-330
- V-230285 RHEL 8 must enable the hardware random number generator entropy gatherer service. prevents CWE-330
RHEL 9 (1 rule)
- V-257782 RHEL 9 must enable the hardware random number generator entropy gatherer service. prevents CWE-330