CVE-2016-5001 in Hadoop
Summary
by MITRE
This is an information disclosure vulnerability in Apache Hadoop before 2.6.4 and 2.7.x before 2.7.2 in the short-circuit reads feature of HDFS. A local user on an HDFS DataNode may be able to craft a block token that grants unauthorized read access to random files by guessing certain fields in the token.
If you want to get best quality of vulnerability data, you may have to visit VulDB.
Analysis
by VulDB Data Team • 01/10/2021
The vulnerability identified as CVE-2016-5001 represents a critical information disclosure flaw within Apache Hadoop's HDFS component affecting versions prior to 2.6.4 and 2.7.2. This security weakness specifically targets the short-circuit reads functionality, which is designed to improve performance by allowing local access to data blocks without network overhead. The vulnerability arises from insufficient randomness in the block token generation process, creating a scenario where malicious local users can exploit predictable token structures to gain unauthorized access to files stored within the Hadoop Distributed File System.
The technical implementation of this vulnerability stems from weak cryptographic practices in the block token creation mechanism. When Hadoop generates block tokens for short-circuit reads, certain fields within these tokens contain insufficient entropy, making them susceptible to brute force attacks or pattern recognition techniques. An attacker with local access to an HDFS DataNode can construct specially crafted block tokens by guessing specific components of the token structure, particularly the sequence numbers, timestamps, or other predictable elements. This weakness allows the attacker to bypass normal access controls and read files that should otherwise be restricted, effectively undermining the integrity of the Hadoop security model. The vulnerability is classified under CWE-330 as the use of insufficiently random values, which directly relates to the predictable nature of the block token generation process.
The operational impact of CVE-2016-5001 extends beyond simple data exposure, potentially enabling broader system compromise and data exfiltration. Since the vulnerability requires only local access to a DataNode, it can be exploited by users with legitimate system access who wish to escalate their privileges or by attackers who have already compromised a system. The implications are particularly severe in environments where Hadoop clusters process sensitive data such as personal information, financial records, or proprietary business data. The vulnerability affects the fundamental security assumptions of Hadoop's access control mechanisms, potentially allowing attackers to read any file accessible through the HDFS short-circuit read feature. This represents a significant threat to data confidentiality and can lead to compliance violations under various regulatory frameworks including gdpr, hipaa, and pci dss standards.
Mitigation strategies for CVE-2016-5001 primarily focus on upgrading to patched versions of Apache Hadoop where the block token generation has been improved to use cryptographically secure random number generators. Organizations should immediately apply the security patches released by Apache for versions 2.6.4 and 2.7.2, which address the insufficient entropy in the token creation process. Additionally, system administrators should consider disabling the short-circuit reads feature entirely if it is not essential for performance requirements, as this eliminates the attack surface entirely. Network segmentation and access controls should be implemented to limit local system access to DataNode processes, while monitoring should be enhanced to detect unusual access patterns that might indicate exploitation attempts. The vulnerability aligns with attack techniques described in the mitre att&ck framework under initial access and privilege escalation categories, specifically targeting the use of local system exploitation to gain unauthorized access to sensitive data. Organizations should also conduct thorough security audits of their Hadoop deployments to identify any other potential weaknesses in the authentication and authorization mechanisms that could compound the risks associated with this vulnerability.