specter
We attack your AI before someone else does, then harden it until it holds.
specter is the geist platform for AI security and red teaming, and it is our core strength. When a company uses AI, that AI can also be tricked, manipulated or made to leak secrets. specter tests AI systems the way a real attacker would, on your behalf, to find the gaps first and close them.
Most providers ship a chatbot and move on. We attack the same systems we build, probing for prompt injection, jailbreaks and data exfiltration, until they hold. The result is security you can show an auditor, not a promise on a slide.
What it does
LLM red teaming and jailbreak tests
On your behalf, we try to make your AI do things it should not, then report the exact weakness. We test whether your support bot can be talked into revealing internal discounts or data.
Prompt injection audits
We check whether someone can slip hidden commands into your AI through concealed text in input or your RAG pipeline. A doctored document should never be able to steer your AI off course.
Hardening against jailbreaks
We rebuild your system prompts and guardrails so the model can no longer be tricked into forbidden answers. Hardening means it holds up after we are done, not just on the day of the test.
Data exfiltration tests
We probe whether the AI gives away confidential data, customer records or internal keys under clever questioning, so a leak is found by us and not by an attacker.
Agent security audits
For AI that takes actions itself, such as sending email or placing orders, we check whether it can be tricked into doing the wrong thing, like transferring money by mistake.
Adversarial testing and pen testing
We use uncensored models as attack tools to find gaps a normal test would miss, run AI bug bounties, and speed up classic penetration testing with AI in the loop.
Before a retailer launched its customer chatbot, specter ran a red team engagement against it. Within the test we coaxed the bot into revealing an internal discount policy through a layered prompt injection, then rewrote its system prompt and guardrails so the same attack returned nothing. The launch shipped with a report the board could read.
What you get
- Vulnerabilities found by us first, before a real attacker or a regulator finds them
- Prompt injection, jailbreaks and data leaks tested against, not assumed away
- Guardrails and system prompts hardened so they hold after the test
- A clear report you can show an auditor, a board and your customers
- Tested against OWASP LLM Top 10 and aligned with NIST AI RMF
Questions
Do you only test AI you built, or ours too?
What do we actually get at the end?
Why is red teaming your core competency?
Let us attack your AI first
Book half an hour with us and we will scope a red team engagement for the AI you run today.
