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

Table of contents

Project overview: scipy
High level conclusions
Reachability and coverage overview
Fuzzers overview
Project functions overview
Fuzzer details
Fuzzer: fuzz_io_wavfile
Call tree
Fuzz blockers
Runtime coverage analysis
Files reached
Fuzzer: fuzz_io_mio5
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/fuzz_io_wavfile.py
Dictionary
Fuzzer function priority
/src/fuzz_io_mio5.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
Sink analyser for CWEs
Report generation date: 2024-02-14

Project overview: scipy

High level conclusions

Reachability and coverage overview

Functions statically reachable by fuzzers
0.0%
19 / 6840
Cyclomatic complexity statically reachable by fuzzers
0.0%
81 / 24729
Runtime code coverage of functions
4.0%
265 / 6840

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_io_wavfile /src/fuzz_io_wavfile.py 28 11446 4 3 40 97 fuzz_io_wavfile.py
fuzz_io_mio5 /src/fuzz_io_mio5.py 31 11443 5 4 19 98 fuzz_io_mio5.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 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_io_wavfile

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 18 27.2%
gold [1:9] 0 0.0%
yellow [10:29] 0 0.0%
greenyellow [30:49] 0 0.0%
lawngreen 50+ 48 72.7%
All colors 66 100

Fuzz blockers

The following nodes represent call sites where fuzz blockers occur.

Amount of callsites blocked Calltree index Parent function Callsite Largest blocked function
12 44 scipy.io.wavfile._read_data_chunk call site: 00044 fid.seek
1 14 scipy.io.wavfile.read call site: 00014 fid.tell
1 17 scipy.io.wavfile.read call site: 00017 warnings.warn
1 41 scipy.io.wavfile._read_data_chunk call site: 00041 scipy.io.wavfile._raise_bad_format
1 57 scipy.io.wavfile._read_data_chunk call site: 00057 data.reshape
1 59 scipy.io.wavfile.read call site: 00059 scipy.io.wavfile._skip_unknown_chunk
1 64 scipy.io.wavfile.read call site: 00064 fid.seek

Runtime coverage analysis

Covered functions
475
Functions that are reachable but not covered
21
Reachable functions
28
Percentage of reachable functions covered
25.0%
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.
Warning: The number of covered functions are larger than the number of reachable functions. This means that there are more functions covered at runtime than are extracted using static analysis. This is likely a result of the static analysis component failing to extract the right call graph or the coverage runtime being compiled with sanitizers in code that the static analysis has not analysed. This can happen if lto/gold is not used in all places that coverage instrumentation is used.
Function name source code lines source lines hit percentage hit

Files reached

filename functions hit
/ 1
...fuzz_io_wavfile 4
scipy.io.wavfile 25

Fuzzer: fuzz_io_mio5

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 45 90.0%
gold [1:9] 0 0.0%
yellow [10:29] 0 0.0%
greenyellow [30:49] 0 0.0%
lawngreen 50+ 5 10.0%
All colors 50 100

Fuzz blockers

The following nodes represent call sites where fuzz blockers occur.

Amount of callsites blocked Calltree index Parent function Callsite Largest blocked function
43 6 ...fuzz_io_mio5.TestOneInput call site: 00006 scipy.io.matlab._mio5._simplify_cells
2 3 ...fuzz_io_mio5.TestOneInput call site: 00003 .super

Runtime coverage analysis

Covered functions
475
Functions that are reachable but not covered
30
Reachable functions
31
Percentage of reachable functions covered
3.23%
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.
Warning: The number of covered functions are larger than the number of reachable functions. This means that there are more functions covered at runtime than are extracted using static analysis. This is likely a result of the static analysis component failing to extract the right call graph or the coverage runtime being compiled with sanitizers in code that the static analysis has not analysed. This can happen if lto/gold is not used in all places that coverage instrumentation is used.
Function name source code lines source lines hit percentage hit

Files reached

filename functions hit
/ 1
...fuzz_io_mio5 4
scipy.io.matlab._mio5 25
scipy.io.matlab._miobase 3

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
scipy.stats._continuous_distns.powerlaw_gen.fit scipy.stats._continuous_distns 4 ['N/A', 'N/A', 'N/A', 'N/A'] 24 0 0 16 9 1048 0 3262 3241

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

Functions statically reachable by fuzzers
11.0%
731 / 6840
Cyclomatic complexity statically reachable by fuzzers
9.0%
2332 / 24729

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 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/fuzz_io_wavfile.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=['scipy.io.wavfile._read_data_chunk', 'scipy.io.wavfile.read']

/src/fuzz_io_mio5.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=['...fuzz_io_mio5.TestOneInput']

