CVE-2026-108106 in snappy-java
Summary
by MITRE • 10/09/2026
Xerial snappy-java before 1.1.10.9 contains an unbounded memory allocation vulnerability that allows attackers to exhaust JVM memory by declaring a large uncompressed length in compressed input. Attackers can supply a few crafted bytes to Snappy.uncompress, uncompressString, SnappyInputStream or SnappyFramedInputStream to force allocations up to 2 GB, causing OutOfMemoryError and denial of service.
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Analysis
by VulDB Data Team • 10/09/2026
The vulnerability identified in Xerial snappy-java prior to version 1.1.10.9 represents a critical unbounded memory allocation flaw within the Java implementation of the Snappy compression algorithm. This issue stems from an insufficient validation mechanism when processing compressed data streams, specifically during the decompression phase. The core technical failure lies in how the library interprets the length field embedded within the compressed input format. In standard operation, this field indicates the size of the uncompressed output buffer that must be allocated to hold the resulting data. However, due to a lack of bounds checking against reasonable limits or expected maximums for decompressed content, an attacker can manipulate this value by crafting malicious input where the declared uncompressed length is artificially inflated. This allows the application to request memory allocations far exceeding what is necessary or safe for normal operation, potentially reaching up to 2 gigabytes per single invocation depending on system constraints and JVM settings.
From a technical perspective, this flaw enables a classic denial of service attack vector known as resource exhaustion via unbounded allocation. By invoking methods such as Snappy.uncompress, uncompressString, SnappyInputStream, or SnappyFramedInputStream with specially crafted payloads containing minimal compressed bytes but an excessively large uncompressed length header, the attacker forces the Java Virtual Machine to attempt massive memory allocations. When these requests exceed available heap space or trigger garbage collection overheads that degrade performance significantly, the application experiences severe degradation or crashes entirely due to OutOfMemoryError exceptions. This is particularly dangerous in server-side applications where snappy-java might be used for high-throughput data processing, as a single malicious request can destabilize not only the specific thread handling it but potentially impact other services sharing the same JVM instance if memory limits are shared across contexts.
The operational impact of this vulnerability extends beyond simple application crashes. In distributed systems or microservices architectures that rely on snappy-java for efficient serialization and deserialization, an attacker could exploit this flaw to create a sustained denial-of-service condition without needing significant bandwidth or computational resources themselves. This makes it an attractive target for low-effort attacks aimed at disrupting availability. Furthermore, if the application attempts to recover from these errors by retrying operations or logging stack traces that include large memory dumps, the secondary effects could exacerbate resource consumption and lead to cascading failures across dependent services. The ability to trigger such conditions with just a few crafted bytes underscores the severity of the input validation gap within the library's parsing logic.
To mitigate this risk, organizations utilizing snappy-java must immediately upgrade to version 1.1.10.9 or later, where developers have implemented proper bounds checking and limits on decompressed data sizes. Until an update can be applied in environments with strict change control cycles, defensive measures should include placing the affected services behind a web application firewall that inspects incoming payloads for anomalies in compression headers or size discrepancies between compressed and expected uncompressed lengths. Additionally, configuring JVM heap limits appropriately using flags such as -Xmx to restrict maximum memory usage per process can provide a layer of defense against total system collapse, although this does not prevent the service from becoming unresponsive due to excessive garbage collection pauses. Monitoring tools should also be configured to alert on sudden spikes in memory allocation or frequent OutOfMemoryError events within snappy-related components.
This vulnerability aligns with Common Weakness Enumeration category CWE-789: Uncontrolled Memory Allocation, which describes situations where software allocates memory based on external input without verifying that the size is reasonable relative to available resources. It also maps to MITRE ATT&CK technique T1496: Resource Hijacking, specifically under sub-techniques involving denial of service through resource exhaustion. Understanding these classifications helps security teams prioritize remediation efforts and communicate the risk effectively to stakeholders who may not be familiar with low-level memory management issues in Java libraries. The fix emphasizes the importance of validating all input parameters that influence system resources, ensuring that assumptions about data integrity are rigorously enforced at every layer of processing.