Captured record
report:3696:titleHeadline captured
arXiv — Cryptography & Security (cs.CR) recorded this headline on Aug 25, 2026. No lawful structured evidence is available yet to explain the underlying event.
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Brief status
Headline captured
Evidence records
1
Structured pivots
0
Publisher text
Available
Forensia structured brief
Only the source headline is captured. Forensia will not present a generic provenance summary as a threat brief.
Captured record
report:3696:titlearXiv — Cryptography & Security (cs.CR) recorded this headline on Aug 25, 2026. No lawful structured evidence is available yet to explain the underlying event.
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source brief
source-authored · cleanedarXiv:2608.21803v1 Announce Type: new Abstract: As machine learning (ML) models are increasingly deployed in high-stakes environments, explainable AI (XAI) methods like SHAP and LIME have become essential for regulatory compliance and trust. However, the current auditing paradigm relies on an implicit "chain of trust" where third-party auditors are assumed to be trusted. Recent research demonstrates that this assumption is flawed and adversarial auditors can manipulate XAI explanations through manipulation attacks such as output shuffling or scaffolding out-of-distribution (OOD) to conceal mod
Cleaned from source-provided descriptive text. This is not independent Forensia analysis. Open the original for the publisher's complete reporting.· sha256:77c1adf3461a23b0…
No structured IOCs, malware families, threat actors or ATT&CK techniques were extracted from this source document.
evidence set
1 recordsGrouping means the records share event anchors. It does not prove that every publisher independently verified the claims.
rights & provenance
Coverage state measures available context, not whether every claim is true or independently corroborated. Unknown publication rights fail closed to metadata and the original source link.
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