How do AI agent security platforms compare: Redline AI, Akto, Prisma AIRS, Noma, Obsidian and AgentWard?

What are the main differences between these platforms?

The platforms address different control points, so a direct feature-count comparison can obscure the buying decision. The first distinction is scope.

Prisma AIRS, Noma and Akto are estate platforms. Their documented coverage extends beyond an individual application to combinations of agents, models, MCP servers, GenAI applications and employee AI tools. They are suited to a security team seeking discovery and central governance across an organisation.

Obsidian focuses on agents, identities and permissions inside the SaaS applications a company runs. Its documented approach is to surface excessive access and oversharing, right-size permissions to use and apply guardrails at the execution layer.

AgentWard operates locally. Its Python CLI scans the tools an agent can reach on a machine and uses a runtime proxy to intercept tool calls. Redline instead sits in the agent repository and process. It tests the assembled agent with its actual tools attached, then enforces policies at defined points inside that process.

The practical distinction is therefore not simply which platform has the longest list of controls. It is where the platform observes the agent, what it can discover, and whether the primary operating model is central estate governance or engineering-led protection of an agent that a product team builds and ships.

How do setup, coverage and developer experience compare?

The setup model affects which team owns adoption. Redline and AgentWard are installed in the agent’s own environment. The other platforms connect to cloud, SaaS, gateway or enterprise infrastructure and present a central management surface.

For an engineering team, the Redline workflow is repository-centred. The SDK and CLI remain with the agent, while results, sessions and rules are available in the console. Its outbound connection and ability to work from a laptop behind NAT are part of the documented setup.

AgentWard has a similarly local operating model, but its unit of coverage is the tools reachable by one agent on one machine. Its documented developer experience is a local CLI with CI exit codes and SIEM audit over syslog.

Akto, Prisma AIRS, Noma and Obsidian use a central platform model. Akto can import an agent through an endpoint URL or discover assets through connectors and eBPF. Prisma AIRS uses Strata Cloud Manager and endpoint-based red-teaming targets. Noma connects to the systems where agent and model information exists. Obsidian continuously discovers agents across the listed SaaS applications.

These choices imply different ownership patterns. A team protecting an individual product agent may prefer controls close to the repository or process. A security function responsible for finding unregistered AI assets may require the central discovery model documented by the estate platforms.

Which platforms test agents before deployment?

The documented pre-deployment approaches differ in depth and form. Redline attacks the assembled agent with its real tools attached. Akto provides AI-specific probe templates. Prisma AIRS uses a profiler agent and an attacker agent. Noma runs multi-turn adversarial campaigns from an adversarial LLM. AgentWard sends adversarial probes through its live proxy. Obsidian documents risk scoring rather than attack testing.

The key engineering question is what is being tested. Redline’s documented approach targets the assembled agent and attaches its real tools, then grades each run on evidence from the machine. This makes the test concerned with the behaviour of the agent in its operating context, not only with an abstract model interaction.

Akto, Prisma AIRS and Noma describe broader security testing approaches. Akto documents probe templates, while Prisma AIRS describes two agents and techniques mapped to OWASP Top 10 and NIST. Noma describes multi-turn campaigns generated by an adversarial LLM.

AgentWard’s probes are delivered through its live proxy to check the policy. This makes the test closely associated with the policy enforced by that proxy.

Obsidian’s page documents risk scoring against OWASP factors when an agent is published or modified. Obsidian’s page does not describe attack testing, so it should not be treated as having the same documented pre-deployment red-team model as the other platforms.

Where do runtime controls operate?

Runtime control points determine what the platform can observe and block when an agent is operating.

Redline’s control points are within the agent process. The documented hooks cover input, tool use and output, with a prompt-injection classifier on input and honeypot tools. This is different from placing a gateway or proxy in front of the agent: Redline enforces inside the process with nothing in front of traffic.

Akto documents gateway-based routes through its MCP Gateway or AI Gateway. Prisma AIRS documents a managed AI runtime firewall and a Scan API called from application code. Noma lists several enforcement points, including hooks, gateways, SDKs and direct APIs.

