CVE-2025-1860 identifies a significant cryptographic vulnerability in the ZEFRAM Data::Entropy Perl module, versions 0.007 and earlier. The core issue stems from the module's reliance on the Perl built-in rand() function as its default entropy source for cryptographic operations. The rand() function is a pseudo-random number generator (PRNG) designed for general-purpose randomness and is not cryptographically secure. This means that the output of rand() can be predicted or reproduced by attackers with sufficient knowledge or access, undermining the security guarantees of cryptographic functions that depend on it. The vulnerability is classified under CWE-338 (Use of Cryptographically Weak PRNG) and CWE-331 (Insufficient Entropy). The CVSS 3.1 base score is 7.7 (high severity), reflecting the high impact on confidentiality and integrity without requiring privileges or user interaction, but with local attack vector. Exploitation could allow attackers to predict cryptographic keys, session tokens, or other sensitive values generated by Data::Entropy, leading to unauthorized data disclosure or manipulation. Although no known exploits are currently reported in the wild, the vulnerability poses a significant risk to any system relying on this module for cryptographic randomness. The lack of a patch or update at the time of publication further exacerbates the risk. This vulnerability primarily affects local users or processes with access to the vulnerable Perl environment, as the attack vector is local (AV:L).

For European organizations, the impact of CVE-2025-1860 can be substantial, especially those utilizing Perl-based applications or services that incorporate the ZEFRAM Data::Entropy module for cryptographic functions such as key generation, token creation, or secure random number generation. The predictability of cryptographic values can lead to breaches of confidentiality, allowing attackers to decrypt sensitive data or impersonate legitimate users. Integrity could also be compromised if attackers manipulate cryptographic operations. While availability is not directly impacted, the resulting data breaches or unauthorized access could lead to operational disruptions and regulatory penalties under GDPR and other data protection laws. Sectors such as finance, healthcare, government, and critical infrastructure in Europe, which often rely on Perl for legacy or specialized applications, are particularly at risk. The local attack vector implies that attackers need some level of access to the system, which could be achieved through other vulnerabilities or insider threats, making defense-in-depth strategies critical.

To mitigate this vulnerability, European organizations should first identify all instances of the ZEFRAM Data::Entropy module in their environments. Immediate steps include: 1) Avoid using the default entropy source (rand()) for cryptographic purposes. Instead, configure Data::Entropy or the application to use a cryptographically secure source such as /dev/urandom on Unix-like systems or CryptGenRandom on Windows. 2) If possible, upgrade to a fixed or newer version of Data::Entropy that replaces rand() with a secure PRNG; if no patch exists, consider applying custom patches or switching to alternative Perl modules that provide secure entropy sources (e.g., Crypt::Random). 3) Restrict local access to systems running vulnerable versions to trusted users only and monitor for suspicious activity that could indicate attempts to exploit this weakness. 4) Conduct code audits to ensure no other parts of the application rely on insecure randomness. 5) Implement layered security controls such as application whitelisting, strict access controls, and intrusion detection to prevent attackers from gaining the local access needed to exploit this vulnerability. 6) Prepare incident response plans for potential cryptographic compromise scenarios.