At the beginning of computer science memory management was a big issue with applications requiring to fit in the small amount of available memory (close to a few kilobytes). Hardware evolution has made this resource cheap for the past few years. Available memory is now close to a few hundred gigabytes. But the current evolution in the multi/many-core era tends to make some issues come back. The memory available tends not to follow the increasing number of cores making the memory resource per thread rare again. We also encounter new issues with the requirement to manage a bigger space with many more allocated objects. This new aspect increases the probability of memory leaks. It also increases the probability of memory management performance issues. Hence, with MALT we provide a tool to track the memory allocated by an application. We then map the extracted metrics onto the source code, just like kcachegrind does with valgrind for the CPU performance. Compared to most available tools, MALT can also be used to track potential performance losses due to bad allocation patterns (too many allocations, small allocations, recycling large allocations, short-lived allocations…) thanks to the various metrics it exposes to the user. This paper will detail the metrics extracted by MALT and how we present them to the user thanks to a nice web based graphical interface which is missing with most of the available Linux tools.