Netflix Lemur is an open-source certificate management tool used to automate the issuance and management of TLS certificates and other credentials. CVE-2023-30797 identifies a vulnerability in Lemur versions before 1.3.2 where default credentials are generated using insufficiently random values, classified under CWE-330 (Use of Insufficiently Random Values). This cryptographic weakness means that the randomness source used to create default passwords or tokens is predictable or has low entropy, enabling attackers to guess or brute-force these credentials remotely without requiring authentication or user interaction. The vulnerability has a CVSS 3.1 base score of 7.5, reflecting its network attack vector (AV:N), low attack complexity (AC:L), no privileges required (PR:N), no user interaction (UI:N), and high confidentiality impact (C:H) but no impact on integrity or availability. Exploiting this flaw could allow unauthorized access to Lemur-managed resources, potentially exposing sensitive certificate data or enabling further lateral movement within an environment. No public exploits or active exploitation campaigns have been reported to date. The vulnerability underscores the importance of using cryptographically secure random number generators when creating credentials, especially in security-critical applications like certificate management. The fix involves updating Lemur to version 1.3.2 or later, where credential generation uses sufficiently random values, eliminating the predictability.

For European organizations, the impact of this vulnerability can be significant, particularly for those relying on Lemur to manage TLS certificates and secrets that protect internal and external communications. Unauthorized access to Lemur could lead to exposure of private keys, issuance of fraudulent certificates, or compromise of other sensitive credentials, undermining confidentiality and trust in secure communications. This could facilitate man-in-the-middle attacks, data breaches, or unauthorized system access. Sectors such as finance, healthcare, telecommunications, and government agencies, which have high reliance on secure certificate management and stringent regulatory requirements (e.g., GDPR), are especially vulnerable. The lack of impact on integrity and availability limits the scope to confidentiality breaches, but the sensitivity of certificate data elevates the risk. Additionally, the ease of exploitation without authentication increases the threat level. Organizations using cloud-native infrastructure and automated certificate management tools are more likely to deploy Lemur and thus face higher exposure.

1. Immediately upgrade Netflix Lemur to version 1.3.2 or later, where the credential generation process uses cryptographically secure random values. 2. Audit all existing default credentials generated by Lemur prior to the patch to identify and replace any weak or potentially compromised credentials. 3. Implement strict access controls and network segmentation to limit exposure of Lemur management interfaces to trusted networks and users only. 4. Enable logging and monitoring on Lemur instances to detect unusual access patterns or repeated failed authentication attempts indicative of brute-force attacks. 5. Consider integrating multi-factor authentication (MFA) for accessing Lemur management interfaces to add an additional security layer. 6. Review and harden the underlying infrastructure hosting Lemur, including patching operating systems and dependencies, to reduce attack surface. 7. Educate security teams about the risks of insufficient randomness in credential generation and enforce secure development practices for internal tools. 8. Regularly review and rotate credentials managed by Lemur to minimize the window of exposure in case of compromise.