{"id":"W2100883222","doi":"10.1109/compsac.2009.191","title":"Automatic Testing of Program Security Vulnerabilities","year":2009,"lang":"en","type":"article","venue":"","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Security testing; Computer science; Fuzz testing; Application security; SQL injection; Computer security; Secure coding; Vulnerability (computing); Security bug; Automation; Manual testing; Software security assurance; Software engineering; Information security; Security service; Security information and event management; Cloud computing security; Software; World Wide Web; Engineering; Software development","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005043312,0.0001318461,0.000217809,0.00009045335,0.00008534428,0.0001096942,0.0007945206,0.00005111234,0.00005560227],"category_scores_gemma":[0.0003513043,0.0001173564,0.00005943163,0.0006109451,0.0001037828,0.0004676407,0.0001060327,0.0001251932,0.00002177857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003190531,"about_ca_system_score_gemma":0.00008406863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000609872,"about_ca_topic_score_gemma":0.000004135549,"domain_scores_codex":[0.998598,0.00008765623,0.0004209628,0.0003199358,0.0003230607,0.0002503412],"domain_scores_gemma":[0.9983452,0.0004187422,0.0001243461,0.0008035655,0.0002325152,0.00007564192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[7.674233e-7,0.0003825949,0.0006068921,0.00006835853,0.000005469223,7.284267e-7,0.002650208,0.00003276835,0.0006238609,0.6423258,0.0005235164,0.3527791],"study_design_scores_gemma":[0.0002709405,0.0005459916,0.007616168,0.00003742247,0.000005172579,0.00001874322,0.0003415016,0.4771083,0.01995511,0.4915022,0.002276024,0.0003223772],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8875723,0.00009028506,0.04934667,0.002427669,0.00008827577,0.0008871977,0.000002395781,0.002625014,0.05696023],"genre_scores_gemma":[0.7645614,5.420067e-7,0.2351403,0.0001602646,0.00002178517,0.00004238126,6.546314e-7,0.000003170937,0.00006946473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4770755,"threshold_uncertainty_score":0.4785655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02609552071501577,"score_gpt":0.290460923118325,"score_spread":0.2643654024033092,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}