INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 7/7/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
PPE-Bench: A Benchmark for Evaluating MLLM Unlearning under Private-Public Entanglement arXiv:2607.02897v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown strong capabilities, but they may memorize private information from web data, raising privacy concerns. Machine unlearning offers a way to remove such private knowledge without retraining from scratch. However, existing MLLM unlearning benchmarks have two major limitations. First, they rely…
https://arxiv.org/abs/2607.02897
sha256:929f7911b12519fc6dcc15515ccb01fcce139a2e526d46de4b3accd9dd48e418
What we pulled out
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Indicators
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Malware families
Allowlist token matches only.
Threat actors mentioned
Allowlist mentions — not a formal attribution verdict.
ATT&CK techniques
MITRE IDs referenced in text and present in local technique table.
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