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
scipy.io._netcdf.netcdf_file.__init__ 33 0 0.0% []
scipy.io._netcdf.netcdf_file._read_var_array 48 0 0.0% []
scipy.io.wavfile._read_data_chunk 43 20 46.51% ['fuzz_io_wavfile']
scipy.io.wavfile.write 44 0 0.0% []
scipy._lib._testutils.PytestTester.__call__ 34 5 14.70% []
fig.colorbar 297 5 1.683% []
os.rename 571 16 2.802% []
t.append 1730 186 10.75% []
importlib.import_module 101 3 2.970% []
re.escape 2478 657 26.51% []
m.conj 521 6 1.151% []
scipy.io._fortran.FortranFile.read_record 31 0 0.0% []
d.get 225 19 8.444% []
mmap.mmap 92 19 20.65% []
scipy.io._harwell_boeing.hb.HBInfo.from_file 44 0 0.0% []
scipy.io._harwell_boeing.hb.HBInfo.__init__ 48 0 0.0% []
scipy.sparse._compressed._cs_matrix.__init__ 45 0 0.0% []
scipy.sparse._compressed._cs_matrix.multiply 66 0 0.0% []
scipy.sparse._compressed._cs_matrix._insert_many 44 0 0.0% []
r.diagonal 56 10 17.85% []
scipy.sparse.csgraph._laplacian._laplacian_dense_flo 32 0 0.0% []
scipy.sparse._sputils.check_shape 35 0 0.0% []
scipy.sparse._base._spbase._matmul_dispatch 43 0 0.0% []
typing.get_args 1046 250 23.90% []
y.compressed 32 9 28.12% []
b.append 307 9 2.931% []
k.replace 65 34 52.30% []
scipy._lib.array_api_compat.common._helpers.array_namespace 33 1 3.030% []
x.denominator 239 61 25.52% []
scipy._lib.array_api_compat.common._aliases._asarray 31 0 0.0% []
numpy.core.numeric.normalize_axis_tuple 487 139 28.54% []
scipy.sparse.linalg._norm.norm 66 0 0.0% []
scipy.sparse.linalg._eigen._svds._iv 47 0 0.0% []
scipy.sparse.linalg._eigen._svds.svds.matmat_XH_X 46 0 0.0% []
scipy.sparse.linalg._special_sparse_arrays.LaplacianNd.toarray 31 0 0.0% []
scipy.sparse.linalg._eigen.lobpcg.lobpcg.lobpcg 360 0 0.0% []
scipy.linalg._basic.solve 61 0 0.0% []
scipy.linalg._basic.det 37 0 0.0% []
scipy.linalg._basic.lstsq 66 1 1.515% []
scipy.linalg._decomp.eig 37 0 0.0% []
scipy.linalg._decomp.eigh 94 1 1.063% []
scipy.linalg._decomp.eig_banded 35 0 0.0% []
scipy.linalg._decomp.eigh_tridiagonal 64 0 0.0% []
scipy.linalg._decomp.cdf2rdf 39 0 0.0% []
scipy.linalg._decomp_lu.lu 56 0 0.0% []
ps.copy 239 32 13.38% []
c.hess 98 30 30.61% []
types.index 55 19 34.54% []
threading.RLock 684 26 3.801% []
scipy.linalg.blas._get_funcs 31 0 0.0% []
scipy.linalg._matfuncs.expm 66 0 0.0% []
scipy.linalg._matfuncs.funm 32 0 0.0% []
scipy.linalg._solvers.solve_continuous_are 47 0 0.0% []
scipy.linalg._solvers.solve_discrete_are 46 0 0.0% []
scipy.linalg._solvers._are_validate_args 46 0 0.0% []
scipy.linalg._decomp_schur.schur 37 0 0.0% []
v.copy 265 64 24.15% []
scipy.linalg._decomp_qr.qr 35 0 0.0% []
scipy.linalg._decomp_qr.qr_multiply 52 0 0.0% []
scipy.linalg._decomp_qz._qz 33 0 0.0% []
format.lower 272 33 12.13% []
numpy.lib.scimath.sqrt 71 33 46.47% []
scipy.linalg._matfuncs_sqrtm._sqrtm_triu 39 0 0.0% []
scipy.linalg._matfuncs_sqrtm.sqrtm 35 0 0.0% []
scipy.sparse.linalg._eigen.arpack.arpack._ArpackParams.__init__ 37 0 0.0% []
scipy.sparse.linalg._eigen.arpack.arpack._SymmetricArpackParams.__init__ 79 0 0.0% []
