{"id":"https://openalex.org/W7165683688","doi":"https://doi.org/10.48550/arxiv.2606.22698","title":"Black-Box Forensics for Conversational LLM Agents","display_name":"Black-Box Forensics for Conversational LLM Agents","publication_year":2026,"publication_date":"2026-06-21","ids":{"openalex":"https://openalex.org/W7165683688","doi":"https://doi.org/10.48550/arxiv.2606.22698"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.22698","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22698","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.22698","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139207173","display_name":"Isadora White","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"White, Isadora","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139194993","display_name":"Yasaman Jafari","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jafari, Yasaman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017455302","display_name":"Taylor Berg-Kirkpatrick","orcid":"https://orcid.org/0000-0002-1283-4075"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Berg-Kirkpatrick, Taylor","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/T12034","display_name":"Digital and Cyber Forensics","score":0.5034999847412109,"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"}},"topics":[{"id":"https://openalex.org/T12034","display_name":"Digital and Cyber Forensics","score":0.5034999847412109,"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"}},{"id":"https://openalex.org/T12519","display_name":"Cybercrime and Law Enforcement Studies","score":0.1137000024318695,"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"}},{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.09440000355243683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/chatbot","display_name":"Chatbot","score":0.6129999756813049},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.524399995803833},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.5034999847412109},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4763999879360199},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4316999912261963},{"id":"https://openalex.org/keywords/interrogation","display_name":"Interrogation","score":0.40470001101493835},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.37380000948905945},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.37209999561309814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7749000191688538},{"id":"https://openalex.org/C2779041454","wikidata":"https://www.wikidata.org/wiki/Q870780","display_name":"Chatbot","level":2,"score":0.6129999756813049},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.524399995803833},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.5034999847412109},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4763999879360199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4657000005245209},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4560000002384186},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C2776240099","wikidata":"https://www.wikidata.org/wiki/Q327018","display_name":"Interrogation","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.37209999561309814},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.36390000581741333},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29429998993873596},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27619999647140503},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2614000141620636},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2612999975681305}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.22698","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22698","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.22698","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22698","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":"Preprint"},"sustainable_development_goals":[{"score":0.7790795564651489,"display_name":"Peace, Justice and strong institutions","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":{"As":[0],"LLM-powered":[1],"scams":[2,46,74],"proliferate,":[3],"black-box":[4],"forensics":[5],"for":[6,15,125],"conversational":[7],"LLM":[8],"agents":[9,180],"offers":[10],"a":[11,26,105,120,193],"path":[12],"to":[13,48,177],"accountability":[14],"systems":[16],"hidden":[17,38],"behind":[18,25,98],"anonymous":[19],"endpoints.":[20],"Identifying":[21],"the":[22,37,49,60,95,131],"base":[23,96],"model":[24,31,97],"chatbot":[27],"endpoint":[28],"(attribution),":[29],"without":[30],"parameter":[32],"access":[33],"or":[34],"knowledge":[35],"of":[36,88,108,112,123,154,159,196],"system":[39,63,113,128,164,183],"prompt,":[40],"would":[41,71],"let":[42],"investigators":[43],"trace":[44],"AI-enabled":[45],"back":[47],"providers":[50],"whose":[51],"models":[52],"power":[53],"them.":[54],"Detecting":[55],"when":[56],"two":[57],"endpoints":[58],"run":[59],"exact":[61],"same":[62],"prompt":[64],"(fingerprinting),":[65],"even":[66],"one":[67],"novel":[68],"and":[69,78,135,156,166],"unseen,":[70],"link":[72],"individual":[73],"into":[75],"criminal":[76],"networks":[77],"expose":[79],"silent":[80],"API":[81],"changes.":[82],"We":[83],"conduct":[84],"an":[85,99,152,157],"empirical":[86],"investigation":[87],"both":[89],"capabilities.":[90],"Our":[91],"attribution":[92],"classifiers":[93],"identify":[94],"agent":[100,174],"with":[101,181,189],"98%":[102],"accuracy":[103,191],"from":[104,171,192],"few":[106,194],"turns":[107,195],"non-adversarial":[109],"conversation.":[110,198],"Attribution":[111],"prompts,":[114,165],"while":[115],"possible,":[116],"requires":[117],"retraining":[118],"on":[119,161],"large":[121],"amount":[122],"data":[124],"each":[126,172],"prompt;":[127],"prompts":[129,184],"in":[130],"wild":[132],"are":[133],"unbounded":[134],"ever-changing,":[136],"making":[137],"this":[138,143],"approach":[139],"costly.":[140],"To":[141],"tackle":[142],"more":[144],"open-ended":[145],"setting,":[146],"our":[147],"cross-encoder":[148],"fingerprinting":[149],"method":[150],"achieves":[151],"AUC":[153,176],"0.768":[155],"F1":[158],"0.703":[160],"entirely":[162],"unseen":[163,182],"aggregating":[167],"50":[168],"interaction":[169],"conversations":[170],"target":[173],"boosts":[175],"0.943.":[178],"Conversational":[179],"can":[185],"thus":[186],"be":[187],"fingerprinted":[188],"robust":[190],"ordinary":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}