FuzzBench: 2024-03-14-libafl report

experiment summary

We show two different aggregate (cross-benchmark) rankings of fuzzers. The first is based on the average of per-benchmarks scores, where the score represents the percentage of the highest reached median code-coverage on a given benchmark (higher value is better). The second ranking shows the average rank of fuzzers, after we rank them on each benchmark according to their median reached code-covereges (lower value is better).

By avg. score

	average normalized score
fuzzer
libafl	98.27
aflplusplus	97.38
honggfuzz	95.18
libfuzzer	93.95
libafl_pre_012_0	93.65
libafl_pre_012_1	93.29
libafl_pre_012_2	93.03
libafl_pre_012_3	92.72
aflsmart	85.61
mopt	85.48
afl	84.05
eclipser	83.73
aflfast	82.92
fairfuzz	80.01
centipede	68.57

By avg. rank

	average rank
fuzzer
aflplusplus	3.04
libafl	5.04
libafl_pre_012_0	5.57
libafl_pre_012_1	6.17
libfuzzer	6.57
libafl_pre_012_2	7.04
libafl_pre_012_3	7.13
honggfuzz	7.22
aflsmart	7.52
eclipser	8.65
afl	8.91
mopt	9.00
aflfast	11.22
fairfuzz	11.26
centipede	11.65

Critical difference diagram

The diagram visualizes the average rank of fuzzers (second ranking above) while showing the significance of the differences as well. What is considered a "critical difference" (CD) is based on the Friedman/Nemenyi post-hoc test. See more in the documentation.

Note: If a fuzzer does not support all benchmarks, its ranking as shown in this diagram can be lower than it should be. So please check the list of supported benchmarks for the fuzzer(s) of your interest. The list could be specified in the fuzzer's README.md like this.

Median relative code-coverages on each benchmark

Note: The relative coverage summary table shows the median relative performance of each fuzzer to the experiment maximum. Thus the highest relative performance may not be 100%.
trial_relative_coverage = trial_coverage / experiment_max_coverage

	libafl	libafl_pre_012_0	aflplusplus	libafl_pre_012_1	libafl_pre_012_2	libafl_pre_012_3	honggfuzz	libfuzzer	eclipser	aflsmart	mopt	afl	aflfast	centipede	fairfuzz
FuzzerMedian	96.00	97.00	98.00	96.50	96.00	96.50	97.00	95.00	94.00	95.00	94.00	94.00	93.00	90.00	87.00
FuzzerMean	94.65	94.23	93.87	93.77	93.55	93.18	91.78	90.57	88.29	83.00	82.83	81.52	80.48	79.63	77.52
bloaty_fuzz_target	99.00	97.00	98.00	97.00	97.00	87.00	95.00	89.00	94.00	95.00	97.00	94.00	93.00	nan	80.00
curl_curl_fuzzer_http	97.00	98.00	99.00	99.00	99.00	98.00	98.00	91.00	94.00	94.00	94.00	94.00	93.00	nan	85.00
freetype2_ftfuzzer	91.00	90.00	88.00	90.00	88.00	89.00	89.00	77.00	74.00	67.00	66.00	66.00	65.00	57.00	62.00
harfbuzz_hb-shape-fuzzer	99.00	99.00	98.00	97.00	94.00	97.00	96.00	95.00	96.00	96.00	97.00	96.00	95.00	nan	84.00
jsoncpp_jsoncpp_fuzzer	98.00	98.00	99.00	98.00	98.00	98.00	99.00	100.00	98.00	98.00	98.00	98.00	98.00	98.00	98.00
lcms_cms_transform_fuzzer	91.00	94.00	88.00	92.00	89.00	90.00	79.00	84.00	73.00	68.00	69.00	40.00	28.00	37.00	53.00
libjpeg-turbo_libjpeg_turbo_fuzzer	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	nan	99.00	99.00	99.00	99.00	96.00	99.00
libpcap_fuzz_both	82.00	82.00	86.00	79.00	82.00	79.00	80.00	75.00	72.00	1.00	1.00	1.00	1.00	81.00	1.00
libpng_libpng_read_fuzzer	95.00	95.00	95.00	95.00	95.00	95.00	96.00	96.00	95.00	95.00	94.00	95.00	94.00	96.00	94.00
libxml2_xml	99.00	99.00	99.00	85.00	87.00	98.00	99.00	97.00	97.00	97.00	97.00	97.00	97.00	93.00	89.00
libxslt_xpath	96.00	96.00	98.00	96.00	96.00	96.00	97.00	92.00	95.00	95.00	93.00	94.00	94.00	94.00	95.00
mbedtls_fuzz_dtlsclient	86.00	71.00	72.00	84.00	80.00	87.00	70.00	70.00	70.00	70.00	70.00	70.00	68.00	69.00	73.00
openh264_decoder_fuzzer	98.00	98.00	99.00	97.00	98.00	98.00	98.00	98.00	98.00	99.00	99.00	99.00	99.00	nan	90.00
openssl_x509	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00	99.00
openthread_ot-ip6-send-fuzzer	85.00	85.00	73.00	85.00	85.00	85.00	73.00	73.00	72.00	69.00	70.00	69.00	69.00	69.00	66.00
proj4_proj_crs_to_crs_fuzzer	90.00	nan	89.00	nan	nan	nan	97.00	93.00	60.00	10.00	9.00	9.00	9.00	10.00	10.00
re2_fuzzer	98.00	98.00	99.00	98.00	98.00	98.00	98.00	99.00	99.00	99.00	98.00	99.00	99.00	95.00	99.00
sqlite3_ossfuzz	91.00	90.00	96.00	89.00	89.00	82.00	69.00	79.00	91.00	92.00	91.00	92.00	91.00	62.00	58.00
stb_stbi_read_fuzzer	96.00	96.00	93.00	96.00	96.00	87.00	93.00	88.00	92.00	88.00	87.00	88.00	87.00	86.00	87.00
systemd_fuzz-link-parser	99.00	99.00	100.00	99.00	99.00	99.00	97.00	95.00	91.00	92.00	91.00	91.00	91.00	98.00	87.00
vorbis_decode_fuzzer	98.00	98.00	99.00	98.00	98.00	98.00	98.00	99.00	98.00	98.00	98.00	98.00	98.00	90.00	97.00
woff2_convert_woff2ttf_fuzzer	96.00	97.00	96.00	97.00	97.00	97.00	95.00	96.00	nan	92.00	91.00	91.00	90.00	88.00	81.00
zlib_zlib_uncompress_fuzzer	95.00	95.00	97.00	94.00	95.00	94.00	97.00	99.00	96.00	96.00	97.00	96.00	94.00	95.00	96.00