scipy.sparse.linalg._eigen.arpack.arpack._UnsymmetricArpackParams.__init__ 61 0 0.0% []
scipy.sparse.linalg._eigen.arpack.arpack._UnsymmetricArpackParams.extract 66 0 0.0% []
scipy.sparse.linalg._eigen.arpack.arpack.eigs 63 0 0.0% []
scipy.sparse.linalg._eigen.arpack.arpack.eigsh 84 0 0.0% []
scipy.sparse.linalg._matfuncs._expm 49 0 0.0% []
scipy.linalg._expm_frechet.expm_frechet_algo_64 42 0 0.0% []
numpy.lib.stride_tricks.as_strided.copy 93 23 24.73% []
io.BufferedReader.detach 797 76 9.535% []
scipy.linalg._decomp_cossin.cossin 74 0 0.0% []
scipy.sparse.linalg._dsolve.linsolve.spsolve 74 0 0.0% []
scipy.sparse.linalg._dsolve.linsolve.spsolve_triangular 42 0 0.0% []
scipy.sparse.linalg._isolve.iterative.bicg 44 0 0.0% []
scipy.sparse.linalg._isolve.iterative.bicgstab 52 0 0.0% []
scipy.sparse.linalg._isolve.iterative.cg 32 0 0.0% []
scipy.sparse.linalg._isolve.iterative.cgs 51 0 0.0% []
scipy.sparse.linalg._isolve.iterative.gmres 110 0 0.0% []
scipy.sparse.linalg._isolve.iterative.qmr.id 87 0 0.0% []
scipy._lib.decorator.FunctionMaker.__init__ 45 14 31.11% []
func.__get__ 412 24 5.825% []
scipy.sparse.linalg._isolve.utils.make_system.postprocess 31 0 0.0% []
p.item 163 48 29.44% []
scipy.sparse.linalg._isolve.lsmr.lsmr 180 0 0.0% []
scipy.sparse.linalg._isolve.lsqr.lsqr 184 0 0.0% []
scipy.sparse.linalg._isolve.minres.minres 194 0 0.0% []
scipy.sparse.linalg._isolve.tfqmr.tfqmr 64 0 0.0% []
scipy.sparse.linalg._isolve.lgmres.lgmres 60 0 0.0% []
scipy.sparse.linalg._isolve._gcrotmk._fgmres.rpsolve 58 0 0.0% []
scipy.sparse.linalg._isolve._gcrotmk.gcrotmk 124 0 0.0% []
scipy.sparse.linalg._expm_multiply._expm_multiply_interval 58 0 0.0% []
scipy.sparse._construct.diags_array 31 0 0.0% []
scipy.sparse._construct.kron 36 0 0.0% []
scipy.sparse._construct._block 62 0 0.0% []
scipy.sparse.linalg._onenormest._algorithm_2_2 39 0 0.0% []
scipy.sparse.linalg._onenormest._onenormest_core 71 0 0.0% []
scipy.sparse._bsr._bsr_base.__init__ 66 0 0.0% []
scipy.sparse._bsr._bsr_base.check_format 31 0 0.0% []
scipy.sparse._coo._coo_base.__init__ 59 2 3.389% []
scipy.sparse._dia._dia_base.__init__ 49 0 0.0% []
scipy.sparse._index.IndexMixin.__getitem__ 42 0 0.0% []
scipy.sparse._index.IndexMixin.__setitem__ 39 0 0.0% []
scipy.sparse._lil._lil_base.__init__ 33 0 0.0% []
scipy.io.matlab._mio5.MatFile5Reader.get_variables 36 0 0.0% ['fuzz_io_mio5']
scipy.io.matlab._mio5.to_writeable 37 8 21.62% []
source.items 180 42 23.33% []
dtype.type 176 22 12.5% []
scipy.io._idl._read_data 37 0 0.0% []
scipy.io._idl._read_record 60 0 0.0% []
scipy.io._idl._replace_heap 34 2 5.882% []
scipy.io._idl.readsav 103 0 0.0% []
tempfile.mkdtemp 525 114 21.71% []
records.append 364 54 14.83% []
h.dot 319 16 5.015% []
scipy.io._mmio.MMFile._parse_body 100 0 0.0% []
scipy.io._mmio.MMFile._write 103 0 0.0% []
methods.keys 133 34 25.56% []
signal.setitimer 48 8 16.66% []
logging.warning 923 325 35.21% []
numpy.polynomial.polynomial.polyval 227 57 25.11% []
ks.append 265 83 31.32% []
random.random 378 7 1.851% []
ar.flatten 194 11 5.670% []
pathlib.Path 920 239 25.97% []

