
AI Security Review Assistant
Reviews designs, architecture changes and new integrations for security risk, using a threat model.
Attempts to hijack your AI agents or chatbots with hidden or malicious instructions are detected and blocked before they reach the model.
Anyone who can type into your chatbot, or plant text in a page your agent reads, can try to rewrite its instructions. This defense screens messages, retrieved documents and tool outputs before they reach the model. Clear attacks are blocked, borderline ones are flagged for a person, and every attempt is logged. You approve the rules and own the log.

AI Prompt Injection Defense screens the inputs, retrieved documents and tool outputs reaching your own AI applications and chatbots. It blocks or flags prompt injection attempts. It protects AI apps you already run, whoever built them. It does not cover general application code or infrastructure security.
A chatbot or agent that follows a planted instruction can leak data, insult a customer or call a tool it should never touch. That is a real cost, and it often surfaces only after someone screenshots it. This defense sits in front of the applications you name and checks what reaches the model, including the indirect content most teams forget. The written scope lists which applications are covered and which controls are configured, so you know what is protected before you buy.
The agent screens inputs reaching your AI applications and chatbots for prompt injection attempts. Suspicious inputs are blocked or flagged before the model acts on them.
Retrieved documents are screened as well as user messages. Text planted in a file or web page can be caught before it reaches the model.
Outputs from tools your AI calls are checked for injection attempts too. An agent is less likely to act on instructions hidden in a tool's response.
Flagged attempts appear in the admin console for your team to review. You can see what was tried and tune the controls that are in place.
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $5,400 |
| Express | 15–25 working days | $6,200 |
| Rush | 10–20 working days | $7,000 |
Before you start: List the AI applications in scope and any known misuse so far. Keep a sample of recent inputs to test against.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
The build price is one-time. Running the defense costs roughly $20 to $300 a month in your own accounts, for hosting, logging and the monitoring tools it relies on day to day.
AI model usage during the build and testing is billed the same way, directly to your accounts, so you keep ownership of every provider relationship involved.
Ask about running costsIf you need something outside the Scope Card, such as coverage across more than three AI applications, add a note at checkout. You get a written Change Quote, and that work only starts once you accept it. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionMonthly maintenance covers monitoring and a monthly allowance of change hours for things such as tuning detection rules or adding a second application. It starts after the 30 days of included support and can be cancelled any month.
$270/mo (5% of the build price a month, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance works| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A guardrail platform charges per request volume, monthly | A security firm quotes after a scoping call | Ours is one fixed price, shown on this page before you buy |
| Scope | A guardrail platform applies one generic rule set across all customers | An agency agrees scope during the engagement | Ours is written on the Scope Card, tuned to your application |
| Delivery | A guardrail platform still needs tuning before it is reliable | A security firm engagement often takes weeks to schedule | Ours has a fixed delivery time shown before you buy, with faster options |
| Coverage | A guardrail platform mainly filters direct user messages | An agency build depends on what was agreed | Ours checks direct input and indirect content like documents and tool outputs |
| Guarantee | A guardrail platform may market a block rate figure | An agency build depends on what was agreed | Ours reduces exposure; no defense blocks every attempt |
No defense can block every possible attempt, and we do not claim otherwise. It reduces your exposure by screening direct messages and indirect content such as documents and tool outputs against known injection patterns, blocking clear attempts and flagging borderline cases for a person on your team to review.
This defense is narrow and specific to malicious input reaching your AI models, such as messages or documents designed to hijack a chatbot's instructions. AI Application Security Agent covers your broader codebase and dependencies instead. They address different risks, and many teams run both together for full coverage.
It is an instruction hidden inside content your AI application reads rather than typed directly by a user, such as text embedded in a webpage, a document, or the output of a tool the agent calls. This defense screens that content too, not only the direct chat messages a person types.
Expect roughly $20 to $300 a month in your own accounts for hosting, logging and the monitoring tools the defense runs on. Most single-application setups sit toward the lower end, and the figure rises gently with traffic. You pay those providers directly, and we add no per-message fee. The one-time build price for each delivery speed is in the price panel on this page.
Borderline cases are logged and routed to Slack for a named person on your team to review, rather than silently allowed through or automatically blocked without any oversight. Clear, high-confidence attempts are blocked outright based on the rules you approved during setup. This keeps the defense cautious about ambiguous cases rather than making a risky call on its own.
Yes, within the three systems included in scope, adding a second application is part of the build. Extending coverage beyond three AI applications, or substantially different applications added later, comes through a Change Quote, priced and agreed with you before that work starts. This keeps costs predictable as your use of AI applications grows over time.
Your named IT or security owner does, using the log this defense keeps of every attempt, the rule it matched and the action taken. We do not review or act on your logs ourselves; monthly maintenance covers tuning the detection rules if attack patterns change over time.
Order AI Prompt Injection Defense and it starts screening input and content reaching your AI application, live on a fixed delivery date.

Reviews designs, architecture changes and new integrations for security risk, using a threat model.

Scans application code and dependencies for security issues.

Reviews your AI applications and agents for common security weaknesses.