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This project tries to provide additional Ghidra Version Tracking Correlators suitable for patch diffing.
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PatchDiffCorrelator
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README.md

README.md

First prototype. Do not use in production!

Ghidra Patch Diff Correlator Project

This project tries to provide additional Ghidra Version Tracking Correlators suitable for patch diffing.

How do I install it?

In Ghidra: File -> Install Extensions hit the top right green + icon; then select the ghidra_<VERSION>_PatchDiffCorrelator.zip (that you either build from source with the GhidraDev plugin or downloaded pre-build from the releases section; please make sure VERSION matches your Ghidra version!)

Then restart Ghidra.

How to use?

A simple introduction video:

Youtube video introducing the PatchDiffCorrelator Project

Simple workflow:

  1. Run the Automatic Version Tracking Command.
  2. Run a Bulk * Match Correlator with Only match accepted matches select. This will produce a scoring for your accepted matches for similarity of the functions.

Advanced workflow:

While the Automatic Version Tracking Command find very good matches by running the included Correlators in their defined ordered and automagically accepting good matching, it takes more time than only running the Correlators you need to get your matches. This can be done via (but may vary depending on binary):

  1. Run the Exact Symbols Name Match Correlator if there are symbols.
  2. Run the Exact Function * Match Correlators.
  3. Accept all matched functions.
  4. Accept suitable Implied Matches
  5. Run some Reference Correlators.
  6. Accept matches.
  7. Repeat "conventional" matching until the function you are after has been accepted.
  8. Run a Bulk * Match Correlator with Only match accepted matches select. This will produce a scoring for your accepted matches for similarity of the functions.

Hints

  • The symbol matcher in these correlators is not as good as the included Exact Symbols Name Match Correlator.
  • These matchers are slower than the included Exact Function * Match Correlators, so you should run the included ones first, then exclude them (via selection) from running through the patch diff correlators.
  • The Bulk Basic Block Mnemonics Match Correlator is good for finding basic block changes.
  • The Bulk Mnemomics Match Correlator is robust against instruction reordering performed by compilers.

How does it work?

This adds additional Program Correlators to Ghidra. These are - unlike the Correlators that ship with Ghidra - able to produce Matches with a Similarity Score below 1.00. This means these correlators give an estimate how similar functions are to one another instead of providing perfect matching as the included correlators.

This indicator on similarity is need to find patches in functions.

"Bulk" Correlators

Bulk Instructions Match

The Bulk Instructions Match Correlator will make an unordered bulk list of Instructions occurring in a function.

Let's say we have the function:

PUSH       EBP
MOV        EBP,ESP
SUB        ESP,0x8
MOV        ESP,EBP
POP        EBP
RET

Then the Correlator would "bulk" this to the following list of features:

  • MOV EBP,ESP
  • MOV ESP,EBP
  • POP EBP
  • PUSH EBP
  • RET
  • SUB ESP,0x8

If we now have a function:

PUSH       EBP
MOV        EBP,ESP
SUB        ESP,0x42
MOV        ESP,EBP
POP        EBP
RET

With features:

  • MOV EBP,ESP
  • MOV ESP,EBP
  • POP EBP
  • PUSH EBP
  • RET
  • SUB ESP,0x42

It would match 5 out of 6 features of the earlier function.

The matching is unordered - hence the notion of "bulk".

So a function of (warning: doesn't make sense):

SUB        ESP,0x8
POP        EBP
MOV        EBP,ESP
PUSH       EBP
MOV        ESP,EBP
RET

Would still match 6 of 6 with the original function, because of the unordered bulk comparison logic.

Bulk Mnemonics Match

The Bulk Mnemonics Match Correlator only adds the instruction mnemonics to the feature bundle for matching.

If you have the function:

PUSH       EBP
MOV        EBP,ESP
SUB        ESP,0x8
MOV        ESP,EBP
POP        EBP
RET

Then the Correlator would "bulk" this to the following list of features:

  • MOV
  • MOV
  • POP
  • PUSH
  • RET
  • SUB

If we now have a function:

PUSH       EBP
MOV        EBP,ESP
SUB        ESP,0x42
MOV        ESP,EBP
POP        EBP
RET

With features:

  • MOV
  • MOV
  • POP
  • PUSH
  • RET
  • SUB

would match 6 of 6.