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
[] []
_highs [] []
scipy.optimize._hessian_update_strategy [] []
scipy.stats._continuous_distns [] []
scipy.optimize._linesearch [] []
_vq [] []
scipy.linalg.blas [] []
scipy.io.matlab.byteordercodes [] []
...fuzz_io_wavfile ['fuzz_io_wavfile'] []
scipy.sparse._sputils [] []
scipy.optimize._lbfgsb_py [] []
scipy.interpolate.fitpack [] []
OptimizeResult [] []
scipy.ndimage._ni_docstrings [] []
scipy.interpolate._ndgriddata [] []
scipy.interpolate [] []
_sigtools [] []
scipy.ndimage._nd_image [] []
scipy.optimize._linprog_util [] []
scipy.stats._qmvnt [] []
mmap [] []
scipy.signal.fir_filter_design [] []
scipy._lib._elementwise_iterative_method [] []
scipy.optimize._dual_annealing [] []
scipy.misc.doccer [] []
scipy.sparse.linalg.interface [] []
scipy.optimize._trustregion_constr.projections [] []
scipy.signal._sigtools [] []
scipy.optimize._lsq.least_squares [] []
scipy.optimize._lsq.common [] []
scipy.integrate._ivp.radau [] []
_cythonized_array_utils [] []
cffi [] []
scipy.sparse.csgraph._shortest_path [] []
scipy.stats._mannwhitneyu [] []
scipy.sparse.linalg._onenormest [] []
cupy_backends [] []
scipy.integrate.odepack [] []
argparse [] []
scipy.linalg._solve_toeplitz [] []
scipy.signal.waveforms [] []
scipy.linalg._decomp_svd [] []
scipy.optimize._trustregion_exact [] []
scipy._lib.array_api_compat.cupy [] []
scipy._lib.array_api_compat._internal [] []
_mvn [] []
scipy.special._specfun [] []
scipy.sparse.linalg._eigen.lobpcg.lobpcg [] []
scipy.sparse.linalg._matfuncs [] []
scipy.sparse.dia [] []
inspect [] []
scipy.sparse._matrix_io [] []
scipy.optimize._bglu_dense [] []
scipy.stats._mstats_extras [] []
ctypes [] []
scipy.fft._debug_backends [] []
torch [] []
scipy.sparse.linalg._isolve [] []
scipy.special._testutils [] []
scipy.stats._levy_stable.levyst [] []
scipy.stats._resampling [] []
_matfuncs_sqrtm_triu [] []
scipy.optimize._trustregion_constr.equality_constrained_sqp [] []
scipy._lib.array_api_compat.common._helpers [] []
os [] []
scipy.constants.codata [] []
scipy.integrate._quadrature [] []
scipy.fftpack._helper [] []
scipy.signal._wavelets [] []
scipy.optimize._differentiable_functions [] []
scipy.linalg._basic [] []
scipy.optimize._minpack_py [] []
scipy.stats._result_classes [] []
scipy.ndimage._ni_label [] []
scipy.optimize._shgo_lib._complex [] []
contextlib [] []
scipy.optimize._dcsrch [] []
scipy.integrate._quad_vec [] []
scipy.optimize._milp [] []
multiprocessing [] []
mpmath [] []
scipy.linalg._decomp_ldl [] []
scipy._lib._ccallback_c [] []
scipy.io.netcdf [] []
scipy.special.add_newdocs [] []
scipy.ndimage._morphology [] []
scipy.stats.mstats_extras [] []
scipy.ndimage._fourier [] []
scipy.io.matlab.miobase [] []
scipy.optimize._optimize [] []
scipy.stats._qmc [] []
scipy.linalg._sketches [] []
scipy.optimize._highs._highs_wrapper [] []
scipy.constants.constants [] []
scipy.datasets._utils [] []
convolve [] []
_ni_label [] []
scipy.integrate.dop [] []
scipy.optimize._linprog_highs [] []
scipy.optimize._trustregion_dogleg [] []
scipy.spatial.distance [] []
scipy.linalg._decomp_polar [] []
interpnd [] []
scipy.stats._ksstats [] []
scipy.sparse.linalg._dsolve.linsolve [] []
scipy.interpolate._bsplines [] []
_ufuncs [] []
scipy.optimize._trustregion_constr.minimize_trustregion_constr [] []
scipy._lib._util [] []
scipy.spatial._distance_pybind [] []
scipy.linalg._matfuncs [] []
scipy.stats.morestats [] []
signal [] []
scipy.sparse.linalg._isolve.utils [] []
scipy.fft._fftlog [] []
scipy.stats._mstats_basic [] []
scipy.sparse._csc [] []
scipy.sparse.lil [] []
bz2 [] []
scipy._lib.array_api_compat.numpy._typing [] []
pytest [] []
scipy.signal._spectral_py [] []
pathlib [] []
scipy._lib.array_api_compat.cupy._aliases [] []
...fuzz_io_mio5 ['fuzz_io_mio5'] []
scipy.spatial._plotutils [] []
scipy.special._precompute.wright_bessel [] []
scipy.constants._codata [] []
scipy.special._orthogonal [] []
scipy.interpolate.ndgriddata [] []
scipy.integrate.vode [] []
scipy.stats._unuran.unuran_wrapper [] []
scipy._lib.array_api_compat.torch.linalg [] []
scipy.signal.windows._windows [] []
scipy.odr._odrpack [] []
_mio5_utils [] []
scipy.linalg [] []
scipy.spatial._distance_wrap [] []
scipy._lib.array_api_compat.numpy._aliases [] []
scipy.optimize._highs._highs_constants [] []
scipy.signal._max_len_seq_inner [] []
scipy.linalg._matfuncs_sqrtm_triu [] []
