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ARXIV:2603.25997 · SOFTWARE SUPPLY CHAIN SECURITY · SUBMITTED 30 MAR · 21:55 UTC · FRESHNESS STALE
ARXIV:2603.25997SOFTWARE SUPPLY CHAIN SECURITYSUBMITTED 30 MAR · 21:55 UTCFRESHNESS STALEZirui Chen · Qi Zhan · Jiayuan Zhou · Xing Hu · Xin Xia · Xiaohu Yang · arXiv
Automate Java library vulnerability detection by migrating and applying existing exploits across versions, significantly improving accuracy over current tools.
Opportunity summary
Pain Automate Java library vulnerability detection by migrating and applying existing exploits across versions, significantly improving accuracy over current tools.
Evidence 71 refs | 3 sources | 50% coverage
Blocker Evidence unverified
Automate Java library vulnerability detection by migrating and applying existing exploits across versions, significantly improving accuracy over current tools. While prior studies have leveraged exploits for verifying vulnerability affected versions, they point out a…
Open-source software supply chain security relies heavily on assessing affected versions of library vulnerabilities. While prior studies have leveraged exploits for verifying vulnerability affected versions, they point out a key limitation that exploits are…
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Our results (RQ1) show that, even without migration, exploits achieve 83.0% recall and 99.3% precision in identifying affected versions in Java, outperforming most widely…
Software Supply Chain Security moved forward this cycle; last verified April 2026. Public score 7.0/10. Production flags indicate code availability.
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mobile layout uses overflow-hidden min-w-0 break-wordsOpportunity summary
Score7.0Public score shown from the verified overall while the stale axis breakdown refreshesAnalysis summary
Automate Java library vulnerability detection by migrating and applying existing exploits across versions, significantly improving accuracy over current tools.
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Paper Pack
10.48550/arXiv.2603.25997Automate Java library vulnerability detection by migrating and applying existing exploits across versions, significantly improving accuracy over current tools.
Abstract
Open-source software supply chain security relies heavily on assessing affected versions of library vulnerabilities. While prior studies have leveraged exploits for verifying vulnerability affected versions, they point out a key limitation that exploits are version-specific and cannot be directly applied across library versions. Despite being widely acknowledged, this limitation has not been systematically validated at scale, leaving the actual applicability of exploits across versions unexplored. To fill this gap, we conduct the first large-scale empirical study on exploit applicability across library versions. We construct a comprehensive dataset consisting of 259 exploits spanning 128 Java libraries and 28,150 historical versions, covering 61 CWEs that account for 76.33% of vulnerabilities in Maven. Leveraging this dataset, we execute each exploit against the library version history and compare the execution outcomes with our manually annotated ground-truth affected versions. We further investigate the root causes of inconsistencies between exploit execution and ground truth, and explore strategies for exploit migration. Our results (RQ1) show that, even without migration, exploits achieve 83.0% recall and 99.3% precision in identifying affected versions in Java, outperforming most widely used vulnerability databases and assessment tools. Notably, this capability enables us to contribute 796 confirmed missing affected versions to the CPE dictionary. We investigate the remaining exploit failures (RQ2) and find that they mainly stem from compatibility issues introduced by library evolution and changing environmental constraints. Based on these observations, we manually migrate exploits for 1,885 versions and distill a taxonomy of 10 strategies from these successful adaptation cases (RQ3), thereby increasing the overall recall to 96.1%.
Source availability
PDF linkedThe paper record includes a public PDF URL.
Extraction status
Parse run pending anchorsA parse run id is attached, but no public source anchors are materialized yet.
Proof status
unverified71 refs; 3 sources; 50% coverage.
What was readable
Derived fallback: Estimated from adjacent evidence; not verified from source.
Viability
Time to MVP
Commercial
Export
Preparing verified analysis
Dimensions overall score 7.0
PROBLEM
Automate Java library vulnerability detection by migrating and applying existing exploits across versions, significantly improving accuracy over current tools. While prior studies have leveraged exploits for verifying vulnerability affected versions, they point out a key limitat...
METHOD
Open-source software supply chain security relies heavily on assessing affected versions of library vulnerabilities. While prior studies have leveraged exploits for verifying vulnerability affected versions, they point out a key limitation that exploits are version-specific and...
