We present SARVAM, a system for content-based Search And RetrieVAl of Malware. In contrast with traditional static or dynamic analysis, SARVAM uses malware binary content to find similar malware. Given a malware query, a fingerprint is first computed based on transformed image features [19], and similar malware items from the database are then returned using image matching metrics. The current SARVAM database holds approximately 4.3 million samples of malware and benign executables. The system is demonstrated using a desktop computer with Ubuntu OS, and takes approximately 3 seconds per query to find the top matching malware. SARVAM has been operational for the past 15 months during which we have received approximately 212,000 queries from users. In this paper, we describe the design and implementation of SARVAM and also discuss the nature and statistics of queries received.