scipy.special._comb [] []
scipy.io.matlab.mio5_utils [] []
scipy.sparse.linalg._norm [] []
scipy.optimize.cython_optimize [] []
scipy.linalg._special_matrices [] []
scipy.fft._fftlog_backend [] []
scipy.stats._crosstab [] []
scipy.stats._rcont.rcont [] []
scipy.special._precompute.wright_bessel_data [] []
scipy.stats._unuran [] []
scipy.linalg._interpolative_backend [] []
scipy.stats._page_trend_test [] []
scipy.integrate._ivp.rk [] []
scipy.sparse._spfuncs [] []
scipy.stats._sobol [] []
scipy.signal._max_len_seq [] []
_superlu [] []
scipy.special._precompute.lambertw [] []
scipy._lib._fpumode [] []
scipy.sparse.linalg._propack._spropack [] []
sksparse [] []
scipy.special._precompute [] []
scipy.sparse.linalg.dsolve [] []
scipy.optimize._bracket [] []
scipy.linalg._decomp [] []
keyword [] []
scipy.optimize._root_scalar [] []
scipy.stats._warnings_errors [] []
scipy.linalg._procrustes [] []
scipy.signal.filter_design [] []
scipy.signal._arraytools [] []
scipy.linalg.decomp_lu [] []
scipy.sparse._extract [] []
scipy.interpolate._rgi_cython [] []
scipy._lib._pep440 [] []
scipy.optimize._trustregion_ncg [] []
scipy.io.matlab._mio5_utils [] []
scipy.signal.lti_conversion [] []
scipy.sparse.linalg._propack._dpropack [] []
scipy.odr.__odrpack [] []
scipy.optimize.optimize [] []
_mio_utils [] []
scipy.optimize [] []
scipy.spatial [] []
_hierarchy [] []
scipy.interpolate._rbfinterp [] []
scipy.io.matlab._mio5_params [] []
scipy.spatial.ckdtree [] []
scipy.io.matlab.streams [] []
scipy.sparse.csgraph._reordering [] []
cupy [] []
scipy.ndimage._filters [] []
scipy.special._precompute.gammainc_asy [] []
scipy.sparse._construct [] []
types [] []
scipy.spatial.transform._rotation [] []
scipy.stats._boost.skewnorm_ufunc [] []
scipy.integrate._ivp [] []
scipy.stats.mstats_basic [] []
scipy.stats.mvn [] []
scipy.signal._signaltools [] []
cmath [] []
scipy.optimize._lsq.givens_elimination [] []
scipy._lib.array_api_compat [] []
scipy.optimize.tnc [] []
scipy.io.mmio [] []
scipy.optimize._chandrupatla [] []
scipy.fft._pocketfft.realtransforms [] []
scipy.cluster._optimal_leaf_ordering [] []
scipy.signal.wavelets [] []
scipy.optimize._lsq.dogbox [] []
_stats_pythran [] []
scipy.interpolate._fitpack2 [] []
scipy.linalg.lapack [] []
scipy.signal._spline [] []
scipy.special._precompute.gammainc_data [] []
scipy.linalg._matfuncs_expm [] []
scipy.linalg._decomp_cossin [] []
scipy.sparse.csgraph._laplacian [] []
scipy.signal._fir_filter_design [] []
scipy.sparse.linalg._eigen._svds_doc [] []
scipy.signal._waveforms [] []
scipy.linalg.decomp_cholesky [] []
scipy._lib.array_api_compat.numpy.linalg [] []
scipy._lib.uarray [] []
scipy.integrate._tanhsinh [] []
scipy.fft._pocketfft.basic [] []
scipy._lib.array_api_compat.common._typing [] []
scipy.optimize._trustregion_constr.report [] []
scipy.optimize._trustregion_constr.tr_interior_point [] []
scipy.odr [] []
scipy.sparse.linalg._eigen._svds [] []
scipy.signal._upfirdn_apply [] []
pickle [] []
scipy.sparse.linalg._isolve.lsmr [] []
_rgi_cython [] []
scipy.sparse.linalg._eigen [] []
scipy._lib._ccallback [] []
scipy.sparse._matrix [] []
abc [] []
scipy._lib._array_api [] []
scipy.stats._axis_nan_policy [] []
scipy.linalg._testutils [] []
scipy.sparse._dok [] []
scipy.optimize._qap [] []
scipy.datasets._download_all [] []
scipy.linalg.special_matrices [] []
scipy.stats._boost.hypergeom_ufunc [] []
scipy.stats._mvn [] []
scipy.signal.windows.windows [] []
scipy.sparse.spfuncs [] []
scipy.sparse._sparsetools [] []
scipy.sparse._coo [] []
scipy.sparse._lil [] []
scipy.optimize._nnls [] []
_minpack [] []
scipy [] []
scipy.sparse._csr [] []
scipy.interpolate.polyint [] []
timeit [] []
scipy.stats._boost.ncf_ufunc [] []
scipy.sparse.linalg._eigen.arpack [] []
scipy.conftest [] []
scipy.stats._multivariate [] []
eigsh [] []
copy [] []
scipy.sparse._data [] []
scipy.stats._boost.nct_ufunc [] []
scipy._lib.array_api_compat.numpy [] []
scipy.ndimage.interpolation [] []
scipy.special [] []
_stats [] []
scipy.stats._levy_stable [] []
_uarray [] []
_sparsetools [] []
scipy.special.sf_error [] []
zlib [] []
scipy.cluster.hierarchy [] []
scipy.io.matlab.mio5 [] []
givens_elimination [] []
scipy.io.matlab._mio_utils [] []
_hausdorff [] []
_peak_finding_utils [] []
_fmm_core [] []
_fitpack [] []
scipy.optimize._isotonic [] []
_distance_wrap [] []
scipy.sparse._dia [] []
_min_spanning_tree [] []
