Fuzz introspector
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Project coverage

Table of contents

Project overview: jsonpickle
High level conclusions
Reachability and coverage overview
Fuzzers overview
Project functions overview
Fuzzer details
Fuzzer: fuzz_unpickle
Call tree
Fuzz blockers
Runtime coverage analysis
Files reached
Analyses and suggestions
Optimal target analysis
Remaining optimal interesting functions
All functions overview
Fuzz engine guidance
/src/jsonpickle/fuzzing/fuzz-targets/fuzz_unpickle.py
Dictionary
Fuzzer function priority
Runtime coverage analysis
Complex functions with low coverage
Files and Directories in report
Files in report
Directories in report
Metadata section
Report generation date: 2025-07-11

Project overview: jsonpickle

High level conclusions

Reachability and coverage overview

Functions statically reachable by fuzzers
25.0%
55 / 222
Cyclomatic complexity statically reachable by fuzzers
26.0%
199 / 770
Runtime code coverage of functions
36.0%
81 / 222

Warning: The number of runtime covered functions are larger than the number of reachable functions. This means that Fuzz Introspector found there are more functions covered at runtime than what is considered reachable based on the static analysis. This is a limitation in the analysis as anything covered at runtime is by definition reachable by the fuzzers.
This is likely due to a limitation in the static analysis. In this case, the count of functions covered at runtime is the true value, which means this is what should be considered "achieved" by the fuzzer.

Use the project functions table below to query all functions that were not covered at runtime.

Fuzzers overview

Fuzzer Fuzzer filename Functions Reached Functions unreached Fuzzer depth Files reached Basic blocks reached Cyclomatic complexity Details
fuzz_unpickle /src/jsonpickle/fuzzing/fuzz-targets/fuzz_unpickle.py 120 314 9 4 91 391 fuzz_unpickle.py

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

Full calltree

Call tree overview bitmap:

The distribution of callsites in terms of coloring is
Color Runtime hitcount Callsite count Percentage
red 0 101 40.7%
gold [1:9] 0 0.0%
yellow [10:29] 0 0.0%
greenyellow [30:49] 0 0.0%
lawngreen 50+ 147 59.2%
All colors 248 100

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 59 jsonpickle.unpickler.Unpickler._restore_reduce call site: 00059 jsonpickle.unpickler.Unpickler._swapref
14 96 jsonpickle.util.items call site: 00096 jsonpickle.unpickler.Unpickler._restore
14 201 jsonpickle.unpickler.Unpickler._restore_object_instance_variables call site: 00201 jsonpickle.unpickler.Unpickler._restore_state
7 233 jsonpickle.unpickler.Unpickler._restore call site: 00233 jsonpickle.unpickler.loadrepr
6 15 jsonpickle.unpickler.Unpickler.restore call site: 00015 jsonpickle.unpickler.Unpickler.register_classes
5 186 jsonpickle.unpickler.Unpickler._restore_from_dict call site: 00186 .setattr
4 25 jsonpickle.util.translate_module_name call site: 00025 jsonpickle.util.importable_name
4 131 jsonpickle.unpickler.Unpickler._restore_object call site: 00131 jsonpickle.unpickler.Unpickler._mkref
4 180 jsonpickle.unpickler.Unpickler._restore_from_dict call site: 00180 .hasattr
3 7 jsonpickle.unpickler.decode call site: 00007 jsonpickle.util._is_function
3 53 jsonpickle.unpickler.Unpickler._restore_reduce call site: 00053 jsonpickle.unpickler.Unpickler._restore
2 2 ...jsonpickle.fuzzing.fuzz-targets.fuzz_unpickle.TestOneInput call site: 00002 fdp.remaining_bytes

Runtime coverage analysis

Covered functions
93
Functions that are reachable but not covered
71
Reachable functions
120
Percentage of reachable functions covered
40.83%
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 11