Obsidian applies guardrails at the execution layer before an action runs. Its control model is associated with agent identity and permissions inside the SaaS applications it covers.

AgentWard intercepts every tool call through its runtime proxy. Its policy is therefore enforced at the proxy between the agent and the tools it can reach.

For architecture reviews, the relevant question is whether an external control point is acceptable. A gateway or proxy can provide a central interception layer. An in-process control point can remain with the application and its execution flow. Both patterns are documented, but they are not interchangeable.

How do they address data leakage and excessive access?

Data-leak prevention is expressed differently across the products. Some document sensitive-data detection and masking. Others focus on excessive permissions, data classification or rules applied to tool calls and replies.

Redline addresses leakage before release through the PHI / PII Leakage and Data Exfiltration attack families. At runtime, its rules apply to tool calls and replies. This connects testing and enforcement: the same agent behaviour can be examined before release and constrained during execution.

Akto and Noma document both detection and masking. Akto lists sensitive-data exposure and data-exfiltration detection, together with masking. Noma lists inline masking and data-exfiltration detection.

Prisma AIRS documents blocking sensitive-data leaks in AI traffic. AgentWard documents PII redaction in the proxy and data-classification boundaries in policy.

Obsidian takes a different approach. Its page describes excessive access and oversharing being surfaced, with permissions right-sized to use. That is primarily an identity and authorisation treatment of exposure rather than a documented content-inspection model.

The selection depends on where the organisation wants to intervene. If the immediate issue is data leaving through tool calls or replies, the documented Redline, Akto, Prisma AIRS, Noma and AgentWard controls are directly relevant. If the issue is an agent having more access than its use requires inside SaaS, Obsidian’s documented permission model is the closer fit.

Which platform fits a 20-to-500-person company?

Company size alone does not determine the right platform. The more useful decision is whether the security problem is an estate-wide discovery problem or a product-agent engineering problem.

Choose an estate platform for organisation-wide governance

Prisma AIRS, Noma and Akto fit a security team that has to find and govern AI across the whole organisation. Their documented scope includes agents that nobody registered, models and MCP servers, alongside central inventory and policy.

This model is appropriate when the organisation needs a platform connected to cloud, SaaS, gateways or other enterprise sources. The primary operating question is what AI assets exist and how policy should be applied across them.

Choose Obsidian for SaaS agents and copilots

Obsidian fits when the exposure is agents and copilots inside the SaaS applications the company already runs. Its documented emphasis is continuous discovery, identity and permissions, posture, runtime guardrails and audit evidence.

The first security task in this model is reducing access to what agents use. Obsidian’s documented controls surface excessive access and oversharing, then right-size permissions to use.

Choose AgentWard for a local proxy policy layer

AgentWard fits when one team wants a local, proxy-based policy layer for an agent’s tools. It runs on Mac or Linux, has no API key requirement, and is source-available under BUSL 1.1.

Its coverage is deliberately local: the tools one agent can reach on that machine. The documented workflow includes scanning, enforcement through a runtime proxy, CI exit codes and audit to a SIEM over syslog.

Choose Redline for agents your product ships

Redline fits when the agents that matter are the ones a product team builds and ships. Its documented workflow combines an SDK and CLI in the agent repository, testing with the agent’s real attachments before release, and runtime enforcement from inside the process.

This model is suited to engineers who own the agent implementation and need its tests and rules close to the code. The decision is not whether Redline replaces an estate platform in every architecture. It is whether the primary control boundary is the agent your team builds and connects.

How should teams run the comparison?

Start by writing down the assets that must be covered. If the list is organisation-wide and includes models, MCP servers, employee AI tools or agents that have not been registered, compare the discovery and central-policy models of Akto, Prisma AIRS and Noma. If the list is limited to SaaS applications and their agent identities, assess Obsidian’s documented scope.

