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Pretrained, Frozen, Still Leaking: Auditing Cross-Encoder Attribute Transfer in EEG Foundation Models
arXiv:2606.09189v1 Announce Type: new Abstract: EEG foundation-model releases are usually audited one endpoint at a time: raw-reconstruction, membership inference, identity linkage, or DP-SGD on the downstream head. We audit the same released embeddings under all four endpoints jointly, on BIOT, LaBraM, and EEGPT, and show that each single-endpoint audit clears releases that still leak spectral attributes. The decisive evidence is a cross-encoder transfer audit: a single ridge attribute...
Another KPMG leader steps aside amid audit leak scandal fallout
KPMG Australia chief operating officer Eileen Hoggett steps aside as audit leak fallout widens Wed 3 Jun 2026 at 4:32pm In short: Eileen Hoggett's move marks another major change in the firm's leadership team after the chief executive and head of audit resigned last week. Ms Hoggett will return to a full-time audit role as investigations continue. The changes come after publicly aired revelations by a whistleblower that auditors at the firm had misused confidential client documents.
ASIC names two KPMG partners it is formally investigating over audit scandal
ASIC names two KPMG partners it is formally investigating over audit scandal Fri 5 Jun 2026 at 5:15pm In short: ASIC has named KPMG's former chief operating officer Eileen Hoggett and audit partner Paul Rogers as two of the individuals it is investigating over the audit scandal. ASIC told a Senate estimates committee today it was formally investigating KPMG and that it still had eight current contracts with the firm. Current and former KPMG partners will appear before a parliamentary inquiry...
AuditFraudBench: Benchmarking Audit Judgment in Detecting Fraudulent Misstatements
Announce Type: new Abstract: Large language models (LLMs) have shown strong performance in financial analysis and surface-level factual error detection, yet their ability to identify fraudulent financial misinformation in audited corporate reporting remains underexplored. Existing financial and audit benchmarks mainly focus on factual verification, numerical reasoning, rule compliance, or audit workflows, but rarely evaluate misleading disclosure narratives or management explanations that...
How Reliable are Fairness Audits with Unreliable Data?
Announce Type: replace Abstract: Fairness audits are a key component of responsible machine-learning deployment. Yet, the reliability of audit recommendations under incomplete protected-label access is still poorly understood. In this work, we focused on protected-label missingness in fairness mitigation audits.
Decoupled Smart Contract Audits: Lightweight LLM Framework via Distillation and Aggregation
Announce Type: new Abstract: Smart contracts face critical security challenges that require thorough auditing in decentralized web services. While Large Language Models (LLMs) have shown promise in automated vulnerability detection, existing approaches lack severity evaluations with actionable remediation and demand unnecessarily massive computational overhead. In this study, we introduce an efficient end-to-end smart contract security audit framework utilizing lightweight, highly optimized...
Detectability in Diversity: Improved Canary Crafting for Privacy Auditing in One Run
arXiv:2605.27292v2 Announce Type: replace Abstract: Privacy auditing aims to empirically assess privacy leakage in machine learning models using membership inference attacks (MIAs), and to derive lower bounds on differential privacy (DP) parameters. Recent one-run auditing methods address the high cost of standard approaches by relying on a single training run with multiple "canary" points whose inclusion or exclusion must be detected by the auditor. In this work, we study the problem of...
Talk is (Not) Cheap: A Taxonomy and Benchmark Coverage Audit for LLM Attacks
arXiv:2605.15118v2 Announce Type: replace Abstract: We introduce a reusable framework for auditing whether LLM attack benchmarks collectively cover the threat surface: a 4$\times$6 Target $\times$ Technique matrix grounded in STRIDE, constructed from a 507-leaf taxonomy -- 401 data-populated and 106 threat-model-derived leaves -- of inference-time attacks extracted from 932 arXiv security studies (2023--2026). The matrix enables benchmark-external validation -- auditing collective coverage...
Auditable Climate Risk Intelligence from Fragmented ESG Data: Deterministic Orchestration and Imbalance-Aware Learning for Scope 1-3 Validation
Announce Type: new Abstract: ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation pipelines lack provenance aware auditability, hidden drift detection, and reproducibility oriented governance. This paper proposes a deterministic climate risk intelligence framework integrating single source of truth orchestration, temporal anomaly detection, imbalance aware ensemble learning, and explainability...
On the Shoulders of Giants: Empowering Automated Smart Contract Auditing via the GiAnt Corpus
arXiv:2606.07363v1 Announce Type: new Abstract: High-quality smart contract auditing datasets are crucial for evaluating security tools and advancing smart contract security research. Two major limitations of existing datasets are the manual-induced scalability bottleneck and the deficiency in data granularity and diversity.