_decomp_lu_cython [] []
scipy.sparse.linalg._expm_multiply [] []
scipy.stats._relative_risk [] []
scipy.interpolate._fitpack [] []
scipy.special._ufuncs [] []
scipy.sparse.linalg._isolve.minres [] []
scipy.sparse.linalg._isolve.tfqmr [] []
scipy.fftpack.realtransforms [] []
scipy.__config__ [] []
scipy.stats._rcont [] []
scipy.stats._biasedurn [] []
operator [] []
scipy.ndimage.measurements [] []
dfitpack [] []
scipy.sparse.compressed [] []
_csparsetools [] []
scipy.integrate._quadpack_py [] []
scipy.special._ellip_harm [] []
scipy.ndimage._ni_support [] []
scipy.sparse.linalg._dsolve [] []
itertools [] []
_direct [] []
numpy [] []
scipy.sparse.linalg._isolve.iterative [] []
scipy.optimize._linprog_rs [] []
scipy.sparse.csgraph._tools [] []
scipy.sparse.linalg._interface [] []
scipy.sparse.linalg.isolve [] []
scipy.integrate [] []
scipy.sparse.csgraph._validation [] []
scipy.interpolate._ppoly [] []
_lbfgsb [] []
hypothesis [] []
scipy._lib.array_api_compat.common._aliases [] []
_zeros [] []
scipy.optimize._tstutils [] []
scipy.sparse.linalg._isolve.lgmres [] []
scipy.stats._entropy [] []
scipy.special._ellip_harm_2 [] []
scipy.io.idl [] []
scipy.odr.odrpack [] []
_specfun [] []
importlib [] []
scipy.fftpack.convolve [] []
scipy.spatial._spherical_voronoi [] []
scipy.linalg._matfuncs_sqrtm [] []
scipy.interpolate._ndbspline [] []
scipy.version [] []
scipy.sparse.coo [] []
scipy.io._netcdf [] []
scipy.spatial._geometric_slerp [] []
gc [] []
scipy.fftpack._basic [] []
scipy.optimize._trustregion_constr.canonical_constraint [] []
scipy.integrate._bvp [] []
scipy.io._mmio [] []
_matfuncs_expm [] []
csv [] []
scipy.io.matlab [] []
json [] []
yaml [] []
pooch [] []
scipy.optimize._minimize [] []
_ansari_swilk_statistics [] []
scipy.stats._survival [] []
threading [] []
scipy.sparse._index [] []
scipy.fft._pocketfft [] []
_unuran [] []
scipy.linalg.decomp_qr [] []
scipy.stats._boost.ncx2_ufunc [] []
scipy.sparse.linalg._propack._zpropack [] []
scipy.optimize.minpack [] []
scipy.stats._morestats [] []
scipy.stats._hypotests [] []
scipy.fftpack._pseudo_diffs [] []
scipy.optimize._trustregion_constr.qp_subproblem [] []
datetime [] []
sympy [] []
scipy.stats._distn_infrastructure [] []
scipy.sparse.linalg.eigen [] []
scipy.stats [] []
scipy.interpolate.fitpack2 [] []
scipy.fft._basic_backend [] []
sys [] []
weakref [] []
scipy.signal._sosfilt [] []
scipy.spatial._voronoi [] []
scipy.io.wavfile ['fuzz_io_wavfile'] []
scipy.stats._stats_py [] []
scipy.sparse.csgraph._traversal [] []
scipy.optimize._trustregion_krylov [] []
scipy.optimize._minpack [] []
dataclasses [] []
scipy.integrate._ivp.dop853_coefficients [] []
scipy.sparse.linalg._eigen.lobpcg [] []
scipy._lib [] []
scipy.interpolate._rgi [] []
scipy.stats._common [] []
scipy.stats._stats [] []
scipy.optimize._trustregion [] []
scipy.special._precompute.zetac [] []
scipy.io.matlab._mio5 ['fuzz_io_mio5'] []
scipy.stats._multicomp [] []
scipy.cluster [] []
scipy.sparse._csparsetools [] []
decimal [] []
scipy.optimize._shgo_lib [] []
linear_sum_assignment [] []
scipy.signal._bsplines [] []
scipy._lib._uarray [] []
scipy.special._logsumexp [] []
scipy.optimize._minpack2 [] []
scipy.optimize._slsqp_py [] []
scipy.optimize._lsq [] []
scipy.signal.signaltools [] []
scipy.signal._peak_finding [] []
_ckdtree [] []
_quadpack [] []
scipy.stats._boost.nbinom_ufunc [] []
_upfirdn_apply [] []
scipy.linalg.decomp_schur [] []
scipy.interpolate.rbf [] []
scipy.special._mptestutils [] []
scipy.optimize._nonlin [] []
scipy.signal.ltisys [] []
scipy.optimize._linprog [] []
scipy.fft._helper [] []
_rotation [] []
scipy.integrate._ivp.base [] []
scipy.signal._czt [] []
scipy.stats._qmc_cy [] []
scipy.integrate._dop [] []
scipy.optimize._pava_pybind [] []
scipy.linalg._flapack [] []
scipy.io.matlab.mio_utils [] []
io [] []
_ccallback_c [] []
scipy.fft._basic [] []
scipy.optimize.nonlin [] []
scipy.special._precompute.struve_convergence [] []
scipy.ndimage [] []
scipy.integrate._quadpack [] []
platformdirs [] []
scipy.interpolate.interpolate [] []
scipy.stats._generate_pyx [] []
scipy.special.orthogonal [] []
_solve_toeplitz [] []
scipy.linalg.decomp_svd [] []
scipy.stats._tukeylambda_stats [] []
scipy.sparse [] []
scipy.cluster.vq [] []
scipy.stats._ansari_swilk_statistics [] []
scipy.sparse.linalg [] []
scipy.stats._bws_test [] []
scipy.stats.sampling [] []
scipy.stats._boost.invgauss_ufunc [] []
