{"id":"https://openalex.org/W7170556575","doi":"https://doi.org/10.48550/arxiv.2607.20759","title":"IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests","display_name":"IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests","publication_year":2026,"publication_date":"2026-07-22","ids":{"openalex":"https://openalex.org/W7170556575","doi":"https://doi.org/10.48550/arxiv.2607.20759"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.20759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.20759","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.2607.20759","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5143581294","display_name":"Ankur Singh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Singh, Ankur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143545256","display_name":"Jinqiu Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jinqiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5143582019","display_name":"Tse-Hsun Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Tse-Hsun","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":0.6069999933242798,"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":0.6069999933242798,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.17900000512599945,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.041099999099969864,"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/backdoor","display_name":"Backdoor","score":0.8447999954223633},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6211000084877014},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6162999868392944},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.47450000047683716},{"id":"https://openalex.org/keywords/secure-coding","display_name":"Secure coding","score":0.37380000948905945},{"id":"https://openalex.org/keywords/compromise","display_name":"Compromise","score":0.37119999527931213}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.8447999954223633},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.6959999799728394},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6211000084877014},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6162999868392944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.616100013256073},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.47450000047683716},{"id":"https://openalex.org/C22680326","wikidata":"https://www.wikidata.org/wiki/Q7444867","display_name":"Secure coding","level":5,"score":0.37380000948905945},{"id":"https://openalex.org/C46355384","wikidata":"https://www.wikidata.org/wiki/Q726686","display_name":"Compromise","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3402999937534332},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C2777381055","wikidata":"https://www.wikidata.org/wiki/Q308922","display_name":"Damages","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.20759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.20759","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.2607.20759","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.20759","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"AI":[0,239],"coding":[1,89,155,173,222,240],"agents":[2,29,90],"powered":[3,97],"by":[4,98,144],"LLMs":[5,185],"are":[6,118],"increasingly":[7],"integrated":[8],"into":[9],"real-world":[10],"software":[11],"development,":[12],"where":[13,38,60],"they":[14],"generate,":[15],"edit,":[16],"and":[17,26,44,56,71,94,106,141,170,196,233],"execute":[18],"code":[19],"with":[20,191],"autonomous":[21],"access":[22],"to":[23,50,237],"local":[24],"files":[25],"tools.":[27],"Coding":[28],"inherit":[30],"security":[31],"risks":[32],"from":[33,163,184],"both":[34],"the":[35,152,160,167,188,212,227],"LLM":[36],"backbone,":[37],"adversarial":[39],"prompts,":[40],"poisoned":[41],"training":[42],"data,":[43],"backdoor":[45],"triggers":[46],"can":[47],"cause":[48],"models":[49,193],"emit":[51],"insecure":[52],"or":[53,138],"attacker-chosen":[54],"code,":[55],"their":[57],"agentic":[58],"architecture,":[59],"tool-using":[61],"autonomy":[62],"enables":[63],"induced":[64],"misuse":[65],"of":[66,74,83,159,172,204],"external":[67],"APIs,":[68],"data":[69],"exfiltration,":[70],"persistent":[72],"compromise":[73],"development":[75],"environments.":[76],"This":[77],"paper":[78],"presents":[79],"a":[80],"systematic":[81],"evaluation":[82,208],"malicious":[84,115,129,161],"issue":[85,139],"requests":[86],"against":[87],"state-of-the-art":[88],"(Cursor,":[91],"Claude":[92],"Code,":[93],"Codex":[95],"Desktop),":[96],"two":[99],"major":[100],"model":[101],"families":[102],"(OpenAI":[103],"GPT-5.3":[104],"Codex/GPT-5.4":[105],"Anthropic":[107],"Sonnet":[108,197],"4.6).":[109],"Our":[110,146,175,207,224],"novel":[111,123],"benchmark":[112],"IssueTrojanBench":[113,164],"contains":[114],"issues":[116,162],"that":[117,179,211],"constructed":[119],"based":[120],"on":[121],"four":[122],"attack":[124],"categories":[125],"(i.e.,":[126],"embedded":[127],"as":[128],"instructions":[130],"in":[131,151],"issues),":[132],"six":[133],"delivery":[134],"vectors":[135],"(e.g.,":[136],"PDF,":[137],"comment),":[140],"further":[142,176],"augmented":[143],"perturbations.":[145],"results":[147],"reveal":[148],"critical":[149],"vulnerabilities":[150],"as-deployed":[153],"modern":[154],"agents,":[156],"i.e.,":[157],"66.5%":[158],"penetrate":[165],"all":[166],"guardrails":[168],"(agent-":[169],"LLM-level)":[171],"agents.":[174,223,241],"analysis":[177],"shows":[178],"rejection":[180],"is":[181],"almost":[182],"entirely":[183],"rather":[186],"than":[187],"agent":[189],"frameworks,":[190],"GPT":[192],"broadly":[194],"vulnerable":[195],"4.6":[198],"exhibiting":[199],"more":[200],"selective,":[201],"risk-aware":[202],"blocking":[203],"high-impact":[205],"actions.":[206],"also":[209],"highlights":[210],"current":[213],"agent-level":[214],"defense":[215],"strategy":[216],"offers":[217],"limited":[218],"additional":[219],"protection":[220],"for":[221,230],"findings":[225],"highlight":[226],"urgent":[228],"need":[229],"stronger":[231],"agent-":[232],"model-level":[234],"safety":[235],"mechanisms":[236],"protect":[238]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-25T00:00:00"}