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'] 52 0 3 4 5 124 0 419 343
jsonpickle.ext.pandas.PandasDfHandler.restore jsonpickle.ext.pandas 2 ['N/A', 'N/A'] 36 0 3 5 5 136 0 448 72
jsonpickle.ext.numpy.NumpyNDArrayHandlerBinary.restore jsonpickle.ext.numpy 2 ['N/A', 'N/A'] 2 0 3 5 5 18 0 59 47
jsonpickle.ext.numpy.NumpyNDArrayHandlerBinary.flatten jsonpickle.ext.numpy 3 ['N/A', 'N/A', 'N/A'] 2 0 4 5 5 18 0 60 36

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

Functions statically reachable by fuzzers
57.9%
129 / 222
Cyclomatic complexity statically reachable by fuzzers
61.0%
472 / 770

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

Fuzz engine guidance

This sections provides heuristics that can be used as input to a fuzz engine when running a given fuzz target. The current focus is on providing input that is usable by libFuzzer.

/src/jsonpickle/fuzzing/fuzz-targets/fuzz_unpickle.py

Dictionary

Use this with the libFuzzer -dict=DICT.file flag


Fuzzer function priority

Use one of these functions as input to libfuzzer with flag: -focus_function name 

-focus_function=['jsonpickle.unpickler.Unpickler._restore_reduce', 'jsonpickle.util.items', 'jsonpickle.unpickler.Unpickler._restore_object_instance_variables', 'jsonpickle.unpickler.Unpickler._restore', 'jsonpickle.unpickler.Unpickler.restore', 'jsonpickle.unpickler.Unpickler._restore_from_dict', 'jsonpickle.util.translate_module_name', 'jsonpickle.unpickler.Unpickler._restore_object', 'jsonpickle.unpickler.decode']

Runtime coverage analysis

This section shows analysis of runtime coverage data.

For futher technical details on how this section is generated, please see the Glossary .

Complex functions with low coverage

Func name Function total lines Lines covered at runtime percentage covered Reached by fuzzers
jsonpickle.unpickler.Unpickler._restore_reduce 57 18 31.57% ['fuzz_unpickle']
jsonpickle.unpickler.Unpickler._restore_from_dict 42 21 50.0% ['fuzz_unpickle']
jsonpickle.unpickler.Unpickler._restore_dict 32 13 40.62% ['fuzz_unpickle']
jsonpickle.pickler.Pickler._flatten_obj_instance 105 0 0.0% []

Files and Directories in report

This section shows which files and directories are considered in this report. The main reason for showing this is fuzz introspector may include more code in the reasoning than is desired. This section helps identify if too many files/directories are included, e.g. third party code, which may be irrelevant for the threat model. In the event too much is included, fuzz introspector supports a configuration file that can exclude data from the report. See the following link for more information on how to create a config file: link

Files in report

Source file Reached by Covered by
[] []
jsonpickle.ext [] []
json [] []
importlib [] []
base64 [] []
warnings [] []
jsonpickle.ext.numpy [] []
jsonpickle [] []
pandas [] []
numpy [] []
jsonpickle.tags [] []
queue [] []
io [] []
re [] []
jsonpickle.unpickler ['fuzz_unpickle'] []
threading [] []
jsonpickle.tags_pd [] []
itertools [] []
jsonpickle.compat [] []
uuid [] []
jsonpickle.version [] []
jsonpickle.ext.yaml [] []
inspect [] []
jsonpickle.ext.pandas [] []
jsonpickle.handlers [] []
jsonpickle.ext.gmpy [] []
zlib [] []
...jsonpickle.fuzzing.fuzz-targets.fuzz_unpickle ['fuzz_unpickle'] []
jsonpickle.pickler [] []
gmpy2 [] []
typing [] []
ast [] []
[] []
jsonpickle.errors [] []
jsonpickle.backend [] []
array [] []
utils [] []
jsonpickle.util ['fuzz_unpickle'] []
atheris [] []

Directories in report

Directory

Metadata section

This sections shows the raw data that is used to produce this report. This is mainly used for further processing and developer debugging.

Fuzzer Calltree file Program data file Coverage file
fuzz_unpickle fuzzerLogFile-fuzz_unpickle.data fuzzerLogFile-fuzz_unpickle.data.yaml all_cov.json