scipy.fft._backend [] []
scipy.io.matlab._streams [] []
scipy.sparse._compressed [] []
_ellip_harm_2 [] []
scipy.special._lambertw [] []
_optimal_leaf_ordering [] []
scipy.interpolate._cubic [] []
scipy.optimize._slsqp [] []
pydoc [] []
_odepack [] []
re [] []
_bglu_dense [] []
scipy.linalg.matfuncs [] []
_max_len_seq_inner [] []
scipy.fftpack.basic [] []
_biasedurn [] []
scipy.fft._pocketfft.pypocketfft [] []
scipy.sparse.linalg._eigen.arpack.arpack [] []
scipy.sparse.linalg._propack._cpropack [] []
scipy.integrate.quadpack [] []
scipy._lib.array_api_compat.common._linalg [] []
scipy.special._support_alternative_backends [] []
scipy.ndimage.morphology [] []
scipy.optimize._lsq.trf [] []
random [] []
scipy.sparse.construct [] []
scipy.signal._lti_conversion [] []
scipy.io.matlab.mio [] []
scipy.cluster._hierarchy [] []
scipy.optimize._zeros_py [] []
_streams [] []
scipy.optimize._trustregion_constr [] []
scipy.special.spfun_stats [] []
scipy.io.arff.arffread [] []
scipy._lib.deprecation [] []
scipy.fftpack.pseudo_diffs [] []
scipy._lib._docscrape [] []
scipy.interpolate.interpnd [] []
scipy.optimize.lbfgsb [] []
shutil [] []
scipy.linalg._matfuncs_inv_ssq [] []
scipy.spatial._ckdtree [] []
scipy.spatial.kdtree [] []
scipy.stats._binomtest [] []
scipy._lib.array_api_compat.cupy.linalg [] []
_voronoi [] []
scipy.sparse.linalg.matfuncs [] []
scipy.linalg._decomp_lu [] []
scipy.optimize._spectral [] []
_sosfilt [] []
platform [] []
scipy.misc._common [] []
scipy.special._basic [] []
scipy.optimize._highs [] []
scipy.signal._spectral [] []
scipy.special.basic [] []
scipy.io._harwell_boeing._fortran_format_parser [] []
scipy.special._spherical_bessel [] []
scipy.optimize._linprog_doc [] []
scipy.special._spfun_stats [] []
scipy.linalg._fblas [] []
scipy.stats.kde [] []
scipy.datasets._fetchers [] []
scipy.spatial.transform._rotation_spline [] []
scipy.optimize._numdiff [] []
scipy.stats._rvs_sampling [] []
scipy.sparse.base [] []
scipy.integrate._ivp.ivp [] []
scipy.linalg.decomp [] []
scipy.io.arff [] []
scipy.integrate._odepack_py [] []
scipy.optimize._lsq.lsq_linear [] []
scipy.optimize._remove_redundancy [] []
scipy._lib._disjoint_set [] []
scipy.integrate._vode [] []
scipy.stats._binned_statistic [] []
scipy.stats.stats [] []
scipy.optimize._direct_py [] []
scipy.sparse.dok [] []
scipy.io.matlab._byteordercodes [] []
scipy.optimize._moduleTNC [] []
scipy.fftpack._realtransforms [] []
scipy.stats.distributions [] []
builtins [] []
scipy.optimize.moduleTNC [] []
scipy.stats._distr_params [] []
scipy.stats._censored_data [] []
scipy.io._fast_matrix_market._fmm_core [] []
math [] []
scipy.datasets._registry [] []
scipy.sparse.linalg._dsolve._superlu [] []
scipy.sparse._bsr [] []
scipy.linalg._interpolative [] []
scipy.sparse.linalg._dsolve._add_newdocs [] []
scipy.integrate._ivp.common [] []
scipy.stats._boost.beta_ufunc [] []
bisect [] []
scipy.odr._add_newdocs [] []
scipy.optimize._lsq.bvls [] []
textwrap [] []
scipy.optimize._root [] []
scipy.interpolate._rbfinterp_pythran [] []
scipy.optimize._cobyla [] []
scipy.special._sf_error [] []
scipy.interpolate._polyint [] []
scipy._lib._gcutils [] []
scipy.special._add_newdocs [] []
scipy.stats.qmc [] []
collections [] []
scipy._lib._threadsafety [] []
_bspl [] []
scipy.sparse.csgraph._matching [] []
scipy.interpolate.dfitpack [] []
scipy.constants [] []
scipy.sparse._base [] []
scipy.optimize._linprog_ip [] []
scipy.fftpack.helper [] []
scipy.stats._fit [] []
scipy.stats._discrete_distns [] []
scipy._lib.array_api_compat.torch._aliases [] []
scipy.sparse.sparsetools [] []
heapq [] []
scipy._lib._testutils [] []
functools [] []
scipy.linalg._decomp_qr [] []
scipy.stats._stats_pythran [] []
_trlib [] []
scipy.special._precompute.loggamma [] []
scipy.ndimage._measurements [] []
scipy.signal._peak_finding_utils [] []
scipy.sparse.csgraph._flow [] []
scipy.optimize._tnc [] []
scipy.stats._boost.binom_ufunc [] []
scipy.optimize._lsap [] []
psutil [] []
scipy.io.matlab.mio4 [] []
scipy.linalg._decomp_schur [] []
scipy.spatial._hausdorff [] []
scipy.optimize._zeros [] []
scipy.sparse.csr [] []
scipy.io.arff._arffread [] []
scipy.optimize._group_columns [] []
threadpoolctl [] []
scipy.signal.spectral [] []
scipy.io._harwell_boeing [] []
scipy.io.matlab._mio4 [] []
scipy.optimize.minpack2 [] []
scipy.io [] []
scipy.integrate._ivp.bdf [] []
scipy.io.harwell_boeing [] []
