Ceron @getceron
Frontier AI security assessments & pen-tests on your business from $1,500. No findings, no fee. getceron.com Scottsdale, AZ Joined December 2009-
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Did you know: a forgotten DNS record can become an account takeover path. If a subdomain still points to a deprovisioned third-party service, an attacker may be able to claim that resource and inherit traffic, cookies, OAuth redirects, or trust tied to the company’s domain.
Anthropic claims open-source models like GLM 5.3 are as powerful as Mythos at cybersecurity offensive & defensive measures @getceron anthropic.com/research/glm-5…
JUST IN: OpenAI & Anthropic are investigating tens of thousands of internal AI agent security incidents Is your business protected? Getceron.com
Protect your vibe coding security, at no risk to you. getceron.com/blog/vibe-codi…
The goal isn’t to make teams afraid to ship AI. It’s to know where trust actually breaks before your customers find out for you. That’s the idea behind Ceron: Proof before production. Fixed-scope AI security audits. No findings, no fee. Getceron.com
Most teams shipping AI agents are testing whether the model functions Far fewer are testing what happens when the model is wrong, manipulated, or given a malicious instruction That’s the security gap that NEEDS focus. 🧵
Then inspect secrets. API keys, session tokens, environment variables, credentials, internal endpoints. If the model can access a secret, you should assume a hostile instruction may eventually try to extract or misuse it. “Hidden from the UI” ≠ inaccessible.
Then inspect identity. Whose permissions is the agent borrowing? A user’s? A service account’s? An admin token? An agent should never inherit more authority than the task requires. Least privilege matters even more when reasoning is probabilistic.
Read: The AI Arms Race by Mario Getceron.com/blog/the-ai-ar…
@orenyomtov Honestly this is the dream workflow: point a model at your own stack, sleep, wake up to a real finding. The scary part is attackers run the same loop now. The only difference between your story and a breach story is who pointed the model first.
@akshay_pachaar Runtime recording is the part most teams skip until after their first incident. If you can't answer "what did the agent touch in the last 24 hours," you can't scope a compromise. Local-first is the right call: nobody should ship agent traces to a third party for this.
@gastronomy Supply chain is the scariest vector for small teams: you can do everything right internally and still get owned through a dependency. With agents compressing intrusions to hours, per the Unit 42 report, a poisoned dependency becomes a nasty force multiplier.
@harleyfoote_ @gastronomy The question I keep coming back to: is the fix architectural, typed tool channels that never mix instruction and data, or do we just need models better at provenance? The former feels shippable today, the latter feels like wishful thinking.
@TambaClan Agree. The layer teams most often skip is treating tool outputs as untrusted input too. A lot of real injection chains now ride in through tool results rather than the user prompt itself, so output-side validation matters as much as input-side.
@techspence Not quite. The agents didn't find zero-days, they exploited basic hygiene failures: a public API, hard-coded tokens, creds sitting in repos. The job isn't gone, it just moved upstream to making sure there's nothing worth finding.
@endswithay @ThriveCapital @khoslaventures @mlevchin @tbpn Congrats on the raise, Andrew! 70X growth in a year is incredible. Rooting for you and the team.
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