Superagent Review (2026): Pricing, Features & Honest Verdict

TLDR

Superagent is a runtime security layer for AI agents that inspects every request and blocks prompt injection, malicious tool calls, and data leaks. It is model-agnostic and runs in production or CI. Best for: engineering teams shipping agents. Price: free for open source, then $1.50 per million tokens. Free plan: yes. Rating: 8.1/10.

What is Superagent?

Superagent is a security layer that wraps your AI agents at runtime. It sits between your application, the tools your agent can call, and the model behind it, and it inspects every input and output as they happen. The goal is narrow and useful: stop prompt injections, jailbreaks, malicious tool calls, and leaks of PII or secrets before they cause damage. It is model-agnostic, so it works whether you are on OpenAI, Anthropic, Google, Groq, or Bedrock.

The product comes from the YC W24 team behind the original open-source Superagent, an agent framework that developers already knew. In late 2025 they pivoted the brand to agent security, launching the runtime product on October 1, 2025. The founders, Alan Zabihi and Ismail Pelaseyed, built it because the same autonomy that makes agents useful also makes them a soft target: an agent that reads a web page, clones a repo, or calls an API can be steered by hidden instructions. Superagent is their answer to that gap. The bet is that security has to move to runtime, because you cannot review every prompt, every retrieved document, and every tool response by hand once an agent is loose in production.

What Are Superagent’s Key Features?

Guard

Guard is a purpose-trained safety model that inspects inputs and tool calls before they run. Instead of simple keyword filters, it uses reasoning-driven detection to catch prompt injections, jailbreaks, and malicious tool invocations. When we dug into it, the useful part is that Guard evaluates the actual tool call an agent is about to make, not just the user message, so it can block an exfiltration attempt even when the prompt looks clean. This matters because most guardrail tools only inspect the text a user types. An injection often hides in a retrieved document or a web page the agent reads mid-task, and by then the model has already decided to act. Guard checks the action itself, which is a harder thing to fool.

Redact

Redact is a separate model that strips PII and secrets before data crosses a trust boundary. It filters both inputs and outputs at integration points, so an API key, email, or customer record does not slip into a model prompt or leak back out in a response. For teams handling regulated data, this is the feature that makes agents defensible. The redaction happens at the boundary rather than inside the model, so you are not trusting the LLM to police itself. That distinction is what turns a demo-stage agent into something a security team will actually sign off on.

Scan

Scan analyzes repositories and content for agent-targeted attacks like repo poisoning and hidden malicious instructions. It runs as a PR scan directly inside GitHub and CI/CD, so it slots into your existing pipeline without a separate workflow. If someone plants an injection in a README or config that your coding agent will later read, Scan is meant to flag it at review time.

Red Team and observability

Superagent ships adversarial test scenarios such as prompt_injection and data_exfiltration that chain vulnerabilities to find real exploit paths, so you can test your agent before attackers do. On top of that you get unified observability: live traces, audit trails, and policy controls across every method. That audit trail matters when you need to prove what an agent did and why a call was blocked.

How Much Does Superagent Cost?

Superagent starts at free, and that is not a trial. The full suite, Guard, Redact, and Scan, is free forever on any public repository, with no credit card. For open-source maintainers and solo developers, that covers the whole product.

Paid usage is billed by tokens. The rate is $1.50 per million tokens of customer data, counting both input and output, drawn from pre-paid credits that are shared across all three methods. There are no seat fees. This keeps the entry cost low but ties your spend to traffic, so a high-volume agent will burn credits faster than a light one. Anything involving private repositories moves to a contact-sales conversation, and there is no self-serve tiered table for that, which is the main pricing frustration.

Against competitors, the model is friendlier at the low end. Lakera Guard offers a free developer tier but keeps enterprise pricing quote-based, Prompt Security (now part of SentinelOne) is contact-sales only, and Protect AI from Palo Alto is firmly enterprise. Superagent is the one you can actually turn on today without a sales call, as long as your code is public.

Who is Superagent Best For?

Use Superagent if you are shipping AI agents that call tools, touch user data, or run without a human in the loop. If your agent browses the web, executes code, or reads external content, you have an attack surface, and Superagent is built for exactly that. Open-source teams get the full product free, which makes it an easy yes.

• Use it if you run agents in production and need an audit trail of blocked calls.
• Use it if you handle PII or secrets and want Redact filtering inputs and outputs.
• Use it if your codebase is public, because then the whole suite costs nothing.

It is also a strong fit for teams building coding agents. Scan running as a PR check means a poisoned dependency or a booby-trapped README gets flagged before your agent ever reads it. Named users on the site, including Firecrawl, Nango, and Ubicloud, are exactly this kind of infrastructure-adjacent company, which tells you where the product lands today.

Skip Superagent if you only ship a simple chatbot with no tool access and no sensitive data, because the risk it addresses barely applies to you. Skip it too if you need published accuracy and latency numbers before adopting a security control, since Superagent does not yet release those benchmarks. And if predictable flat-rate billing is a hard requirement, the token model may not suit you, because a chatty agent can run up credits quickly and there is no fixed monthly cap on the usage-based tier.

Best Superagent Alternatives

Lakera

Lakera Guard is the most established name in agent guardrails. It offers a runtime API for prompt injection, jailbreaks, and PII leakage, and it publishes real numbers, including a strong PINT benchmark score and sub-17ms latency. Lakera has a free developer tier, but enterprise pricing is quote-based and not public. Pick Lakera if published benchmarks and a longer track record matter more to you than a free open-source tier.

Prompt Security

Prompt Security focuses on DLP and guardrails for AI traffic across an organization, and it was acquired by SentinelOne in September 2025, which gives it enterprise weight. There is no public self-serve pricing; you talk to sales. It is the better fit for larger companies that already want a vendor with a security platform behind it, rather than developers who want to wire something in this afternoon.

Protect AI

Protect AI, now part of Palo Alto Networks, sits at the platform end of the market, covering model scanning, runtime security, and broader AI supply-chain risk. Pricing is quote-based and aimed at enterprise buyers. Choose Protect AI if you need one vendor to cover far more than agent runtime and you have the budget and procurement process to match.

Final Verdict: Is Superagent Worth It?

Superagent earns its 8.1 by doing the boring, important thing well: it gives AI agents a real security layer without forcing you into a sales call to try it. Guard, Redact, and Scan cover the three failure modes that actually bite (injected instructions, leaked data, and poisoned inputs), and the fact that the full suite is free on public repos makes it trivial to adopt for open-source and side projects. The token pricing is fair for private use, even if it is harder to forecast than a flat plan.

The reasons it is not higher are honest ones. It launched in October 2025, it is a small YC seed company, and it competes against better-funded incumbents that publish accuracy and latency benchmarks Superagent has not yet matched. If you need a proven, benchmarked control with vendor heft, look at Lakera or Protect AI. But if you are a developer shipping agents and you want protection you can turn on today, Superagent is one of the best options in the category and an easy recommendation. Wire it into a public repo first, watch what Guard and Scan flag, and you will quickly see whether it belongs in your stack before you ever pay a cent.