Security & Threat Intelligence · 03.08.2026, 11:18 UTC
30 days with Claude Mythos Preview: How Tenable adapted our security program, and why yours is next
| Schweregrad | info |
|---|---|
| Kategorie | Security & Threat Intelligence |
| Quelle | Tenable Research ↗ |
| Veröffentlicht | 03.08.2026 UTC |
Sicherheitsmeldung mit Schweregrad noch nicht bewertet. Technische Details im Tab „Originaltext“; empfohlene Schritte in der Checkliste.
Tenable spent 30 days running frontier AI models against our own code. It didn’t just find bugs — it proved they’re real, with reproducible exploits. That fundamentally changes code security from ranking potential code defects to a much higher signal focused on the findings that matter. Read on to learn how it reshaped our security team's work, what it cost, and why your program is next.Key takeaways:Now code security starts with proof, not suspicions. Frontier AI instantly builds working exploits and proves which flaws are genuinely dangerous in your source code. Now remediations are confirmed issues, not just ranked lists of maybes. The durable asset is the harness, not the model. Frontier AI models get the attention, but the durable asset for security teams is the harness: the orchestration and systems around the model that turn suspected flaws into proven, reproducible exploits engineers can act on. Frontier AI doesn’t replace senior researchers; it makes one as productive as five. The scarce resource is still the expert who writes the threat model and judges what’s real. Buy the compute without funding that person, and you get a very fast way to generate findings no one can use.We’ve been running Claude Mythos Preview against our own code now for over 30 days, and one thing is crystal clear: Code security is fundamentally changing, and we believe there’s no turning back.At Tenable, our security team already had security testing agents that drove our applications, exercised API endpoints, and ran our predefined checks. But until recently, the agents couldn’t handle the …