42Crunch, Cequence Security, Levo.ai and Wallarm

About Cequence Security

Cequence Security sells a single platform that combines agentic AI governance, API security, bot defense and web app protection. Cequence says the platform welcomes legitimate traffic and shuts out abuse.^[5]

Cequence says its platform gives organizations the security, governance and control they need to protect their applications and data against attacks, business logic abuse and fraud. Cequence says that core technology now extends to securing the AI agents and workflows modern enterprises depend on.^[6]

Cequence analyzes behavioral intent so good agents transact smoothly while fraud, abuse and account takeover are kept at bay. Cequence says the platform distinguishes humans and bots, and legitimate automation from threats. Cequence says the platform continuously evaluates live traffic to identify threats in real time and trigger countermeasures. Cequence says its detection runs independent of the client. Cequence also says customers do not need to replace their CDN, because Cequence is separate from the delivery network.^[5][6]

Cequence API Security is an AI-first solution that discovers, monitors and tests APIs. Cequence API Security assesses a broad range of risks that can lead to compliance or governance issues, data loss and business disruption. Cequence API Security discovers internal, external and third-party APIs. Cequence integrates with existing infrastructure such as API gateways, or can be deployed inline. Cequence identifies and masks sensitive data using ML-based rules with predefined and customizable data patterns. Cequence API Security test plans can be generated automatically from Postman collections or API specifications. Cequence API Security exposes every capability as MCP tools.^[7]

Cequence AI Gateway contains every agent wherever it runs and governs its actions in real time, across any model, MCP server, API or application, at enterprise scale. Cequence says its Agent Personas scope every agent to the tools, APIs, skills and LLMs its job requires. Agent Behavior Protection evaluates each tool call in the context of the full session. Agents authenticate with Agent Access Keys while the gateway brokers backend tokens, so agents never have direct access to backend credentials. Prompt Guard detects prompt injection, override instructions and safety filter bypass attempts before they reach a model or tool. Cequence AI Gateway can monitor, redact and block sensitive data across more than 100 out-of-the-box detection types. Budgets in Cequence AI Gateway cap spend per employee, team and agent persona, by day or by month. Trusted registries of MCP servers, APIs, LLMs and skills define exactly what agents can connect to.^[8]

Cequence takes a network-based approach that monitors all API transactions to protect against AI bot attacks, IP scraping and sensitive data exposure. Cequence says its approach requires no application modification. Cequence discovery identifies and inventories all APIs in use, whether they are internal, external or third-party. Cequence actively monitors API transactions, including GenAI and agentic AI APIs, for inappropriate sensitive data flows. Cequence describes business logic abuse as targeting the intended functionality of applications and APIs rather than exploiting traditional technical vulnerabilities. Cequence says it protected multiple major telecommunications companies from a series of six high-profile BOLA API attacks.^[9][10][11]

Cequence describes use cases that include stopping credential stuffing and brute force attacks before attackers seize legitimate user accounts. Cequence describes use cases that include neutralizing scalper bots that buy out high-demand inventory before real customers can. Cequence describes use cases that include blocking bots that enumerate account numbers and drain gift card and rewards balances. Cequence describes use cases that include identifying and redacting PII, credentials and regulated data moving through API traffic in real time. Cequence says PCI DSS v4.0.1 includes provisions that require capabilities found in Cequence API Security and Bot Management, including API discovery and sensitive data identification and masking. Cequence describes digital banking platforms, mobile apps, payment systems, trading portals, partner integrations and open banking initiatives as relying on interconnected APIs to move money and data in real time.^{[1][3][5][6][7][12][13][14]}

About Levo.ai

Levo.ai sells a security platform for APIs and AI assets, covering discovery, visibility and protection for API driven systems. Levo discovers and inventories APIs, AI agents, MCP servers, LLMs and vector stores through eBPF-powered runtime visibility. Levo captures auth scopes, identities and data flows across APIs and AI assets. Levo dynamically tests agents, LLMs, MCP servers and APIs for prompt injection, tool abuse, collusion and misconfigurations. Levo tracks drift, anomalies and policy violations across agents, LLM sessions, MCP orchestration and API calls. Levo enforces protection inline across APIs, agents, MCP servers and LLMs.^[1][2][9]

Levo says that as enterprises adopted agents, LLMs, MCP servers and autonomous toolchains, traditional edge controls could not see or explain their behavior. Levo describes the resulting risk surface as machine-to-machine calls, prompt injection, data leakage and privilege misuse. Levo applies kernel level visibility, passive observability and dynamic security testing. Levo ties vulnerabilities in APIs, agents, MCP servers and LLMs to real traffic traces. Levo detects PHI, PII and secrets inside API payloads, AI prompts, embeddings and vector queries without sending them to the cloud.

Levo's AI Firewall is a security and compliance layer for in-house AI applications. Levo gives visibility into AI transactions across prompts, agents, tool calls, API calls and downstream actions. Levo applies AI-aware data protection inline to prevent sensitive data from being exposed through prompts or responses. Levo controls can redact, mask, block or route events to workflows based on risk and business context. Levo enforces boundaries on what agents can do, which tools they can call and what parameters they can pass, inline and in real time. Levo prevents sensitive system prompts and internal instructions from leaving the environment.^[6]

