All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
Miggo Security sells software that baselines how running applications and AI agents behave and detects deviations from that baseline. It sells to security teams in regulated industries such as finance and healthcare. For vulnerabilities confirmed as exploitable, its WAF Copilot generates firewall rules meant to block exploits until customers patch. Founded in 2023, Miggo raised a $7.5 million seed and a $17 million Series A led by SYN Ventures, announced in April 2025, about $24.5 million total per SecurityWeek. Its named customers are LifeLabs, SoFi, Patreon, Riskified and Eitan Medical. Calcalist’s Series A report counted 25 staff. WAF Copilot’s rules run in the customer’s firewall, so a firewall provider shipping comparable exploit-specific rules could replace that part of the product.
| Description | Miggo: Runtime application security platform that mitigates exploitable vulnerabilities in running applications while patches are pending, alongside detection and response for applications and AI agents. | [f1] |
|---|---|---|
| Founded | 2023 | [f2] |
| HQ | New York, New York, USA and Tel Aviv, Israel | [f3] |
| Funding | $24.5M total | [f2] |
| Latest funding | Series A, $17M, April 2025, led by SYN Ventures | [f4] |
| Product | What it does |
|---|---|
| Miggo ADR | Application Detection and Response platform powered by DeepTracing that maps how applications run, finds exploitable paths, and blocks vulnerability exploitation at runtime without patching. |
| Miggo AIDR | AI Detection and Response that monitors agents, models, tools, and MCP at runtime, detecting prompt injection, model misuse, and agent hijacking, then contains incidents with a forensic chain. |
| Miggo WAF Copilot | Generates custom WAF rules for instant virtual patching, letting teams block exploitation of new vulnerabilities in seconds before a code fix ships. |
| Miggo Pulse | Detects, validates, and stops AI-accelerated exploitation, closing the patch gap between a vulnerability disclosure and a deployed fix. |
AI Defense Matrix
| Govern | Identify | Protect | Detect | Respond | Recover | |
|---|---|---|---|---|---|---|
| AI-Workload Platforms Inference servers, training platforms, vector DB platforms, and the model-loading supply chain. | ||||||
| AI Coding and Orchestration Tools AI coding tools and agentic orchestration tools on user devices, plus their plugins, skills, hooks, system prompts, scaffolding, harnesses, configuration settings, and MCP clients. | ||||||
| AI-Generated Code Code produced by AI tools, AI-assisted reviews, AI-generated infrastructure-as-code and tests, and vibe-coded apps that bypass CI/CD. | ||||||
| AI Traffic Paths to external and self-hosted AI services, MCP tool channels, agent-to-agent calls, model-registry downloads, and egress to unapproved AI services. AI gateways, LLM routers, and MCP gateways steer traffic along those paths. The steering decisions and their inputs belong here too: routing policies, MCP server registries, and agent naming and discovery services. | ||||||
| AI Model Model weights, fine-tuning checkpoints, model cards, registries, an AI bill of materials (AIBOM), and the third-party LLMs your enterprise consumes. | ||||||
| Training Data Datasets used for training, fine-tuning, and continued learning. | ||||||
| Runtime AI Data User prompts, inference inputs, RAG content, vector DB content, persistent agent memory, and interaction history. | ||||||
| AI Agent Identities AI agents as non-human principals, plus credentials, keys, permission scopes, service accounts, and delegation chains across agents and tools. |
Miggo AIDR builds a runtime AI-BOM that maps active agents, models, tools, and MCP integrations, enforces guardrails on model usage and tool access, and detects prompt injection and agent hijacking at runtime. It is mapped to the AI Defense Matrix. [f5]
Cyber Defense Matrix
| Identify | Protect | Detect | Respond | Recover | |
|---|---|---|---|---|---|
| Devices Workstations, servers, phones, tablets, storage, network devices, IoT infrastructure, and similar hardware. | |||||
| Applications Software, interactions, and application flows on the devices. | |||||
| Networks Connections and traffic flowing among devices and apps, plus communication paths. | |||||
| Data Content at rest, in transit, or in use across devices, apps, and networks. | |||||
| Users The people using the devices, apps, networks, and data. |
Miggo ADR records, baselines, and monitors first and third-party application behavior at runtime to detect anomalies and threat exposure. This application defense is mapped to the Cyber Defense Matrix. [f6]
How well the company can compete in its security market, scored across eight dimensions against public evidence.