Same unordered remarks as in the [Bulk Instructions Match] Correlator apply.

Bulk Basic Block Mnemonics Match

The Bulk Basic Block Mnemonics Match Correlator first converts the mnemonics of each basic block into a list. That list is sorted and hashes (so the order of the mnemonics within the basic block don't matter). Then these basic block hashes are compared between functions in an unordered bulk comparison.

Options

There are several options:

  • Minimum similarity threshold (score): Only return matches that have a score higher than this threshold.
  • Minimum confidence threshold (score): Confidence is ranked as follows (but may change in the future):
    • 1.0 or 0.000 in log10: When symbols don't match
    • 10.0 or 1.000 in log10: When symbols match
  • Symbol names must match: Only match functions when their symbol names match
    • Warning: If you disable this make sure to set Minimum similarity threshold to something reasonable, otherwise you get the cross-product of all the functions in both binaries, e.g. if the source program has 100 functions and the destination also 100 and no threshold is specified, you'd get 100 * 100 = 100000 matches!
  • Ignore undefined symbols (FUN_): Settings this won't use the default labels assigned to undefined symbols for symbol name matching. So it won't match FUN_00001234 to FUN_00001234.
  • Only match accepted matches: Only calculate the similarity for functions that already have an accepted match entry in the Matches Table. This is the most useful option.

Coloring Correlators

These correlators color address ranges in the Source and Destination Programs that are different.

Abandoned: Coloring Basic Block Mnemonics

State: This is a first work in progess prototype to see whether a correlator is technically able to execute setBackgroundColor() on the Source and Destination Programs.

This colors basic blocks that are either new or deleted or have a different Mnemonic "Bulk" (see [Bulk Mnemonics Match] for a concept of "Bulk").

Current issues:

  • Basic blocks are matched without CFG context.
  • Fails badly if a function contains a duplicate basic block and the other program only contains the basic block once.
  • Version Tracking Correlators can't (and aren't supposed to) color programs

This is implemented as a script.

Other Correlators

Scripts

You can grab just the scripts. They are in PatchDiffCorrelator/ghidra_scripts/.

FunctionDiffColorizer.java

  1. Open Source Program.
  2. In Source Program select the Function you want to compare against the Destination Program (and colorize in the Destination Program).
  3. Run FunctionDiffColorizer.java
    1. Select Destination Program.
    2. Select Destination Function.
  4. The changes of the Destination Function in the Destination Program are now colored.

Issues:

  • if a function contains duplicate basic blocks but the destination only one it just randomly picks one of them for matching
  • complex changes aren't handled optimally

TODO

  • In BasicBlockMnemonicFunctionBulker.hashes() use a proper hashing algorithm to hash the basic blocks.
  • Optimization:
    • Use the instruction prime products concept of BinDiff (see https://www.zynamics.com/bindiff/manual/)
      • For this we need a mnemonic to prime number mapping :/
      • @byte_swap had the idea to work on PCode, so only a mapping PCode -> prime is needed, and that will work on all arches.
  • Help of the Extension isn't available in Ghidra. Need to figure out how to fix that.
  • Figure out this Ghidra bug(?): https://github.com/NationalSecurityAgency/ghidra/issues/1135
  • Add option to only return the highest scoring match(es) for each function instead of the cross product of all functions.
  • Use symbol.getSource() == SourceType.DEFAULT to detect undefined symbols instead of .startswith("FUN_".
  • Either add masking to the Instructions bulker, e.g. via:
from ghidra.app.plugin.core.instructionsearch import InstructionSearchApi
from ghidra.app.plugin.core.instructionsearch.model import MaskSettings
InstructionSearchApi().getBinarySearchString(currentProgram,currentSelection.getFirstRange(),MaskSettings(False,False,True))
  • ... or remove the Instructions bulker ... because it is kind of useless without masking.
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