RESULT
ScienceToStartup currently rates this 7.0/10 on the public viability pass. Our results (RQ1) show that, even without migration, exploits achieve 83.0% recall and 99.3% precision in identifying affected versions in Java, outperforming most widely used vulnerability databases and...
WHY NOW
Software Supply Chain Security moved forward this cycle; last verified April 2026. Public score 7.0/10. Production flags indicate code availability.
Our results (RQ1) show that, even without migration, exploits achieve 83.0% recall and 99.3% precision in identifying affected versions in Java, outperforming most widely used vulnerability databases and assessment tools.
This is a direct result stated in the abstract and supported by the analysis of RQ1.
partial
We construct a comprehensive dataset consisting of 259 exploits spanning 128 Java libraries and 28,150 historical versions, covering 61 CWEs that account for 76.33% of vulnerabilities in Maven.
This is a key contribution and dataset size explicitly stated in the abstract and contributions section.
partial
We investigate the remaining exploit failures (RQ2) and find that they mainly stem from compatibility issues introduced by library evolution and changing environmental constraints.
This is a direct finding from the analysis of RQ2, as stated in the abstract.
partial
Based on these observations, we manually migrate exploits for 1,885 versions and distill a taxonomy of 10 strategies from these successful adaptation cases (RQ3), thereby increasing the overall recall to 96.1%.
This is a direct result of the exploit migration effort (RQ3) stated in the abstract.
partial
Notably, this capability enables us to contribute 796 confirmed missing affected versions to the CPE dictionary.
This is a direct outcome of the exploit applicability analysis, as stated in the abstract.
partial
Based on these observations, we manually migrate exploits for 1,885 versions and distill a taxonomy of 10 strategies from these successful adaptation cases (RQ3), thereby increasing the overall recall to 96.1%.
This is a direct outcome of the exploit migration analysis (RQ3) stated in the abstract.
partial
Our dataset encompasses vulnerabilities affecting 128 libraries across 41 categories, ranging from testing frameworks and logging tools to JVM languages, HTTP clients, XML processors, and Object Serialization libraries.
This detail about the dataset composition is explicitly mentioned in the 'Library Categories' section.
partial
Our results (RQ1) show that, even without migration, exploits achieve 83.0% recall and 99.3% precision in identifying affected versions in Java, outperforming most widely used vulnerability databases and assessment tools.
This is a direct result stated in the abstract and supported by the analysis of RQ1.
partial
We construct a comprehensive dataset consisting of 259 exploits spanning 128 Java libraries and 28,150 historical versions, covering 61 CWEs that account for 76.33% of vulnerabilities in Maven.
This is a key contribution and dataset size explicitly mentioned in the abstract and contributions section.
partial
We investigate the remaining exploit failures (RQ2) and find that they mainly stem from compatibility issues introduced by library evolution and changing environmental constraints.
This is a direct finding from the analysis of RQ2, as stated in the abstract.
partial
Based on these observations, we manually migrate exploits for 1,885 versions and distill a taxonomy of 10 strategies from these successful adaptation cases (RQ3), thereby increasing the overall recall to 96.1%.
This is a direct result quantifying the impact of exploit migration, as stated in the abstract and conclusion.
partial
Notably, this capability enables us to contribute 796 confirmed missing affected versions to the CPE dictionary.
This is a specific, verifiable outcome of the study's findings, mentioned as a contribution.
partial
Paper-native neighborhood for concepts, methods, materials, markets, and competitors. Missing lanes stay labeled instead of disappearing behind commercialization gates.
Concepts
Methods
Materials
Markets
Competitors
Automate Java library vulnerability detection by migrating and applying existing exploits across versions, significantly improving accuracy over current tools.
Segment
Software Supply Chain Security
Adoption evidence
No public code link in the paper record yet
Commercial read
7.0/10 public viability
Direct
Adjacent
Substitute
Unknown
No indexed public discussion is attached to 2603.25997 yet. That is a visibility signal, not a blank module: the monitor is watching the public channels below.
Hacker News
Not indexed yet
Not indexed yet
Bluesky
Not indexed yet
Preview the source document here, or use the hero PDF action for a new tab.
