{"id":"https://openalex.org/W7161685576","doi":"https://doi.org/10.48550/arxiv.2605.18583","title":"Overeager Coding Agents: Measuring Out-of-Scope Actions on Benign Tasks","display_name":"Overeager Coding Agents: Measuring Out-of-Scope Actions on Benign Tasks","publication_year":2026,"publication_date":"2026-05-18","ids":{"openalex":"https://openalex.org/W7161685576","doi":"https://doi.org/10.48550/arxiv.2605.18583"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.18583","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18583","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2605.18583","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136465826","display_name":"Yubin Qu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qu, Yubin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136457817","display_name":"Ying Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Ying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136491260","display_name":"Yanjun Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yanjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136498361","display_name":"Gelei Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Gelei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136475829","display_name":"Yuekang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuekang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136484084","display_name":"Leo Yu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Leo Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136502343","display_name":"Yi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yi","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/T10927","display_name":"Access Control and Trust","score":0.45649999380111694,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10927","display_name":"Access Control and Trust","score":0.45649999380111694,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11424","display_name":"Security and Verification in Computing","score":0.1378999948501587,"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/T11644","display_name":"Spam and Phishing Detection","score":0.051600001752376556,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/discriminative-model","display_name":"Discriminative model","score":0.5841000080108643},{"id":"https://openalex.org/keywords/declaration","display_name":"Declaration","score":0.5209000110626221},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.46639999747276306},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.39559999108314514},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3871000111103058},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.34389999508857727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.670799970626831},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5841000080108643},{"id":"https://openalex.org/C138147947","wikidata":"https://www.wikidata.org/wiki/Q1183659","display_name":"Declaration","level":2,"score":0.5209000110626221},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.46639999747276306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4291999936103821},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.39559999108314514},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C178005623","wikidata":"https://www.wikidata.org/wiki/Q308859","display_name":"Anonymity","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28450000286102295},{"id":"https://openalex.org/C2776788033","wikidata":"https://www.wikidata.org/wiki/Q320769","display_name":"Eavesdropping","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C108759981","wikidata":"https://www.wikidata.org/wiki/Q788590","display_name":"Authorization","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25690001249313354},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.18583","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18583","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.18583","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.18583","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.6593447923660278,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Coding":[0],"agents":[1],"now":[2],"run":[3],"autonomously":[4],"with":[5],"shell,":[6],"file,":[7],"and":[8,94,152,156,164,178,190],"network":[9],"privileges.":[10],"When":[11],"a":[12,15,30,63,75,79,135,143,182,217],"user":[13,38],"issues":[14],"benign":[16,70],"request,":[17],"the":[18,37,83,87,89,103,108,198,230],"agent":[19,90,169],"sometimes":[20],"does":[21,251],"more":[22],"than":[23],"asked:":[24],"it":[25,73],"deletes":[26],"unrelated":[27],"files,":[28],"wipes":[29],"stale":[31],"credentials":[32],"backup,":[33],"or":[34,57],"rewrites":[35],"configuration":[36],"never":[39],"mentioned.":[40],"We":[41,60],"call":[42],"these":[43],"scope":[44,85],"expansions":[45],"overeager":[46,67,109,199],"actions,":[47],"an":[48],"authorization":[49],"problem":[50],"distinct":[51],"from":[52,111],"capability":[53],"failures,":[54],"prompt":[55],"injection,":[56],"sandbox":[58],"escapes.":[59],"present":[61],"OverEager-Gen,":[62],"benchmark":[64,80],"dedicated":[65],"to":[66,113],"behavior":[68],"on":[69,115,201],"tasks.":[71],"Building":[72],"surfaces":[74],"measurement-validity":[76],"issue:":[77],"if":[78],"spells":[81],"out":[82],"authorized":[84],"inside":[86],"prompt,":[88],"stops":[91],"inferring":[92],"boundaries":[93],"starts":[95],"pattern-matching":[96],"declaration":[97,105],"text.":[98],"On":[99],"Claude":[100],"Code,":[101,172,221],"stripping":[102],"consent":[104,196],"alone":[106],"raises":[107],"rate":[110,200],"0.0%":[112],"17.1%":[114],"paired":[116],"scenarios":[117,163],"(McNemar":[118],"exact":[119],"p":[120,238],"=":[121,188,193],"2.4":[122],"x":[123],"10^-4).":[124],"OverEager-Gen":[125],"therefore":[126],"certifies":[127],"each":[128],"scenario's":[129],"discriminative":[130],"power":[131],"before":[132],"admission":[133],"via":[134],"behavioral-gradient":[136],"validator,":[137],"audits":[138],"internal":[139],"tool":[140],"calls":[141],"through":[142,255],"dual-channel":[144],"stack":[145],"(PATH-injected":[146],"shim":[147],"plus":[148],"per-agent":[149],"event":[150],"streams),":[151],"ships":[153],"byte-identical":[154],"consent_kept":[155],"consent_stripped":[157],"variants.":[158],"OverEager-Bench":[159],"contains":[160],"500":[161],"validated":[162],"~7,500":[165],"runs":[166,226],"across":[167],"four":[168],"products":[170],"(Claude":[171,220],"OpenHands,":[173],"Codex":[174,222],"CLI,":[175,223],"Gemini":[176,224],"CLI)":[177,225],"six":[179],"base":[180,204],"models;":[181],"50-sample":[183],"re-annotation":[184],"gives":[185],"Cohen's":[186],"kappa":[187],"0.73":[189],"rule-judge":[191],"recall":[192],"1.00.":[194],"Stripping":[195],"multiplies":[197],"every":[202],"shared":[203],"model":[205],"(Delta":[206],"in":[207],"[11.9,":[208],"17.2]":[209],"pp).":[210],"The":[211],"framework":[212,232],"axis":[213],"dominates":[214],"effect":[215],"size:":[216],"permissive":[218,256],"cluster":[219],"at":[227,235],"5.4-27.7%":[228],"while":[229],"ask-to-continue":[231],"(OpenHands)":[233],"sits":[234],"0.2-4.5%":[236],"(Fisher":[237],"<=":[239],"10^-5).":[240],"Within-framework":[241],"base-model":[242],"variance":[243],"reaches":[244],"15.9":[245],"pp,":[246],"indicating":[247],"that":[248],"model-layer":[249],"alignment":[250],"not":[252],"fully":[253],"propagate":[254],"permission":[257],"gating.":[258]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-20T00:00:00"}