| Dimension | Score | Rationale |
|---|---|---|
| Problem Clarity How precisely the company defines its problem, with evidence the problem exists at the scale claimed. | 3/5 | Miggo states a specific problem, application behavior in production that endpoint tools miss, and Latio Pulse makes the same point that an endpoint tool has no insight into an application payload. The one quantified figure, time to exploit falling from 63 hours to 22 minutes, is industry data the company cited to Calcalist rather than an independent measure of buyer pain. [s24, s20, s22] |
| Capability Depth How specific the technical capabilities are, with evidence beyond marketing claims such as docs and third-party validation. | 3/5 | Miggo’s pages describe function-level reachability analysis, a runtime map of AI agents and tools, and WAF rules tested against payload variations before deployment. Latio Pulse describes the detection approach and SecurityWeek relays the DeepTracing design, and the reviewed sources are product pages and coverage rather than technical documentation or a third-party test of the product. [s3, s4, s6, s19, s20, s9] |
| Market Timing Whether the market is ready for this product, with evidence that buyers are actively seeking solutions. | 3/5 | The enabler is AI-driven attackers turning disclosed vulnerabilities into exploits faster than teams can patch, the threat SecurityWeek describes Miggo launching against in 2023. Within the last twelve months the buyer-side signal is one kind, the Gartner Cool Vendors in AI Security report of 24 September 2025 that Miggo relays. Latio Pulse’s April 2025 vendor list is older, and AWS offering Miggo’s rule sets is distribution rather than buyer demand. [s9, s8, s27, s19] |
| Team Credibility Demonstrated domain expertise with public signals such as prior exits, publications, and industry recognition. | 3/5 | Daniel Shechter describes a decade in Unit 8200 and McKinsey consulting, and Calcalist reports that CTO Itai Goldman led a cyber research unit. No prior company or named product build appears in the cited sources. The research team has two independently documented disclosures, ALBeast in 2024 and the Grafana flaw CVE-2026-27876. The cited sources document neither multiple prior product builds nor a sustained recognized publication record. [s11, s22, s2, s13, s14, s15] |
| GTM Proof Evidence of actual traction (customers, revenue signals, partnerships) beyond stated intentions. | 4/5 | Miggo names SoFi, Patreon, Lifelabs, Riskified, and Eitan Medical across its Series A post and homepage, quotes the LifeLabs CISO as a customer, and offers its rule sets to AWS WAF customers through AWS Marketplace. Calcalist reports 3x revenue growth in 2024. No revenue base or independent corroboration of scale appears in the cited sources. [s7, s1, s10, s19, s9, s22] |
| Funding Efficiency Whether funding matches go-to-market ambition, with signs of capital-efficient growth. | 3/5 | Miggo’s disclosed capital is a $7.5 million seed and a $17 million Series A announced in April 2025, roughly $24.5 million in total per SecurityWeek. Since then it has shipped AI runtime detection, the Pulse vulnerability feed, and edge and in-application mitigation. That capital is proportional to an early enterprise motion with visible shipping, and no disclosed revenue base or margin confirms output per dollar. [s24, s9, s10, s17, s23, s16] |
| Category Clarity Whether the company creates or fits a recognizable category that buyers can quickly place in their stack. | 3/5 | Latio Pulse places Miggo among application detection and response vendors in 2024 and 2025, and SecurityWeek uses the same label. Latio also writes that Oligo and Miggo do not do the same thing. Miggo’s homepage describes mitigating exploitable vulnerabilities while a separate page covers its AI runtime platform, so the category a buyer would file it under is still forming. [s20, s27, s9, s1, s4] |
| Incumbent Defensibility How vulnerable the core value proposition is to absorption as a feature by a platform vendor. | 3/5 | Miggo’s in-application runtime tracing adds some friction to absorption, and Miggo positions that in-application context as something EDR, WAF, and CNAPP tools do not provide. The reviewed sources show no structural moat. Part of its mitigation output is rules pushed into AWS, Cloudflare, Azure, and Akamai firewalls, so a firewall provider that shipped comparable exploit-specific rules could substitute for that part of the product. [s3, s10, s6, s19] |
Miggo sells runtime defense for applications to enterprise security teams, and its homepage describes mitigating exploitable vulnerabilities before a patch ships. The homepage says Miggo mitigates exploitable vulnerabilities in under an hour and reduces backlog and exploitable risk by over 90%, figures that are the company’s own claims. SecurityWeek describes the Series A as funding a push into the enterprise market.