Reference metadata is not materialized in the public index yet. The source PDF remains the authority; cache refresh is optional.
CITED BY
No citing papers are indexed in the public S2S graph yet. This is an explicit zero-signal state, not a hidden lookup.
Foundation
Extension
Commercially relevant
Conflicting
Owned Distribution
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3/3 checks · 100%
Build Passport
Build passport pending - Proof Lab budget No verified cost estimate / $7.00 cap
status
missing
reason
passport_row_missing
proof status
unverified
cost/budget
No verified cost estimate
confidence low
next verification path
Build brief missing until Build Passport data exists.
Source missing: Build Passport payload.
Experiment plan missing until prototype path is available.
No prototype path attached.
Validation checklist missing until required assets, cost, and regulatory flags are verified.
No checklist artifact is attached to the Build Passport payload.
Derived signals show verified:false until source-backed receipts exist.
Evidence coverage
OpportunityKernel evidence_receipt
71 refs / 3 sources / 50% coverage
stale
Verify missing sources before using this as buyer proof. verified:false
Build readiness
BuildPassport EvidenceState
passport absent
stale
Run Proof Lab or inspect typed missing state. verified:false
Artifact maturity
GitHub and Hugging Face maturity payloads
No public artifact surface observed
stale
Open source artifacts or mark the gap as missing. verified:false
Technical feasibility
partial
Current read
Runnable path is not fully verified.
Evidence
No Build Passport payload attached.
Gaps
Next test
Run minimal reproduction from the Build Passport prototype path.
Market urgency
partial
Current read
Research evidence exists; buyer urgency still needs source proof.
Evidence
71 references, 3 sources, 50% evidence coverage.
Gaps
Next test
Collect buyer interview, deployment evidence, or cited demand signal.
Buyer clarity
missing
Current read
No budget owner is verified for this paper.
Evidence
Build tab has no CRM, procurement, or operator source.
Gaps
Next test
Map target operator, economic buyer, and procurement trigger.
Defensibility
missing
Current read
Defensibility signals are missing.
Evidence
No defensibility receipt attached.
Gaps
Next test
Refresh defensibility bars with source receipts.
Integration burden
missing
Current read
No public implementation surface observed.
Evidence
No GitHub or Hugging Face payload attached.
Gaps
Next test
Write integration checklist from prototype path and target workflow.
Capital intensity
missing
Current read
No observed cost estimate is verified.
Evidence
Cost passport has no observed_usd value.
Gaps
Next test
Run cost passport or mark the cost field not applicable.
Regulatory load
missing
Current read
No regulatory classification is attached.
Evidence
Build Passport ledger does not include regulatory flags.
Gaps
Next test
Classify regulatory flags before commercialization planning.
No named scientific founder assigned.
Paper authors are not treated as operators without consent.
People
No named person assigned.
Gaps
Next verification path
Prototype owner missing.
Build Passport does not name an implementer.
People
No named person assigned.
Gaps
Next verification path
Operator workflow not sourced.
No buyer or workflow interview attached.
People
No named person assigned.
Gaps
Next verification path
No GTM owner verified.
No CRM or outreach source attached.
People
No named person assigned.
Gaps
Next verification path
Regulatory need unclassified.
No clinical or regulatory source attached.
People
No named person assigned.
Gaps
Next verification path
ARTIFACTS
No public artifacts yet.
DEFENSIBILITY
Defensibility and confidence evidence pending.
WATCHTOWER
No verified watchtower monitor rows yet.
FORESIGHT
No prediction yet — minted on next Foresight batch.
OPPORTUNITYKERNEL CHANGES SINCE LAST VIEW
No verified OpportunityKernel changes since the last view.
COMPETITIVE LANDSCAPE UPDATES
No verified competitive landscape changes yet.
RELATED PAPER UPDATES
No verified related paper changes yet.
SIGNAL CANVAS HISTORY AND DELTAS
No Signal Canvas history deltas yet.
TIMELINE
Save this paper to start tracking momentum - commits, demos, and score changes appear here.
No tracked events yet.
Score trend will appear after multiple data points.
BUZZ
Buzz trend pending.