scipy.stats._constants [] []
scipy.integrate._ivp.lsoda [] []
scipy.misc [] []
_comb [] []
scipy.special.specfun [] []
scipy.io.matlab.mio5_params [] []
scipy.stats.contingency [] []
scipy.optimize._differentialevolution [] []
PPoly [] []
struct [] []
scipy.stats._variation [] []
scipy.optimize._basinhopping [] []
scipy.spatial.qhull [] []
scipy.signal._savitzky_golay [] []
scipy.sparse.linalg._isolve._gcrotmk [] []
scipy.linalg._decomp_cholesky [] []
scipy.signal.windows [] []
scipy.interpolate._interpnd_info [] []
scipy.fftpack [] []
matplotlib [] []
scipy.stats.mstats [] []
sysconfig [] []
scipy.integrate._lsoda [] []
scipy._lib.array_api_compat.torch [] []
_qmc_cy [] []
scipy.fft [] []
levyst [] []
scipy.special._precompute.expn_asy [] []
scipy.stats._boost [] []
scipy.stats._sensitivity_analysis [] []
scipy.ndimage.filters [] []
scipy._lib._uarray._backend [] []
scipy.odr._models [] []
scipy.sparse.bsr [] []
scipy.interpolate._fitpack_impl [] []
scipy.sparse.linalg._eigen.arpack._arpack [] []
scipy._lib.decorator [] []
_spline [] []
scipy.special._precompute.utils [] []
logging [] []
typing [] []
scipy.ndimage.fourier [] []
scikits [] []
scipy.optimize._shgo_lib._vertex [] []
_nd_image [] []
_rbfinterp_pythran [] []
scipy._lib._bunch [] []
scipy.sparse.data [] []
scipy.spatial._kdtree [] []
scipy.sparse.csgraph [] []
scipy.stats.biasedurn [] []
subprocess [] []
copyreg [] []
scipy.optimize._trlib._trlib [] []
scipy.fft._realtransforms_backend [] []
scipy.linalg._solvers [] []
scipy.spatial.transform.rotation [] []
scipy.io._fast_matrix_market [] []
scipy.optimize._direct [] []
scipy.cluster._vq [] []
scipy.optimize.zeros [] []
scipy.ndimage._interpolation [] []
scipy.optimize.cobyla [] []
scipy.spatial._qhull [] []
scipy.signal.spline [] []
scipy.io._fortran [] []
atheris [] []
scipy.sparse.sputils [] []
scipy._lib.array_api_compat.cupy._typing [] []
scipy.signal._ltisys [] []
scipy._distributor_init [] []
gzip [] []
scipy.optimize._cobyla_py [] []
time [] []
scipy.linalg._misc [] []
_registry [] []
scipy.spatial.transform [] []
scipy.interpolate._bspl [] []
scipy.linalg._decomp_qz [] []
scipy.optimize._linprog_simplex [] []
scipy.signal._upfirdn [] []
scipy.integrate.lsoda [] []
scipy.spatial.transform._rotation_groups [] []
_group_columns [] []
scipy._lib.array_api_compat.common [] []
scipy.sparse.linalg._svdp [] []
sparse [] []
scipy.signal._short_time_fft [] []
scipy.linalg.basic [] []
scipy.interpolate._rbf [] []
scipy.io._idl [] []
scipy.sparse.linalg._special_sparse_arrays [] []
scipy.stats._stats_mstats_common [] []
scipy.fft._pocketfft.helper [] []
pypocketfft [] []
scipy.stats._sampling [] []
_pava_pybind [] []
scipy._lib._tmpdirs [] []
warnings [] []
scipy.sparse.csgraph._min_spanning_tree [] []
scipy.optimize._lbfgsb [] []
scipy.linalg._decomp_lu_cython [] []
scipy.io.matlab._miobase ['fuzz_io_mio5'] []
scipy.constants._constants [] []
scipy.signal._filter_design [] []
scipy._lib._uarray._uarray [] []
scipy.integrate._ode [] []
scipy.special._precompute.wrightomega [] []
_ppoly [] []
scipy.linalg.interpolative [] []
scipy.signal [] []
scipy.optimize._shgo [] []
scipy.special._precompute.cosine_cdf [] []
scipy.optimize._lsq.trf_linear [] []
scipy.fft._realtransforms [] []
scipy.misc.common [] []
scipy.stats._covariance [] []
scipy.linalg.misc [] []
scipy.linalg._decomp_update [] []
_sobol [] []
scipy.io.matlab._mio [] []
scipy._lib._finite_differences [] []
scipy.linalg._expm_frechet [] []
scipy.optimize._differentiate [] []
scipy.stats._kde [] []
scipy.optimize._constraints [] []
scipy.linalg._cythonized_array_utils [] []
scipy.interpolate._interpolate [] []
scipy.io._harwell_boeing.hb [] []
scipy.integrate._odepack [] []
scipy.datasets [] []
scipy.optimize.slsqp [] []
scipy.interpolate._fitpack_py [] []
scipy.interpolate._pade [] []
tempfile [] []
scipy.optimize._trlib [] []
scipy._lib.doccer [] []
scipy.sparse.extract [] []
scipy.sparse.linalg._isolve.lsqr [] []
scipy.spatial._procrustes [] []
[] []
scipy.odr.models [] []
scipy.optimize.linesearch [] []
scipy.signal.bsplines [] []
scipy.stats._odds_ratio [] []
scipy.sparse.csc [] []

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_io_wavfile fuzzerLogFile-fuzz_io_wavfile.data fuzzerLogFile-fuzz_io_wavfile.data.yaml all_cov.json
fuzz_io_mio5 fuzzerLogFile-fuzz_io_mio5.data fuzzerLogFile-fuzz_io_mio5.data.yaml all_cov.json