CVE-2018-16985 in Lizard
Summary
by MITRE
In Lizard (formerly LZ5) 2.0, use of an invalid memory address was discovered in LZ5_compress_continue in lz5_compress.c, related to LZ5_compress_fastSmall and MEM_read32. The vulnerability causes a segmentation fault and application crash, which leads to denial of service.
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Analysis
by VulDB Data Team • 05/16/2023
The vulnerability identified as CVE-2018-16985 affects the Lizard compression library version 2.0, formerly known as LZ5, where a critical memory access issue has been discovered within the LZ5_compress_continue function located in lz5_compress.c. This flaw manifests during the execution of LZ5_compress_fastSmall and MEM_read32 operations, creating a scenario where the application attempts to access invalid memory addresses. The root cause stems from inadequate bounds checking and memory validation within the compression algorithm's implementation, specifically when handling certain data patterns that trigger the problematic code path. The vulnerability represents a classic buffer over-read condition that can be exploited through malformed input data or specific compression parameters that cause the compression routine to attempt accessing memory outside of its allocated boundaries.
The technical impact of this vulnerability extends beyond simple application instability, as it creates a reliable denial of service condition that can be triggered by an attacker who controls the input data being compressed. When the LZ5_compress_continue function encounters the invalid memory address scenario, it results in a segmentation fault that terminates the executing process and causes the application to crash. This behavior aligns with CWE-125, which describes out-of-bounds read vulnerabilities, and demonstrates how improper memory handling can lead to system instability. The vulnerability is particularly concerning because compression libraries are often used in network services, file processing pipelines, and system utilities where a single crash can disrupt critical operations and potentially provide an attacker with a means to cause sustained service disruption.
From an operational perspective, this vulnerability creates significant risk for systems that rely on Lizard compression for data processing, particularly in environments where the library handles untrusted input data such as network traffic, file uploads, or user-provided content. The denial of service impact can be leveraged by attackers to disrupt services through carefully crafted compression requests that trigger the segmentation fault. This vulnerability maps to several ATT&CK tactics including TA0040 (defense evasion) and TA0006 (credential access) when considering that service disruption can be used as a precursor to more sophisticated attacks or when the compression service is part of a larger attack chain. The stability implications extend to applications that may be running with elevated privileges or in mission-critical environments where a single crash can cascade into broader system issues.
The recommended mitigations for this vulnerability include immediate upgrading to a patched version of the Lizard library where the memory access validation has been corrected and bounds checking has been implemented. System administrators should also consider implementing input validation and sanitization measures at the application level to prevent malformed data from reaching the compression routines. Additionally, deploying intrusion detection systems that can identify unusual compression patterns or excessive compression requests may help detect potential exploitation attempts. Organizations should also review their software supply chain to ensure that all components using Lizard compression are updated to versions that address this vulnerability, as the issue may be present in multiple applications or services that depend on the affected library. The fix typically involves implementing proper memory boundary checks and ensuring that all memory access operations within the compression functions validate their addresses before attempting to read or write data.