CVE-2017-15536 in Data Science Workbench
Summary
by MITRE
An issue was discovered in Cloudera Data Science Workbench (CDSW) 1.x before 1.2.0. Several web application vulnerabilities allow malicious authenticated users of CDSW to escalate privileges in CDSW. CDSW users can exploit these vulnerabilities in combination to gain root access to CDSW nodes, gain access to the CDSW database which includes Kerberos keytabs of CDSW users and bcrypt hashed passwords, and gain access to other privileged information such as session tokens, invitation tokens, and environment variables.
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Analysis
by VulDB Data Team • 01/01/2020
The vulnerability identified as CVE-2017-15536 represents a critical privilege escalation flaw within Cloudera Data Science Workbench version 1.x prior to 1.2.0, demonstrating a significant security weakness in enterprise data science platforms. This vulnerability specifically affects authenticated users who can leverage multiple web application flaws to achieve elevated privileges, ultimately gaining root access to the underlying system nodes. The flaw stems from inadequate access controls and privilege management mechanisms within the CDSW architecture, creating a pathway for malicious actors to move laterally within the system and escalate their privileges beyond what should be permitted for standard users.
The technical implementation of this vulnerability involves a combination of web application flaws that work in concert to enable privilege escalation. Attackers with legitimate user accounts can exploit these weaknesses to gain root-level access to CDSW nodes, which represents a severe compromise of the system's security model. The vulnerability's impact extends beyond simple privilege escalation as it provides access to sensitive database contents including Kerberos keytabs that contain authentication credentials for multiple users. These keytabs represent a particularly dangerous exposure since they contain cryptographic keys used for authentication within the Hadoop ecosystem, potentially allowing attackers to impersonate legitimate users across the entire cluster.
The exposure of bcrypt hashed passwords within the CDSW database represents another critical security concern, as these password hashes can be targeted through various cracking techniques to recover user credentials. Additionally, the vulnerability provides access to session tokens, invitation tokens, and environment variables that contain sensitive configuration information and authentication mechanisms. This comprehensive access to authentication tokens and system information creates a complete compromise scenario where attackers can maintain persistent access and move freely within the system without detection. The vulnerability's impact aligns with CWE-284 (Improper Access Control) and CWE-798 (Use of Hard-coded Credentials), as it demonstrates both inadequate access controls and exposure of sensitive authentication materials.
The operational consequences of this vulnerability are severe for organizations relying on CDSW for data science workloads, as it essentially provides a backdoor for attackers to gain complete system control. The ability to access Kerberos keytabs means that attackers can potentially move laterally across the entire Hadoop ecosystem, as these keytabs are used for authentication across multiple services. Organizations may experience data breaches, unauthorized access to sensitive analytics workloads, and potential compromise of their entire data science infrastructure. The vulnerability's impact is particularly concerning given that it requires only authenticated access, meaning that attackers who can obtain legitimate user credentials or who can exploit other authentication bypasses can immediately begin escalating privileges.
Mitigation strategies for CVE-2017-15536 should focus on immediate patching of the CDSW platform to version 1.2.0 or later, which addresses the privilege escalation vulnerabilities. Organizations should implement additional access controls including network segmentation to limit access to CDSW nodes, enforce strong authentication mechanisms, and regularly audit user access privileges. The exposure of sensitive information such as keytabs and password hashes necessitates immediate credential rotation for all affected users, along with monitoring for suspicious activities that might indicate exploitation attempts. System administrators should also implement monitoring solutions to detect unusual privilege escalation activities and ensure that environment variables and session tokens are properly secured and rotated. This vulnerability demonstrates the importance of maintaining up-to-date security patches and implementing defense-in-depth strategies to protect critical data science platforms from exploitation.