Binary Ninja’s extensibility allows for powerful customizations, one of which is the ability to tailor how data is presented in Linear View. This capability is primarily provided by the DataRenderer class (C++, Python). In this post, we’ll delve into how to leverage a DataRenderer to create custom representations for specific types of data, enhancing the clarity and utility of Binary Ninja’s interface for reverse engineering tasks.

Understanding DataRenderers

The DataRenderer class in Binary Ninja enables developers to define custom visual representations for data types in Linear View. This mechanism is particularly useful when the default rendering does not meet specific needs or when a more domain-specific visualization can provide clearer insights into the data’s structure and meaning.

Key Components of a DataRenderer

• perform_is_valid_for_data Method: This method determines if the custom renderer is applicable for a given type of data, based on the address (addr) and context (context). The context is a sequence of Type objects representing the chain of nested objects being displayed.

• perform_get_lines_for_data Method: This method generates the visual representation for the data, returning a list of DisassemblyTextLine objects. Each object represents a single line of output in the Linear View. The method allows for the integration of custom text or graphical elements into the view.

Registering DataRenderers

To make a DataRenderer active, it must be registered with Binary Ninja’s core. This can be done using either register_type_specific or register_generic. Type-specific renderers have precedence over generic ones, allowing for fine-grained control over the rendering of certain data types.

Consider a scenario like reverse engineering a COM library: A whole series of GUIDs will be present and we’ll want to display them in a more human-readable format. A DataRenderer is the perfect solution for this.

Defining a Custom Renderer

Here’s a custom DataRenderer in python – it mirrors one implemented in our core when we released our COMpanion plugin. There’s no need to use this exact plugin in recent versions, but it’s provided as a useful example.

class GuidDataRenderer(DataRenderer):
    def __init__(self):
        super(GuidDataRenderer, self).__init__()

    def perform_is_valid_for_data(self, ctx, view, addr, type, context):
        # Equivalent of checking the platform
        if not view.platform:
            return False

        if type.type_class == TypeClass.StructureTypeClass:
            ntr = type.registered_name
            if ntr and ntr.name == "_GUID":
                if view.is_valid_offset(addr) and view.is_valid_offset(addr + 16):
                    return True
        return False

    def perform_get_lines_for_data(self, ctx, view, addr, type, prefix, width, context):
        result = []
        result.append(DisassemblyTextLine(prefix, addr))
        # read the GUID at the current address and formate it properly
        reader = BinaryReader(view)
        reader.seek(addr)
        data1 = reader.read32()
        data2 = reader.read16()
        data3 = reader.read16()
        dataEnd = reader.read64be()
        data4 = (dataEnd >> 48) & 0xffff
        data5 = dataEnd & 0x0000FFFFFFFFFFFF
        guid_str = f"{data1:08x}-{data2:04x}-{data3:04x}-{data4:04x}-{data5:012x}"
        tokens = [InstructionTextToken(InstructionTextTokenType.TextToken, "  [GUID(\""),
                  InstructionTextToken(InstructionTextTokenType.StringToken, guid_str),
                  InstructionTextToken(InstructionTextTokenType.TextToken, "\")]")]
        result.append(DisassemblyTextLine(tokens, addr))
        return result

GuidDataRenderer().register_type_specific()

Activating the Renderer

GuidDataRenderer().register_type_specific()

By registering the renderer as type-specific, we ensure that it will be used for _GUID structures, overriding the generic structure renderer.

Results

With the custom GuidDataRenderer in place, the GUIDs in Linear View will now be displayed in a more human-readable format, including the GUID string and the corresponding interface name. This enhanced visualization can significantly improve the reverse engineering process by providing more context and clarity around the data being analyzed.

Here’s a before and after image of the renderer being enabled: