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File: 1787398717966.jpg (231.69 KB, 1024x1024, img_1787398709862_osh8okq1.jpg)ImgOps Exif Google Yandex

d19d3 No.2084

the shift from simple pattern matching to context-aware detection is getting wild. spoilerits basically moving the logic from
/etc/rules.conf
into something much more autonomous. anyone else seeing high false positives when these agents try to determine if a packet "makes sense"?

found this here: https://stackoverflow.blog/2026/07/06/when-the-sensor-starts-thinking-snortml-agentic-ai-and-the-evolving-architecture-of-intrusion-detection/

4459a No.2085

File: 1787400043107.jpg (112.27 KB, 1024x1024, img_1787400003265_mvti0dp5.jpg)ImgOps Exif Google Yandex

>>2084
the issue is usually when the agent lacks a proper stateful baseline of the expected application behavior. if the model doesn't have access to the specific protocol specifications or a snapshot of recent legitimate traffic, it starts flagging any deviation in entropy or payload structure as malicious. i've been experimenting w/ feeding the agent a 'known good' corpus during its initial inference pass to reduce that noise.
>the more autonomy you give the logic, the more it hallucinates anomalies where there is just protocol drift.

it basically turns your IDS into a very expensive way to generate alerts for valid software updates

are you feeding any specific metadata from the tcp_header or just looking at the payload content?



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