CVE-2009-1391 in Compress-raw-zlib Perl Module
Summary
by MITRE
Off-by-one error in the inflate function in Zlib.xs in Compress::Raw::Zlib Perl module before 2.017, as used in AMaViS, SpamAssassin, and possibly other products, allows context-dependent attackers to cause a denial of service (hang or crash) via a crafted zlib compressed stream that triggers a heap-based buffer overflow, as exploited in the wild by Trojan.Downloader-71014 in June 2009.
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Analysis
by VulDB Data Team • 12/22/2024
The vulnerability identified as CVE-2009-1391 represents a critical off-by-one error within the inflate function of the Zlib.xs component in the Compress::Raw::Zlib Perl module. This flaw exists in versions prior to 2.017 and affects several widely deployed security applications including AMaViS and SpamAssassin. The vulnerability stems from improper boundary checking during decompression operations, where the inflate function fails to correctly validate buffer limits when processing compressed data streams. This particular error class falls under CWE-129, which specifically addresses improper validation of array indices and buffer bounds, making it a classic example of buffer overflow conditions that can be exploited through malformed input data.
The technical exploitation of this vulnerability occurs when attackers craft specially malformed zlib compressed streams that trigger a heap-based buffer overflow during decompression. The off-by-one error manifests when the decompression algorithm attempts to write data beyond the allocated buffer boundaries, causing memory corruption that can lead to application hangs or crashes. This behavior is particularly dangerous in email security systems like SpamAssassin and AMaViS, where the processing of malformed email attachments or headers could trigger the vulnerability. The exploit was actively used in the wild through Trojan.Downloader-71014 in June 2009, demonstrating the real-world impact of such flaws in security infrastructure applications.
The operational impact of this vulnerability extends beyond simple denial of service conditions, as it can potentially allow attackers to disrupt email services and security monitoring capabilities. In environments where AMaViS and SpamAssassin are critical components of email security infrastructure, a successful exploitation could lead to complete service disruption, allowing malicious emails to bypass security controls. The vulnerability's context-dependent nature means that exploitation requires specific conditions where the targeted applications process crafted compressed data, but the widespread adoption of the affected Perl module means that numerous systems could be vulnerable. This aligns with ATT&CK technique T1499.004 for network denial of service attacks and represents a significant risk to email security operations. The heap-based buffer overflow can be particularly challenging to detect and mitigate, as it may not always result in immediate crashes but can cause subtle memory corruption that affects system stability over time.
Mitigation strategies for CVE-2009-1391 primarily focus on updating the Compress::Raw::Zlib Perl module to version 2.017 or later, which contains the necessary patches to address the off-by-one error in the inflate function. Organizations should also implement input validation measures that filter or reject malformed compressed data before it reaches the vulnerable decompression functions. Network-based solutions can include implementing content filtering rules that identify and block suspicious compressed data patterns. Additionally, system administrators should conduct thorough vulnerability assessments to identify all instances of the affected Perl module across their infrastructure, as the vulnerability may exist in various security applications beyond the initially identified targets. The fix implemented in version 2.017 demonstrates proper boundary checking and buffer management practices that prevent the heap overflow condition, aligning with secure coding principles that emphasize proper input validation and memory management as outlined in industry standards and best practices.