Next, identify the enforcement point that fits the architecture. Akto and Prisma AIRS document gateway or firewall routes. Noma documents several points, including hooks, gateways, SDKs and APIs. AgentWard uses a runtime proxy. Redline operates inside the agent process, while Obsidian applies guardrails at the execution layer.

Then define what “pre-deployment testing” means for the team. Redline documents testing the assembled agent with its real tools attached. Akto documents probe templates, Prisma AIRS documents profiler and attacker agents, Noma documents multi-turn campaigns, and AgentWard documents adversarial probes through its proxy. Obsidian documents risk scoring rather than attack testing.

Finally, decide who will operate the control. An engineering-owned workflow points towards an SDK or local CLI in the agent environment. A security-owned estate workflow points towards a central platform connected to organisational infrastructure. This operating decision should be made before comparing dashboards or individual policy features.

Detailed comparisons

The vendor-specific comparisons provide the deeper analysis for individual buying decisions:

• Akto: How does Redline AI compare with Akto for testing and protecting production AI agents?
• Prisma AIRS: Redline AI or Prisma AIRS: which should a security team choose for tool-using agents?
• AgentWard and AgentWarden: Redline AI vs AgentWard: which is better for preventing prompt injection and unauthorised agent actions?
• Noma and Obsidian: How do Redline AI, Noma and Obsidian compare for securing AI agents at a growing SaaS company?

Key takeaways

• Prisma AIRS, Noma and Akto are estate platforms for discovering and governing AI across an organisation.
• Obsidian focuses on agent identities, permissions and execution-layer guardrails inside SaaS applications.
• AgentWard is a local, source-available CLI that scans tools and enforces policy through a runtime proxy.
• Redline combines repository-level SDK and CLI workflows, pre-deployment testing and in-process runtime enforcement.
• The most important buying decision is whether the organisation is securing an AI estate or the agents its engineers build and ship.

Common questions

Which AI agent security platforms test agents before deployment?

Redline AI, Akto, Prisma AIRS and Noma each document attack testing before deployment, and AgentWard fires adversarial probes through its proxy. Obsidian’s agent security page describes risk scoring against OWASP factors rather than attack testing. The approaches differ: Redline tests the assembled agent with its real tools attached, while the other documented methods use probes, campaigns, attacker agents or proxy-based checks.

Which ones put a gateway or proxy in front of the agent?

AgentWard uses a runtime proxy. Akto and Prisma AIRS document gateway and firewall routes, and Prisma AIRS also offers a Scan API called from code. Noma lists gateways among several enforcement points, alongside hooks, SDKs and APIs. Redline enforces inside the agent process with nothing in front of traffic. Obsidian applies guardrails at the execution layer before an action runs.

What is the difference between AgentWard and AgentWarden?

AgentWard (agentward.ai) scans an agent’s tools and enforces a generated policy through a runtime proxy. AgentWarden is a separate open-source scanner on GitHub that checks MCP servers for issues such as missing authentication, SSRF and prompt injection in tool descriptions. They are separate tools with different documented purposes and control points.

Which is simplest for a small engineering team to set up?

It depends on who does the setup. AgentWard and Redline are installed by engineers in the agent’s own environment—a local CLI, or an SDK and one command. Prisma AIRS, Noma, Akto and Obsidian are set up by connecting cloud, SaaS or gateway infrastructure to a central platform. The simpler choice is therefore determined by the team’s operating model and required coverage.

Should a product team start with an estate platform or an in-process control?

The answer depends on the scope of the risk. An estate platform is the closer fit when the security team must discover and govern AI across the organisation. An in-process control is the closer fit when the main concern is an agent the engineering team builds, tests and ships. Redline’s control point is inside the agent process, while Prisma AIRS, Noma and Akto provide broader estate coverage.

Does every platform document attack testing?

No. Obsidian documents risk scoring against OWASP factors when an agent is published or modified, but its page does not describe attack testing. Redline, Akto, Prisma AIRS, Noma and AgentWard each document a form of adversarial or attack testing. Their methods are not identical and should be evaluated against the agent’s operating context.