Runtime AI Visibility is Levo's kernel level, eBPF powered view of the AI control plane, covering agents, MCP servers, LLMs and AI applications. Levo auto discovers external and internal LLMs, agents, MCP servers, AI apps, gateways, embeddings and vector stores, building a continuous AI bill of materials with ownership and lineage. Levo traces prompts, responses, tokens and downstream API calls across agents, MCP servers and LLMs. Levo maps who authorized an action versus who executed it, attributes non-human identities, and surfaces token scopes and auth states. Levo produces immutable, queryable trails of who acted, what data moved, where it went and under which policy. Levo covers LLMs, MCP servers, agents, AI apps and LLM apps across hybrid and multi cloud footprints.^[7]

Levo continuously discovers MCP servers across developer laptops, prototypes, production environments and third-party services. Levo integrates with MDM and endpoint agents to build a living inventory that includes location, owner and context. Levo builds a single enterprise repository of MCP servers across in-house deployments and third-party sources. MCP Discovery deploys via existing MDM and endpoint agents, requiring no proxies or rewrites. When a server exhibits dangerous patterns, Levo can block those actions selectively while letting the rest of the workflow continue. Levo tests MCP servers the way they are actually used, including real authentication states, real tool paths and custom payloads. Levo continuously tests newly discovered servers and re-tests as posture changes.^[8][9]

Levo's API Inventory surfaces how each API behaves, where it exists and what it exposes. Levo autonomously inventories every API across the stack, including internal, partner, third-party, shadow and zombie endpoints. Levo auto-discovers internal, partner and third-party APIs across environments and maps how sensitive data flows through them. Levo auto-classifies PII, PHI, PCI and other regulated data in motion. Levo auto-generates and executes runtime-aware, exploit-focused test payloads across APIs without manual configuration from customer teams. Levo integrates into CI/CD pipelines, not just post-release audits.^[8][10]

Levo supports cloud-native, hybrid and air-gapped deployment models, including single VM setups and multi-year contracts. Levo charges based on the number of API endpoints it secures, not on arbitrary usage metrics or traffic. Levo supports companies at all stages, from 1K to 100K+ endpoints.^[11]

Levo.ai closed its first set of customers across North America and India, including Square and AngelOne. Institutions such as the Insurance Information Bureau of India adopted the Levo.ai platform, along with Axis Finance, Axis Bank and Five9. Levo.ai says fintechs are infusing AI into fraud, onboarding, lending and payments, yet most systems run without guardrails. Levo secures AI systems that power fraud detection, onboarding, underwriting, payments, agent automation and customer experience. Levo simulates adversarial prompts, fraud attacks, agent exploits, threshold probing and data manipulation on staging environments.^[3][8][12]

About Wallarm

Wallarm is an AI security and API security platform that discovers AI workloads, monitors runtime behavior, enforces policy inline, and generates continuous compliance evidence. Wallarm says it secures web applications, APIs, and AI through a single platform that delivers runtime visibility, protection, and governance. Wallarm says its platform reads the whole request instead of scanning for known-bad patterns, stopping disguised attacks on web apps and APIs without blocking real customers.^[6][7][12]

Wallarm says almost every legacy WAF keeps a list of known bad text patterns and matches requests against it. Wallarm unwraps and decodes every request layer before analysis, so encoding tricks that pass pattern-matching firewalls do not get through. Wallarm has no size cutoff, while many WAFs stop reading after a fixed number of kilobytes. Wallarm blocks the malicious session and lets everyone else through.^[7]

Wallarm sells API Security, which discovers APIs and blocks attacks against them in one product, one deployment, one console. API Security covers REST, GraphQL, gRPC, SOAP, and WebSocket, including the APIs behind AI applications and agents. API Security deploys at the load balancer or ingress.^[2][7][8]

AI Hypervisor is the runtime enforcement layer for enterprise AI agents. AI Hypervisor shows every decision agents make, every data boundary they cross and every external call they initiate, and blocks the ones that violate policy. AI Hypervisor deploys as a Kubernetes DaemonSet on EKS and instruments every labeled pod at the kernel using eBPF analysis. AI Hypervisor finds every model provider, MCP tool and agent framework running in a cluster, including ones nobody approved. AI Hypervisor is the Observe and Enforce layer of the AI Control Loop.^[7][9]

Infrastructure Discovery is a continuous, cross-account asset discovery for AWS estates, mapping every API, compute, network, and IAM resource across up to 5,000 accounts. Infrastructure Discovery uses cross-account IAM to scan every AWS account registered, across every region. Infrastructure Discovery maps EC2, EKS, load balancers, API Gateway, Lambda, VPC and IAM. Infrastructure Discovery connects via cross-account IAM and reads the AWS estate continuously, with no per-account credentials stored and no agents to roll out. Infrastructure Discovery surfaces shadow AI within minutes of deployment.^[7][8][10]

Wallarm runs natively in Kubernetes as an Ingress controller, a sidecar, an Istio filter, or an out-of-band eBPF sensor. Wallarm runs on EKS, GKE, AKS, OpenShift, and self-managed clusters in private data centers. Wallarm says its filtering node adds 0.05ms of latency at 1700 requests per second.

On Google Cloud, Wallarm discovers every API running there and blocks API attacks, bots and abuse in real time. Wallarm can be deployed on GKE, Compute Engine or alongside Apigee in minutes. On Google Cloud, traffic is inspected inside the customer's GCP project, and only attack metadata reaches the Wallarm Cloud. The Wallarm policy for MuleSoft adds a layer of API protection to the MuleSoft Anypoint platform.^[6][12][15]

For AI systems, Wallarm says it provides API-first security by protecting AI agents, AI proxies, and APIs with AI features, preventing injection attacks and data leakage, controlling costs, and ensuring secure, compliant operations. Wallarm says AI agents with access to internal APIs and data can bypass LLM guardrails, so security must extend to every Agent API endpoint.^{[3][7][13][14][16]}