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Received yesterday β€” 2 June 2026 ⏭ /r/netsec - Information Security News & Discussion
Received β€” 1 June 2026 ⏭ /r/netsec - Information Security News & Discussion

r/netsec monthly discussion & tool thread

Questions regarding netsec and discussion related directly to netsec are welcome here, as is sharing tool links.

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  • All discussions and questions should directly relate to netsec.
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As always, the content & discussion guidelines should also be observed on r/netsec.

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submitted by /u/albinowax
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Received β€” 31 May 2026 ⏭ /r/netsec - Information Security News & Discussion
Received β€” 29 May 2026 ⏭ /r/netsec - Information Security News & Discussion

1,001 IPs, 64 countries, one operation: mapping a botnet by its back end Β· HoneyLabs blog

We found a cluster of 1,001 IPs across 306 networks and 64 countries, tied to eight shared staging servers and a single TLS and HTTP fingerprint that appears nowhere else, plus smaller botnets that fall into clean separate islands.

submitted by /u/Honeylabs
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I evaluated 5 LLM agents on patching real-world CVEs. Here is what I found.

I built an independent benchmark with 20 real CVEs across 15 CWE categories, 5 models (3 OpenAI, 2 Poolside Laguna), three prompt conditions: full advisory, behavioral description only, and location only (file and function, no description of the flaw).

I have three findings worth sharing:

  • No model reliably fixes real vulnerabilities. The best solve rate (gpt-5.5) is 50% overall and 60% under the most favorable condition. The failure modes (e.g, wrong-search drift, budget exhaustion mid-implementation, plausible-but-incomplete patches that pass every visible test) are structured and repeatable across models and tasks.
  • Token cost varies 4x for equivalent outcomes. The Laguna models consume 3–4x more tokens than OpenAI models of the same capability tier, with no improvement in solve rate.
  • The locate condition is the benchmark's sharpest instrument. Give a model only a file and function (no description of the flaw). Every model drops. The differences between models are within noise at this scale, but it's the condition that most closely resembles what a security researcher actually does: reading code cold and recognizing independently that something is wrong.

Benchmark code and evaluation traces are open sourced.

submitted by /u/Fickle-Box1433
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Received β€” 28 May 2026 ⏭ /r/netsec - Information Security News & Discussion
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