Fuzzers are sorted by "FuzzerMean" (average median relative coverage), highest on the left.
Green background = highest relative median coverage.
Blue gradient background = greater than 95% relative median coverage.

bloaty_fuzz_target summary

Ranking by median reached code coverage

Mean code coverage growth over time

* The error bands show the 95% confidence interval around the mean code coverage.

The following fuzzers do not have enough samples: aflsmart, mopt, libafl_pre_012_2, libafl_pre_012_1, eclipser, libafl_pre_012_0, libafl_pre_012_3, aflplusplus.

Sample statistics and statistical significance (code coverage)

Code coverage sample statistics

		count	mean	std	min	25%	median	75%	max
fuzzer	time
libafl	82800	19.0	6373.315789	64.294507	6225.0	6334.00	6392.0	6418.00	6451.0
aflplusplus	82800	10.0	6320.300000	94.224378	6148.0	6249.75	6352.5	6381.50	6437.0
libafl_pre_012_0	82800	11.0	6330.363636	62.450417	6255.0	6283.00	6317.0	6379.00	6436.0
libafl_pre_012_1	82800	12.0	6296.583333	52.046235	6212.0	6268.75	6302.5	6332.00	6367.0
libafl_pre_012_2	82800	13.0	6279.076923	35.792135	6229.0	6256.00	6276.0	6297.00	6359.0
mopt	82800	14.0	6242.357143	84.158831	6046.0	6225.75	6267.5	6291.00	6350.0
aflsmart	82800	15.0	6143.400000	156.758139	5816.0	6031.00	6149.0	6241.50	6401.0
honggfuzz	82800	18.0	6094.111111	174.869662	5884.0	5918.25	6142.0	6248.00	6329.0
afl	82800	18.0	6101.944444	119.949240	5889.0	6070.75	6098.5	6141.75	6338.0
eclipser	82800	11.0	6053.181818	68.930136	5914.0	6022.50	6078.0	6095.50	6135.0
aflfast	82800	17.0	6028.411765	77.961576	5893.0	5960.00	6035.0	6065.00	6185.0
libfuzzer	82800	20.0	5795.800000	110.501536	5592.0	5718.75	5781.0	5869.50	5994.0
libafl_pre_012_3	82800	11.0	5571.090909	324.540122	4935.0	5347.00	5631.0	5766.50	6135.0
fairfuzz	82800	16.0	5189.937500	67.159977	5111.0	5135.25	5170.0	5226.00	5323.0

Vargha-Delaney A12 measure

The table summarizes the A12 values from the pairwise Vargha-Delaney A measure of effect size. Green cells indicate the probability the fuzzer in the row will outperform the fuzzer in the column.

Mann-Whitney U test

The table summarizes the p values of pairwise Mann-Whitney U tests. Green cells indicate that the reached coverage distribution of a given fuzzer pair is significantly different.

Unique code coverage plots

Ranking by unique code branches covered
Each bar shows the total number of code branches found by a given fuzzer. The colored area shows the number of unique code branches (i.e., branches that were not covered by any other fuzzers).

Pairwise unique code coverage
Each cell represents the number of code branches covered by the fuzzer of the column but not by the fuzzer of the row

Code coverage reports for each fuzzer on this benchmark

afl aflfast aflplusplus aflsmart centipede eclipser fairfuzz honggfuzz libafl libafl_pre_012_0 libafl_pre_012_1 libafl_pre_012_2 libafl_pre_012_3 libfuzzer mopt