Alphabetical, not ranked. Membership includes primary and secondary research categories. These products have different scopes; inspect the evidence profile before comparing capabilities.
Primary category
Configurable safeguard service inside Amazon Bedrock that evaluates user inputs and model responses against content filters, denied topics, sensitive information filters and word filters, including a prompt attack category. It can be applied at inference or via a standalone API, but does not authorize agent tool calls.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me a Bedrock guardrail blocking a prompt attack and masking PII for a Bedrock Agent, then show the same guardrail invoked through ApplyGuardrail for a non-Bedrock model.
Read sources and limitations →
Also covers this layer
Capability of AppOmni's SaaS security platform that surfaces AI agents running inside connected SaaS tenants - such as Salesforce Agentforce, ServiceNow Now Assist and Microsoft 365 Copilot - including agents enabled without security review, with their declared tools, identities, permissions and over-privilege findings. Discovery depends on AppOmni's SaaS API connections.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Demonstrate listing every Agentforce and Now Assist agent in our tenants, flagging which ones were enabled without approval and which hold write or destructive permissions.
Read sources and limitations →
Also covers this layer
Astrix discovers AI agents, MCP servers, service accounts, OAuth apps, API keys and other non-human identities across cloud, SaaS, CI/CD and vaults, maps each to a human owner in an identity graph, and applies agent policies plus onboarding and offboarding actions. Enforcement depth outside integrated platforms is unclear.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me the identity graph for one shadow agent — its NHIs, credentials, reachable resources and owner — then apply a policy that blocks it and offboard it.
Read sources and limitations →
Primary category
Microsoft API in Azure AI Content Safety that analyses user prompts and supplied documents for adversarial instructions, returning attack-detected flags for direct user prompt attacks and indirect attacks embedded in external content. It is a detection endpoint that applications must act on rather than an enforcement gateway.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me a shieldPrompt call flagging an indirect injection hidden in an uploaded document, and how the calling agent enforces a block based on that response.
Read sources and limitations →
Primary category
Runtime protection for AI agents that inspects prompts, reference material, tool responses and tool descriptions for injections and manipulation, applies tool allow and deny lists, and flags actions outside an agent's mandate. Also builds an inventory of agents and connected MCP servers across supported agent platforms.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me Check Point AI Guardrails detecting an injection hidden in a tool response and blocking the resulting tool call, plus the agent inventory entry for that agent's MCP servers.
Read sources and limitations →
Primary category
Apache-2.0 Python tool from Cisco's AI Defense group that scans MCP servers, their tools, prompts and resources plus server source code, combining YARA rules, LLM-based analysis and Cisco's hosted inspection API, and audits dependencies and bundled binaries. Full detection depth depends on optional third-party services.
open_source · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me a scan of an untrusted MCP server package that flags a docstring-versus-implementation mismatch, and which findings required the Cisco AI Defense API.
Read sources and limitations →
Also covers this layer
Cloud Security Alliance assurance program extending its STAR registry to AI services, with a Level 1 self-assessment against the AI Controls Matrix questionnaire, an automated validation option, and a Level 2 tier referencing third-party certification. Registry-based transparency for AI providers rather than a regulatory conformity assessment.
service · Research snapshot 2026-09-06
- Ask for a demonstration
- Demonstrate a completed AI-CAIQ submission for an agent platform and what the Valid-AI-ted scoring adds over a plain Level 1 self-assessment.
Read sources and limitations →
Also covers this layer
Entro inventories non-human identities, secrets and agentic AI deployments across cloud, code, CI/CD, on-prem and SaaS, links each agent to the NHIs, entitlements and secrets it uses and to a human owner, and monitors agent behaviour for anomalies through its NHIDR detection engine. Credential issuance is not part of the evidenced scope.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me an agent's NHI lineage — creator, secrets used, entitlements, resources touched — and a live NHIDR alert for anomalous agent behaviour.
Read sources and limitations →
Also covers this layer
Apache-licensed LLM vulnerability scanner maintained by NVIDIA. It fires static, dynamic and adaptive probes at a model or dialog system to test for jailbreaks, prompt injection, toxicity, data leakage and misinformation, logs each generation and detector verdict, and outputs a report with failure rates and hit logs.
open_source · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me a garak scan of my chatbot with the probe-by-probe failure rates and the hit log for successful jailbreaks.
Read sources and limitations →
Also covers this layer
French vendor pairing an open-source Python testing library with a delivered assessment service. Automated and expert-led testing probes conversational agents for prompt injection, data disclosure, sycophancy, hallucination and inappropriate refusals, returning a severity-ranked vulnerability report and a signed go/no-go deployment recommendation.
hybrid · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me a full assessment report for my customer-facing agent, with vulnerabilities ranked by severity and the go/no-go deployment recommendation.
