{"id":"https://openalex.org/W7131415044","doi":"https://doi.org/10.48550/arxiv.2602.19818","title":"SafePickle: Robust and Generic ML Detection of Malicious Pickle-based ML Models","display_name":"SafePickle: Robust and Generic ML Detection of Malicious Pickle-based ML Models","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131415044","doi":"https://doi.org/10.48550/arxiv.2602.19818"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.19818","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19818","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.19818","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115500829","display_name":"Hillel Ohayon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ohayon, Hillel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093006059","display_name":"Daniel Gilkarov","orcid":"https://orcid.org/0009-0008-9274-802X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gilkarov, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5027608715","display_name":"Ran Dubin","orcid":"https://orcid.org/0000-0002-2055-2211"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dubin, Ran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.7254999876022339,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.7254999876022339,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11424","display_name":"Security and Verification in Computing","score":0.1597999930381775,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10743","display_name":"Software Testing and Debugging Techniques","score":0.021299999207258224,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6309000253677368},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6291000247001648},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6144999861717224},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5454999804496765},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.4480000138282776},{"id":"https://openalex.org/keywords/bytecode","display_name":"Bytecode","score":0.4259999990463257},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.3560999929904938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.848800003528595},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6309000253677368},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6291000247001648},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6144999861717224},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5454999804496765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4952000081539154},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C2779818221","wikidata":"https://www.wikidata.org/wiki/Q837330","display_name":"Bytecode","level":3,"score":0.4259999990463257},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42489999532699585},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3391999900341034},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.31310001015663147},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C97250363","wikidata":"https://www.wikidata.org/wiki/Q235557","display_name":"File format","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2694999873638153}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.19818","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19818","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.19818","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.19818","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4460054636001587,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Model":[0],"repositories":[1],"such":[2,29],"as":[3,30,91],"Hugging":[4,107],"Face":[5,108],"increasingly":[6],"distribute":[7],"machine":[8],"learning":[9],"artifacts":[10],"serialized":[11],"with":[12,136,161],"Python's":[13],"pickle":[14],"format,":[15],"exposing":[16],"users":[17],"to":[18,88,182,194],"remote":[19],"code":[20,69],"execution":[21],"(RCE)":[22],"risks":[23],"during":[24],"model":[25,208],"loading.":[26],"Recent":[27],"defenses,":[28],"PickleBall,":[31],"rely":[32],"on":[33,113,147,151],"per-library":[34],"policy":[35,66],"synthesis":[36],"that":[37,60,175,199],"requires":[38],"complex":[39],"system":[40],"setups":[41],"and":[42,49,76,82,85,97,109,126,185,204],"verified":[43],"benign":[44,92],"models,":[45],"which":[46],"limits":[47],"scalability":[48],"generalization.":[50],"In":[51],"this":[52],"work,":[53],"we":[54,173],"propose":[55],"a":[56,99],"lightweight,":[57],"machine-learning-based":[58],"scanner":[59],"detects":[61],"malicious":[62,124,190],"Pickle-based":[63,104,207],"files":[64,90,105],"without":[65],"generation":[67],"or":[68,93],"instrumentation.":[70],"Our":[71,130],"approach":[72],"statically":[73],"extracts":[74],"structural":[75],"semantic":[77],"features":[78],"from":[79,106],"Pickle":[80],"bytecode":[81],"applies":[83],"supervised":[84],"unsupervised":[86],"models":[87,112,191],"classify":[89,186],"malicious.":[94],"We":[95],"construct":[96],"release":[98],"labeled":[100],"dataset":[101],"of":[102],"727":[103],"evaluate":[110],"our":[111,116,148,176],"four":[114],"datasets:":[115],"own,":[117],"PickleBall":[118,153,166],"(out-of-distribution),":[119],"Hide-and-Seek":[120,189],"(9":[121],"advanced":[122],"evasive":[123,188],"models),":[125],"synthetic":[127],"joblib":[128],"files.":[129],"method":[131,177],"achieves":[132,157],"90.01%":[133],"F1-score":[134,159],"compared":[135,160],"7.23%-62.75%":[137],"achieved":[138,163],"by":[139,164],"the":[140,152,165,179],"SOTA":[141],"scanners":[142],"(Modelscan,":[143],"Fickling,":[144],"ClamAV,":[145],"VirusTotal)":[146],"dataset.":[149],"Furthermore,":[150],"data":[154],"(OOD),":[155],"it":[156],"81.22%":[158],"76.09%":[162],"method,":[167],"while":[168],"remaining":[169],"fully":[170],"library-agnostic.":[171],"Finally,":[172],"show":[174],"is":[178],"only":[180],"one":[181],"correctly":[183],"parse":[184],"9/9":[187],"specially":[192],"crafted":[193],"evade":[195],"scanners.":[196],"This":[197],"demonstrates":[198],"data-driven":[200],"detection":[201],"can":[202],"effectively":[203],"generically":[205],"mitigate":[206],"file":[209],"attacks.":[210]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-02-26T00:00:00"}