What we still need to verify : 3 points in this profile are not yet confirmed against vendor documentation.
- Current product module names and how testing and runtime are packaged: verify against vendor docs
- Integration surface for runtime enforcement, proxy versus SDK versus gateway: confirm
- Supported model providers and agent frameworks: confirm
Treat these points as unconfirmed. They are open items in the catalog's verification queue, and this note stays until each is checked against the vendor's documentation.
What it does
Straiker approaches AI application security from two directions that are usually sold separately. The first is automated adversarial testing: point the platform at a deployed AI application or agent, and it generates and executes attack attempts against it, covering prompt injection, jailbreaks, data and system prompt extraction, harmful output, and misuse of whatever tools or actions the agent exposes. The generation is application aware rather than a fixed payload list, meaning attacks are shaped by what the application appears to do and what it is connected to, and findings come back as reproducible conversations rather than rule identifiers.
The second is runtime inspection. Prompts and responses pass through a control that evaluates them in line and can block, redact or flag, applying policy to sensitive data appearing in output, injected instructions arriving in retrieved content, and tool calls outside what the application should do. The argument for buying both from one vendor is the feedback loop: test findings inform what the runtime control watches for, and runtime events feed back as test cases. That is a real advantage when it works, and a coupling risk when you later want to replace half of it.
Where it fits
Pre release and production, with the security team as primary operator rather than the application developers. Testing runs against a deployed or staging endpoint, so it needs an application far enough along to be callable and an accurate description of its intended behavior. Runtime enforcement needs a place in the request path, which is an architectural commitment rather than a configuration change.
Strengths
- Covers both assessment and enforcement, avoiding the common situation where red team findings have no control to land in.
- Attack generation shaped by the application under test produces more relevant findings than generic payload lists.
- Agent specific concerns, particularly unsafe tool invocation, are treated as first class rather than an afterthought to content filtering.
Limitations
- Young vendor in a fast moving category with limited independent evaluation. Run your own bake off, and expect automated findings to need human triage.
- An inline control adds latency to every request and becomes a hard dependency on a third party service.
- Runtime inspection means prompts and responses, including whatever user data they carry, are processed by the vendor. That is a procurement question before a technical one.
Who it suits
Teams shipping customer facing AI applications or agents who need both evidence of testing and an enforcement point, and would rather buy the pair than assemble it. Less suited to teams with strong internal red team capability, or anyone unable to place a vendor service in the production request path.
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