{"id":"https://openalex.org/W7126177720","doi":"https://doi.org/10.48550/arxiv.2601.22136","title":"StepShield: When, Not Whether to Intervene on Rogue Agents","display_name":"StepShield: When, Not Whether to Intervene on Rogue Agents","publication_year":2026,"publication_date":"2026-01-29","ids":{"openalex":"https://openalex.org/W7126177720","doi":"https://doi.org/10.48550/arxiv.2601.22136"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.22136","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.22136","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.22136","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124403075","display_name":"Gloria Felicia","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Felicia, Gloria","raw_affiliation_strings":["University of Virginia"],"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124408595","display_name":"Michael Eniolade","orcid":null},"institutions":[{"id":"https://openalex.org/I276309446","display_name":"University of the Cumberlands","ror":"https://ror.org/05jz3sn81","country_code":"US","type":"education","lineage":["https://openalex.org/I276309446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eniolade, Michael","raw_affiliation_strings":["University of the Cumberlands"],"affiliations":[{"raw_affiliation_string":"University of the Cumberlands","institution_ids":["https://openalex.org/I276309446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124412861","display_name":"Jinfeng He","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"He, Jinfeng","raw_affiliation_strings":["Cornell University"],"affiliations":[{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045162901","display_name":"Zitha Sasindran","orcid":"https://orcid.org/0000-0002-0224-3722"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sasindran, Zitha","raw_affiliation_strings":["Indian Institute of Science Bangalore"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Science Bangalore","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124316412","display_name":"Hemant Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kumar, Hemant","raw_affiliation_strings":["University of Arizona"],"affiliations":[{"raw_affiliation_string":"University of Arizona","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124338780","display_name":"Milan Hussain Angati","orcid":null},"institutions":[{"id":"https://openalex.org/I157638225","display_name":"California State University, Northridge","ror":"https://ror.org/005f5hv41","country_code":"US","type":"education","lineage":["https://openalex.org/I157638225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Angati, Milan Hussain","raw_affiliation_strings":["California State University Northridge"],"affiliations":[{"raw_affiliation_string":"California State University Northridge","institution_ids":["https://openalex.org/I157638225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124327952","display_name":"Sandeep Bandarupalli","orcid":null},"institutions":[{"id":"https://openalex.org/I63135867","display_name":"University of Cincinnati","ror":"https://ror.org/01e3m7079","country_code":"US","type":"education","lineage":["https://openalex.org/I63135867"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bandarupalli, Sandeep","raw_affiliation_strings":["University of Cincinnati"],"affiliations":[{"raw_affiliation_string":"University of Cincinnati","institution_ids":["https://openalex.org/I63135867"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5124403075"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.42890000343322754,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.42890000343322754,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.07819999754428864,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.05260000005364418,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.6675000190734863},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5648999810218811},{"id":"https://openalex.org/keywords/intervention","display_name":"Intervention (counseling)","score":0.5354999899864197},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5242000222206116},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.517799973487854},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4361000061035156},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4323999881744385},{"id":"https://openalex.org/keywords/false-accusation","display_name":"False accusation","score":0.3790000081062317}],"concepts":[{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.6675000190734863},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6338000297546387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5778999924659729},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5648999810218811},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.5354999899864197},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5242000222206116},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.517799973487854},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4361000061035156},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4323999881744385},{"id":"https://openalex.org/C59577422","wikidata":"https://www.wikidata.org/wiki/Q10265143","display_name":"False accusation","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3174999952316284},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28870001435279846},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.28220000863075256},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.26750001311302185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.266400009393692},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.22136","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.22136","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.22136","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.22136","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.626232385635376}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Existing":[0],"agent":[1,64],"safety":[2],"benchmarks":[3,41],"report":[4],"binary":[5],"accuracy,":[6],"conflating":[7],"early":[8,143],"intervention":[9],"with":[10,77],"post-mortem":[11],"analysis.":[12],"A":[13],"detector":[14,152],"that":[15,25,113,131,142],"flags":[16],"a":[17,73,78,121,127,183],"violation":[18],"at":[19,28,168],"step":[20,29],"8":[21],"enables":[22],"intervention;":[23],"one":[24],"reports":[26],"it":[27],"48":[30],"provides":[31,182],"only":[32,125],"forensic":[33],"value.":[34],"This":[35],"distinction":[36],"is":[37,132],"critical,":[38],"yet":[39],"current":[40],"cannot":[42],"measure":[43],"it.":[44],"We":[45,94,139],"introduce":[46],"StepShield,":[47],"the":[48,173],"first":[49],"benchmark":[50],"to":[51,135,160,179],"evaluate":[52],"when":[53],"violations":[54],"are":[55,85,199],"detected,":[56],"not":[57],"just":[58],"whether.":[59],"StepShield":[60,181],"contains":[61],"9,213":[62],"code":[63,196],"trajectories,":[65],"including":[66],"1,278":[67],"meticulously":[68],"annotated":[69],"training":[70],"pairs":[71],"and":[72,106,158,189,197],"7,935-trajectory":[74],"test":[75],"set":[76],"realistic":[79],"8.1%":[80],"rogue":[81],"rate.":[82],"Rogue":[83],"behaviors":[84],"grounded":[86],"in":[87,162],"real-world":[88],"security":[89],"incidents":[90],"across":[91],"six":[92],"categories.":[93],"propose":[95],"three":[96],"novel":[97],"temporal":[98],"metrics:":[99],"Early":[100],"Intervention":[101,104],"Rate":[102],"(EIR),":[103],"Gap,":[105],"Tokens":[107],"Saved.":[108],"Surprisingly,":[109],"our":[110,149],"evaluation":[111,176],"reveals":[112],"an":[114,202],"LLM-based":[115],"judge":[116],"achieves":[117,124],"59%":[118],"EIR":[119],"while":[120],"static":[122],"analyzer":[123],"26%,":[126],"2.3x":[128],"performance":[129],"gap":[130],"entirely":[133],"invisible":[134],"standard":[136],"accuracy":[137],"metrics.":[138],"further":[140],"show":[141],"detection":[144],"has":[145],"direct":[146],"economic":[147],"benefits:":[148],"cascaded":[150],"HybridGuard":[151],"reduces":[153],"monitoring":[154],"costs":[155],"by":[156],"75%":[157],"projects":[159],"$108M":[161],"cumulative":[163],"savings":[164],"over":[165],"five":[166],"years":[167],"enterprise":[169],"scale.":[170],"By":[171],"shifting":[172],"focus":[174],"of":[175],"from":[177],"whether":[178],"when,":[180],"new":[184],"foundation":[185],"for":[186],"building":[187],"safer":[188],"more":[190],"economically":[191],"viable":[192],"AI":[193],"agents.":[194],"The":[195],"data":[198],"released":[200],"under":[201],"Apache":[203],"2.0":[204],"license.":[205]},"counts_by_year":[],"updated_date":"2026-02-01T03:38:14.988550","created_date":"2026-02-01T00:00:00"}