Fuzz introspector
For issues and ideas: https://github.com/ossf/fuzz-introspector/issues

Project functions overview

The following table shows data about each function in the project. The functions included in this table correspond to all functions that exist in the executables of the fuzzers. As such, there may be functions that are from third-party libraries.

For further technical details on the meaning of columns in the below table, please see the Glossary .

Func name Functions filename Args Function call depth Reached by Fuzzers Runtime reached by Fuzzers Combined reached by Fuzzers Fuzzers runtime hit Func lines hit % I Count BB Count Cyclomatic complexity Functions reached Reached by functions Accumulated cyclomatic complexity Undiscovered complexity

Fuzzer details

Fuzzer: fuzz_unpickle

Call tree

The calltree shows the control flow of the fuzzer. This is overlaid with coverage information to display how much of the potential code a fuzzer can reach is in fact covered at runtime. In the following there is a link to a detailed calltree visualisation as well as a bitmap showing a high-level view of the calltree. For further information about these topics please see the glossary for full calltree and calltree overview

Call tree overview bitmap:

The distribution of callsites in terms of coloring is
Color Runtime hitcount Callsite count Percentage
red 0 106 41.4%
gold [1:9] 0 0.0%
yellow [10:29] 0 0.0%
greenyellow [30:49] 0 0.0%
lawngreen 50+ 150 58.5%
All colors 256 100

Fuzz blockers

The following nodes represent call sites where fuzz blockers occur.

Amount of callsites blocked Calltree index Parent function Callsite Largest blocked function
14 66 jsonpickle.unpickler.Unpickler._restore_reduce call site: 00066 jsonpickle.unpickler.Unpickler._swapref
14 115 jsonpickle.util.items call site: 00115 jsonpickle.unpickler.Unpickler._restore
14 214 jsonpickle.unpickler.Unpickler._restore_object_instance_variables call site: 00214 jsonpickle.unpickler.Unpickler._restore_state
9 138 jsonpickle.unpickler.Unpickler._restore_object call site: 00138 jsonpickle.unpickler.Unpickler._call_handler_restore
7 234 jsonpickle.unpickler.Unpickler._restore call site: 00234 jsonpickle.unpickler.loadrepr
6 15 jsonpickle.unpickler.Unpickler.restore call site: 00015 jsonpickle.unpickler.Unpickler.register_classes
5 199 jsonpickle.unpickler.Unpickler._restore_from_dict call site: 00199 .setattr
4 26 jsonpickle.util.translate_module_name call site: 00026 jsonpickle.util.importable_name
4 193 jsonpickle.unpickler.Unpickler._restore_from_dict call site: 00193 .hasattr
3 7 jsonpickle.unpickler.decode call site: 00007 jsonpickle.util._is_function
3 60 jsonpickle.unpickler.Unpickler._restore_reduce call site: 00060 jsonpickle.unpickler.Unpickler._restore
2 2 ...jsonpickle.fuzzing.fuzz-targets.fuzz_unpickle.TestOneInput call site: 00002 fdp.remaining_bytes

Runtime coverage analysis

Covered functions
94
Functions that are reachable but not covered
78
Reachable functions
127
Percentage of reachable functions covered
38.58%
NB: The sum of covered functions and functions that are reachable but not covered need not be equal to Reachable functions . This is because the reachability analysis is an approximation and thus at runtime some functions may be covered that are not included in the reachability analysis. This is a limitation of our static analysis capabilities.
Function name source code lines source lines hit percentage hit

Files reached

filename functions hit
/ 1
...jsonpickle.fuzzing.fuzz-targets.fuzz_unpickle 6
jsonpickle.unpickler 107
jsonpickle.util 18
jsonpickle.handlers 2

Analyses and suggestions

Optimal target analysis

Remaining optimal interesting functions

The following table shows a list of functions that are optimal targets. Optimal targets are identified by finding the functions that in combination, yield a high code coverage.

Func name Functions filename Arg count Args Function depth hitcount instr count bb count cyclomatic complexity Reachable functions Incoming references total cyclomatic complexity Unreached complexity
jsonpickle.ext.pandas.PandasDfHandler.flatten jsonpickle.ext.pandas 3 ['N/A', 'N/A', 'N/A'] 27 0 3 4 5 130 0 440 351
jsonpickle.ext.pandas.PandasDfHandler.restore jsonpickle.ext.pandas 2 ['N/A', 'N/A'] 41 0 3 5 5 143 0 471 72
jsonpickle.ext.numpy.NumpyNDArrayHandlerBinary.restore jsonpickle.ext.numpy 2 ['N/A', 'N/A'] 2 0 3 5 5 18 0 59 50
jsonpickle.ext.numpy.NumpyNDArrayHandlerView.flatten jsonpickle.ext.numpy 3 ['N/A', 'N/A', 'N/A'] 2 0 8 21 11 16 0 60 39

Implementing fuzzers that target the above functions will improve reachability such that it becomes:

Functions statically reachable by fuzzers
57.9%
131 / 227
Cyclomatic complexity statically reachable by fuzzers
61.0%
488 / 794

All functions overview

If you implement fuzzers for these functions, the status of all functions in the project will be:

Func name Functions filename Args Function call depth Reached by Fuzzers Runtime reached by Fuzzers Combined reached by Fuzzers Fuzzers runtime hit Func lines hit % I Count BB Count Cyclomatic complexity Functions reached Reached by functions Accumulated cyclomatic complexity Undiscovered complexity