{
"$type": "site.standard.document",
"bskyPostRef": {
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"uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mmqwql3gbfy2"
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"path": "/t/secbert-to-detect-anomalous-log-entries/176237#post_1",
"publishedAt": "2026-05-26T10:39:02.000Z",
"site": "https://discuss.huggingface.co",
"textContent": "Hi,\n\nI am using the secbert model to build a SIEM application that detects normal and anomalous log entries. I trained the secbert model using CSIC (web) log entries. During inferencing i am finding that the model is detecting even normal entries as anomalous entries.\n\nTo keep the training time reasonable to start with i am using 2000 rows (log entries) to train the model. I am using a set of 4 diagnostic log entries for inferencing - 2 normal and 2 anomalous. the model is detecting all the 4 log entries as anomalous. while looking at the raw logits for the 4 entries, there seems to be a small difference in the raw logits, the risk scores are around the same value.\n\nHow to go about determing what is happenning ? Has anyone used secbert for a similar purpose ?\n\nThanks,\n\nVijay",
"title": "Secbert to detect anomalous log entries"
}