{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002292713,0.0006399192,0.0004407886,0.003461095,0.0003928615,0.0008956203,0.0009871832,0.0008286676,0.001602387],"category_scores_gemma":[0.01773039,0.0003323371,0.0006585694,0.00130172,0.0007207806,0.001638663,0.0008821271,0.0005261713,0.0004587369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004822166,"about_ca_system_score_gemma":0.0009948977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00127166,"about_ca_topic_score_gemma":0.001790116,"domain_scores_codex":[0.9962373,0.001459825,0.0002377858,0.0003830651,0.00147656,0.0002054712],"domain_scores_gemma":[0.9712467,0.02143763,0.002389375,0.002618381,0.002103202,0.0002048113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005262028,0.000779752,0.1068616,0.0009246503,0.0002419336,0.001038566,0.001799948,0.04418221,0.1151132,0.009436004,0.003809975,0.715286],"study_design_scores_gemma":[0.0001534747,0.001391328,0.08243256,0.00046666,0.0003564934,0.003991532,0.0008312691,0.61185,0.2655776,0.02037205,0.01244577,0.0001312287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6738257,0.0009486767,0.3005506,0.0004926462,0.00003261093,0.0003034467,0.000535962,0.01570589,0.007604566],"genre_scores_gemma":[0.9075046,0.0002568061,0.09039952,0.00009068495,0.00001161703,0.00008972978,0.0005665097,0.0002921581,0.0007884877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003461095,"threshold_uncertainty_score":0.01212513,"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."}}