Source: cve@mitre.org
JRuby before 1.6.5.1 computes hash values without restricting the ability to trigger hash collisions predictably, which allows context-dependent attackers to cause a denial of service (CPU consumption) via crafted input to an application that maintains a hash table.
JRuby versions prior to 1.6.5.1 are vulnerable to a denial-of-service (DoS) attack. By providing specially crafted input, attackers can trigger predictable hash collisions, leading to excessive CPU consumption and potentially rendering the application unresponsive.
Step 1: Payload Preparation: The attacker crafts a set of input strings designed to generate the same hash value when processed by JRuby's vulnerable hash function.
Step 2: Input Delivery: The attacker submits the crafted input to the target application, typically through a web form, API call, or other input mechanism.
Step 3: Hash Table Population: The application receives the input and attempts to store the crafted strings in a hash table.
Step 4: Collision Trigger: Due to the predictable hash function, all or a significant portion of the crafted inputs collide, mapping to the same hash bucket.
Step 5: CPU Exhaustion: The application spends an excessive amount of CPU time resolving the hash collisions, as it must linearly search the overloaded hash bucket for each operation. This leads to high CPU utilization.
Step 6: Denial of Service: The application becomes unresponsive or severely degraded in performance due to the CPU exhaustion, effectively resulting in a denial-of-service condition.
The vulnerability stems from a weakness in JRuby's hash function implementation. Specifically, the hash function used to compute hash values for objects within hash tables lacks sufficient randomization. This allows an attacker to craft input that generates predictable hash values, leading to hash collisions. When multiple objects map to the same hash bucket, the hash table's performance degrades significantly as it needs to linearly search the bucket. By providing a large number of inputs that all collide, the attacker can force the application to spend an excessive amount of time resolving these collisions, effectively consuming all available CPU resources and causing a DoS. The root cause is the lack of a robust hash function that mitigates collision attacks. The vulnerability is a form of algorithmic complexity attack, exploiting the worst-case performance of a data structure (hash table) under specific input conditions.
There is no specific APT or malware directly associated with this vulnerability. However, any threat actor targeting applications using vulnerable JRuby versions could potentially leverage this DoS vulnerability. This CVE is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog.
Monitor application CPU usage for sudden and sustained spikes, especially during periods of high input volume.
Analyze application logs for unusually long processing times or errors related to hash table operations.
Network traffic analysis: Look for unusual patterns of requests, especially those with a high volume of input data.
Examine application code for the use of hash tables and the handling of user-supplied input. Identify potential entry points for crafted payloads.
Implement monitoring for application-level denial-of-service attacks.
Upgrade JRuby to version 1.6.5.1 or later.
Implement input validation and sanitization to limit the size and complexity of user-supplied data.
Consider using a more robust hash function or a hash table implementation that mitigates collision attacks (e.g., using a cryptographically secure hash function).
Implement rate limiting to restrict the number of requests from a single source.
Monitor and limit the size of hash tables to prevent excessive memory consumption.
Implement application-level defenses against DoS attacks, such as request throttling and connection limiting.