CVE-2007-4397 in irssi
Summary
by MITRE
Multiple CRLF injection vulnerabilities in (1) xmms-thing 1.0, (2) XMMS Remote Control Script 1.07, (3) Disrok 1.0, (4) a2x 0.0.1, (5) Another xmms-info script 1.0, (6) XChat-XMMS 0.8.1, and other unspecified scripts for XChat allow user-assisted remote attackers to execute arbitrary IRC commands via CRLF sequences in the name of the song in a .mp3 file.
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Analysis
by VulDB Data Team • 09/07/2018
The vulnerability described in CVE-2007-4397 represents a significant class of security flaws known as CRLF injection attacks that affect multiple multimedia and IRC integration scripts within the XMMS ecosystem. This vulnerability specifically targets the handling of song metadata, particularly the song name field within .mp3 files, where maliciously crafted CRLF sequences can be embedded to manipulate the behavior of IRC clients that interface with these multimedia applications. The affected software components include xmms-thing 1.0, XMMS Remote Control Script 1.07, Disrok 1.0, a2x 0.0.1, Another xmms-info script 1.0, and XChat-XMMS 0.8.1, all of which process and display song information through IRC protocols. The technical implementation of this vulnerability stems from insufficient input validation and sanitization within the metadata parsing routines of these scripts, where the song name field is directly incorporated into IRC command sequences without proper escaping or encoding of control characters. This flaw falls under the CWE-113 category of Improper Neutralization of CRLF Sequences in HTTP Headers, which is a well-documented weakness that allows attackers to inject arbitrary commands by manipulating line feed and carriage return characters. The operational impact of this vulnerability is severe as it enables remote attackers to execute arbitrary IRC commands through user-assisted means, where an attacker can embed malicious CRLF sequences in the metadata of an audio file that users might play through these vulnerable scripts. When such files are processed by the affected applications, the embedded CRLF sequences are interpreted as command terminators, allowing attackers to inject and execute unauthorized IRC commands such as sending messages, joining channels, or even executing arbitrary commands on the IRC server. The attack vector requires user interaction, meaning that a victim must play a specially crafted audio file through one of the vulnerable XMMS scripts for the attack to succeed, but this user-assisted nature makes the vulnerability particularly dangerous in environments where users frequently share and play multimedia files. The vulnerability demonstrates a critical flaw in the architecture of these IRC integration tools, where the boundary between user-generated content and command execution is not properly enforced. From an ATT&CK perspective, this vulnerability maps to T1059.008 for Command and Scripting Interpreter and T1566.001 for Phishing, as attackers can craft malicious audio files that, when played, execute unintended IRC commands. The security implications extend beyond simple command injection, as successful exploitation could allow attackers to establish persistent communication channels with IRC networks, potentially enabling more sophisticated attacks such as botnet command and control operations or unauthorized access to IRC server resources. The remediation strategy involves implementing strict input validation and sanitization of metadata fields, particularly those that are directly used in protocol communications, and ensuring that all CRLF sequences are properly escaped or removed from user-supplied content before processing. Additionally, developers should implement proper encoding mechanisms for metadata fields that will be used in IRC contexts, following security best practices established in the OWASP Top Ten and other industry standards for preventing injection vulnerabilities. The vulnerability serves as a reminder of the importance of input sanitization in applications that interface with network protocols, especially when dealing with user-generated content that may be processed through multiple layers of interpretation and transmission.