INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 5/21/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
Detecting Data Exfiltration through I2P Anonymity Networks: A Two-Phase Machine Learning Approach arXiv:2605.20546v1 Announce Type: new Abstract: The Invisible Internet Project (I2P) provides strong anonymity through garlic routing and distributed network architecture, making it attractive for legitimate privacy needs. Nevertheless, the same properties can be exploited by malicious actors to steal sensitive information from corporate networks without detection. Current netwo…
https://arxiv.org/abs/2605.20546
sha256:969aa383278c5fd72a1fe3d747ba0cf2be40e23f9f3df020dca832eee23df3f8
What we pulled out
Deterministic extractor (IOC + allowlisted tokens + ATT&CK IDs present in DB).
Indicators
Linked with report → mentions → indicator. Values open the indicator workspace.
No indicators linked for this report.
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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