Read sources and limitations →
Primary category
Google Cloud service that screens LLM prompts and responses for prompt injection, jailbreaks, unsafe content and sensitive data, optionally returning sanitised text. Integrations extend screening to Google-managed MCP server traffic and the Gemini Enterprise agent platform, while the Agent Gateway integration is documented as preview.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me Model Armor floor settings screening traffic to a Google-managed MCP server, blocking an injected prompt, and clarify which agent integrations are GA versus preview.
Read sources and limitations →
Primary category
Open-source guardrail framework from Meta that runs layered scanners around agent execution: PromptGuard 2 for jailbreak detection, Agent Alignment Checks that audit chain-of-thought for goal misalignment, and CodeShield static analysis of generated code. Meta describes the alignment auditor as still experimental.
open_source · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me LlamaFirewall scanning an email agent's inputs with PromptGuard 2 and flagging an indirect injection through Agent Alignment Checks, including the experimental caveats.
Read sources and limitations →
Also covers this layer
UK vendor running automated red-team tests against AI models, applications and agents. It profiles the target, enumerates attack surface, executes techniques from a maintained attack library via CLI or SDK, and reports exploitable findings with remediation guidance. Documentation covers testing mechanics rather than audit, retention or access controls.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me an automated red-team run against my production agent, including which attack techniques were executed and the remediation guidance produced.
Read sources and limitations →
Also covers this layer
Module of Netskope One AI Security that discovers AI assets - corporate or personal, managed or shadow, cloud or on-premises - from the vendor's SSE/proxy vantage point and maps them to the identities, data stores and tools they connect to, adding risk correlation and response. Discovery leans on traffic and platform telemetry rather than code scanning.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me the asset-to-identity-to-data-store map for a shadow AI application discovered from our traffic, including any MCP servers it reaches.
Read sources and limitations →
Primary category
Barcelona-based platform combining an agent gateway (TrustGate) with runtime protection over the models, tools, MCP servers and data agents touch. Documented gateway behaviour includes per-user and per-tool RBAC, end-user identity forwarding across hops and cryptographic audit trails, with SaaS, hybrid and air-gapped deployment options.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me TrustGate forwarding end-user identity through two agent hops while denying a payments API tool for that user, plus the cryptographic audit record of each tool call.
Read sources and limitations →
Primary category
Platform that inventories agents, MCP servers, skills and models across endpoints, SaaS agent builders and homegrown AI stacks, maps each agent's permissions and data access, red teams them before production, and evaluates runtime actions to alert, block, mask data or route to a human. Claims rest on vendor pages.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me Noma discovering an unapproved MCP server on a developer laptop, mapping its blast radius, and then routing a risky agent action to a human for approval.
Read sources and limitations →
Primary category
Open-source Python toolkit that intercepts LLM application inputs, outputs and custom action calls, applying configurable rails written in YAML and Colang to block or modify content. The guardrail catalogue includes jailbreak detection, PII handling and agentic security checks; the repository labels the release beta and not production-recommended.
open_source · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me NeMo Guardrails applying an execution rail around a tool-calling action plus jailbreak detection, and explain the beta production caveat in the repository.
Read sources and limitations →
Also covers this layer
Module of Obsidian's SaaS security platform that builds a continuously updated inventory of AI tools and agents by combining a managed browser extension, API integrations into SaaS tenants, and mapping of agent-to-MCP connections. Aimed at security teams; agent coverage depends on which SaaS tenants and endpoints are instrumented.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me an agent discovered only by your browser extension that never appeared in the SaaS platform's own API-reported agent list, with its creator, permissions, and MCP connections.
Read sources and limitations →
Also covers this layer
OpenSSF-backed specification with an Apache-2.0 library and CLI that signs and verifies machine learning model artifacts using Sigstore, self-signed certificates, public keys or PKCS#11 devices, producing signature bundles that let consumers check model integrity and provenance before deployment or reuse.
open_source · Research snapshot 2026-09-06
- Ask for a demonstration
- Demonstrate signing a multi-gigabyte model with Sigstore and verifying the signature in a deployment pipeline gate, including what the bundle attests to.
Read sources and limitations →
Also covers this layer
Inline enforcement layer that inspects prompts, plans, tool calls, generated commands and data payloads before execution and returns an allow, block or redact decision, with a companion MCP gateway applying least-privilege controls and trust zones. Evidence comes from vendor product pages rather than reference documentation.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me the Semantic Firewall blocking a shell command produced by an injected instruction and redacting a bulk data read, with the policy that produced each decision.
