42Crunch, Escape, Levo.ai and Pynt

About Escape

Escape sells an offensive security platform that uses AI agents to discover, test and remediate vulnerabilities in engineering workflows. Escape says the platform replaces legacy scanners and manual offensive security processes.

Escape says it rebuilds offensive and application security from the ground up, covering business logic testing, agentic pentesting and code-to-cloud correlation. Escape states that all of this is always developed in-house.

Escape's AI Pentesting is continuous AI-powered pentesting that learns the customer's business, proves exploitability, and delivers reports that auditors and engineers can act on. White-box pentesting is available, so Escape's AI Pentesting can run with the customer's source code. Escape also converts previous AI pentesting findings into automated regression tests that run on every build with DAST.^[5]

Escape's DAST is described as in-house and AI-powered, and it secures applications at the business logic level. Escape's testing covers workflows, access control and multi-step processes, not just payloads.

Escape's external network pentesting is continuous testing of everything reachable from the internet. Every host, port and exposed service is probed the way an attacker would, with proof of what is exploitable, followed by a retest. Escape's attack surface management discovers and validates exposure of modern applications, APIs and infrastructure from code to cloud. Escape discovers APIs and SPAs, not just DNS and ports, both internal and external.

Escape's documentation says its platform section applies across all Escape products: ASM, DAST and AI Pentesting. Customers can deploy a Private Location in their own network to discover and test internal applications. Private Locations enable scanning of applications that are not accessible from the public internet.^[10]

On integrations, Escape sends assets directly to Wiz. Escape offers a public API, a CLI and an MCP Server, and says security gates run in CI/CD when scans are triggered on every push. Escape also has native integrations with AI-assisted IDEs such as Cursor, Claude Code and Gemini for remediation.

For compliance, Escape says PCI-DSS, HIPAA, CRA, SOC 2, ISO 27001 and 20+ other frameworks are natively supported. Escape maintains SOC 2 Type II certification. Escape uses proprietary AI models on AWS infrastructure, Microsoft Azure LLM Deployments and Cloudflare Workers AI Models.^{[2][5][6][7][13]}

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 Pynt

Pynt sells a platform that discovers and secures APIs, LLMs and MCPs in one single solution. Pynt can detect any external or internal API.^[1][2][3]

Pynt supports multiple sources to build a comprehensive API catalog and reveal shadow APIs and hidden spots. Those sources include testing tools like Postman and Selenium, Browser and Burp logs, and live traffic such as eBPF or ALB mirroring. Pynt discovers and classifies all APIs, including shadow and undocumented APIs, across cloud environments.^[2][3]

Pynt builds a complete inventory by learning directly from API behavior, and it performs security tests on every endpoint. Pynt is plugged in once and works across cloud, on-prem, or hybrid deployments.^[4]

For testing, Pynt builds security tests from existing functional tests. Pynt enables automated API pen-tests on every build and is built for CI/CD pipelines. Pynt analyzes Burp XML and HAR browser recordings for contextual analysis before attack generation. Pynt supports Postman, Selenium, and other frameworks natively. Pynt learns the app context, including the API structure, sessions and parameters nature. Pynt uses AI to generate synthetic traffic that enables contextual attacks. Pynt shows the full request-response chain. Pynt detects actual exposures through real API flow, covering leaks of PII, tokens, and secrets.^[1][5][6][7]

On authorization flaws, Pynt automates BOLA detection by analyzing real API traffic and identifying endpoints that require ownership checks. Pynt integrates into CI/CD pipelines and API testing frameworks to catch data leaks early. Pynt detects sensitive data including PII, credentials, API keys, and more.^[8][9]

Pynt discovers all LLM assets in use and builds an inventory of them. Pynt offers an agent-based MCP Firewall enabling full disable or control. Pynt maps how user prompts trigger downstream tool, plugin and API calls. Pynt scores individual components and entire chains for risk, offers visual graph representations of chain flows and enables runtime disablement of any chain link. Pynt auto-discovers MCPs and plugins in the environment.^[7][10]

Pynt provides exportable, standard-format reports for external use. Pynt promotes collaboration between R&D and security teams. Pynt offers runtime control over tool and plugin execution, with full audit trails and risk scoring.^{[1][2][5][6][7][8][10]}