Read sources and limitations →
Primary category
Israeli platform covering the AI agent lifecycle: cataloguing agents, models, prompts, MCP servers and coding agents through agentless integrations, then applying runtime guardrails that monitor prompts, tool calls and commands for prompt injection, tool poisoning and data exfiltration. Product claims come from vendor pages, not reference docs.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me Pillar validating that an agent's tool call matches its declared schema, flagging a permission-scope deviation, and blocking a poisoned instruction in an agent-to-agent handoff.
Read sources and limitations →
Primary category
Palo Alto Networks security service that scans prompts and model responses via API or network enforcement to detect prompt injection, sensitive data leakage and malicious content, with agent-focused detections such as MCP threat detection, tool chaining attack analysis and privilege misuse. Delivered as a managed enterprise service.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me Prisma AIRS scanning an agent request through the AI Runtime API, flagging a tool chaining attack and a prompt injection, and the security profile that blocked it.
Read sources and limitations →
Also covers this layer
Open-source evaluation and red-teaming tool that generates adversarial inputs from configurable plugins, runs them against an LLM application, and grades outputs with deterministic and model-graded metrics in CI. The paid enterprise editions add RBAC and team scoping; audit logging and retention are not documented.
hybrid · Research snapshot 2026-09-06
- Ask for a demonstration
- Demonstrate an end-to-end red-team scan of my deployed agent, including which plugins ran and how findings are scoped to a team.
Read sources and limitations →
Also covers this layer
MIT-licensed Python framework from Microsoft for probing generative AI systems for risk. It is aimed at security engineers running automated adversarial testing campaigns rather than at governance teams, and the repository provides no multi-user controls, evidence retention or reporting workflow of its own.
open_source · Research snapshot 2026-09-06
- Ask for a demonstration
- Demonstrate an automated PyRIT attack run against my deployed model endpoint and show what artefacts the run leaves behind.
Read sources and limitations →
Primary category
Apache-2.0 command line scanner that discovers locally installed agent components — harnesses, MCP servers, skills — and checks tools, prompts and resources for prompt injection, tool poisoning, cross-origin escalation and tool changes, with a proxy mode that inspects live MCP traffic. Some checks call Snyk's hosted API.
open_source · Research snapshot 2026-09-06
- Ask for a demonstration
- Demonstrate scanning our developers' MCP configurations and show what a tool-poisoning and rug-pull finding looks like, plus which checks require the hosted API.
Read sources and limitations →
Also covers this layer
AI-BOM and inventory module of the SPLX platform, now part of Zscaler. It connects to cloud platforms, code repositories and ML/AI platforms to detect LLMs in use, scan repositories to map agents, tools and MCP servers in AI workflows, and run risk assessments on discovered agents. Detection is scan-based, not user-traffic based.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me the agentic workflow map produced from scanning one of our repositories, including each agent, its tools, and the MCP servers it connects to.
Read sources and limitations →
Primary category
Runtime security product for AI agents that inspects prompts, reasoning steps and tool calls across coding assistants, productivity copilots and custom agents, blocking direct and indirect injection, destructive actions such as file deletion, and data exfiltration. Vendor pages also describe shutting down rogue agents and connections.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me Defend AI blocking an indirect injection delivered in an email to a productivity copilot and stopping a coding agent from deleting files, then show the rogue-agent shutdown action.
Read sources and limitations →
Also covers this layer
Part of Valence's SaaS security platform: it inventories sanctioned and unsanctioned SaaS and AI applications, and continuously identifies OAuth tokens, API keys, connected apps and service accounts linking business SaaS tenants to third-party AI tools. Detection is API-based against connected SaaS tenants, so unconnected apps stay invisible.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Demonstrate how you surface an OAuth grant that connects an employee's unsanctioned AI tool to our Google Workspace tenant, including the scopes granted and the granting identity.
Read sources and limitations →
Primary category
Runtime security layer for AI agents that analyses full execution sequences, including chained tool calls, retrievals and agent-to-agent handoffs, to detect direct and indirect prompt injection, unauthorised tool invocations and sensitive data leaving through agent activity, with inline blocking. Evidence is drawn from vendor platform pages.
commercial · Research snapshot 2026-09-06
- Ask for a demonstration
- Show me AIDR detecting a slow-building indirect injection across several turns, blocking the unauthorised tool call it triggers, and the agent-to-agent handoff record.
Read sources and limitations →