The problem Miggo addresses is the time between a vulnerability’s disclosure and its fix. Calcalist reports industry data, cited by the company, that the average time to exploit fell from 63 hours to 22 minutes. Miggo frames its Pulse product around the same patch gap.
Miggo also frames the problem as application behavior that other security tools cannot see. SecurityWeek compares Miggo’s application detection and response with endpoint detection and response. Latio Pulse describes endpoint tools’ lack of visibility into application payloads. [s1, s9, s22, s17, s24, s20]
Miggo ADR is the core product, an application detection and response platform built on Miggo’s DeepTracing engine. Miggo says DeepTracing tracks application behavior and detects high-risk paths, and SecurityWeek relays that it models how microservices, APIs, and authentication paths should interact and cuts off anything outside those baselines. Miggo describes agentless deployment with no code required, and a single lightweight sensor that adds function-level reachability analysis to threat investigation and response.
Mitigation runs at two layers. Miggo WAF Copilot generates a WAF rule for a vulnerability confirmed as exploitable, tests it against payload variations, and pushes it to AWS WAF, Cloudflare, Azure, or Akamai. Miggo’s ExploitationGuard provides runtime detection and blocking for threats inside the perimeter through an eBPF sensor, and Miggo’s Defense-in-Depth release describes inline blocking inside the application as early preview.
Miggo Pulse, a vulnerability intelligence feed announced on 29 April 2026, tracks new threats, checks whether each is exploitable in the customer’s running applications, and generates protection. Its enrichment comes from Miggo’s Predictive Vulnerability Database, a curated repository that Miggo publishes on its website.
Miggo’s AI runtime product adds an AI bill of materials, runtime guardrails, and agentic detection and response. Miggo says this extends its DeepTracing capabilities, which its CEO called patent-pending in a FinSMEs interview and a Miggo release calls patented. The AI product maps agents, models, tools, and data access and monitors tool use across MCP toolchains, the connectors agents use to reach tools. [s2, s9, s3, s17, s6, s23, s26, s16, s4, s11]
Miggo competes among application detection and response vendors. Latio Pulse’s 2025 runtime security review lists Contrast, DataDog, Dynatrace, Kodem, Miggo, Oligo, Operant, Raven, and Traceable as key ADR players, and its 2024 analysis names Oligo and Miggo as the two main companies using the ADR term.
Latio also records that those products differ technically. It writes that Oligo and Miggo do not do the same thing, and it describes Miggo’s approach as application-level detections between microservice calls that use existing application performance monitoring.
Part of Miggo’s mitigation depends on firewalls other companies operate. Miggo positions its in-application context against endpoint, web application firewall and cloud security tools. Its WAF Copilot rules run inside AWS, Cloudflare, Azure, and Akamai firewalls, with AWS offering Miggo’s rule sets in its own WAF console. A firewall provider that shipped comparable exploit-specific rules could compete with that part of the product. [s27, s20, s10, s6, s19]
Miggo names its customers in its own materials. Its Series A post names SoFi, Patreon, and Lifelabs, and its homepage lists LifeLabs, SoFi, Riskified, and Eitan Medical under a Trusted by Industry Leaders heading. Its Series A release quotes Mike Melo, CISO of LifeLabs, as a Miggo customer.
AWS gives Miggo a marketplace route to buyers. Miggo’s partner-managed rule sets are available through AWS Marketplace inside the AWS WAF console, where AWS WAF customers can subscribe directly. Miggo’s release says AWS chose it as one of a select group of providers for integrated WAF protection.
Miggo’s disclosed commercial figures are growth rates. Calcalist reports 3x revenue growth in 2024 after a 4.5x increase the year before. Miggo does not disclose the revenue base behind those rates. Miggo says it is recognized in the Gartner Cool Vendors in AI Security report dated 24 September 2025. [s7, s1, s10, s19, s22, s8, s16]
Miggo’s founders are Unit 8200 alumni, Calcalist reports. CEO Daniel Shechter told FinSMEs he served a decade in Israel’s 8200 cyber unit and then worked as a strategy consultant at McKinsey. Calcalist reports that CTO Itai Goldman, a Talpiot graduate, previously led a cyber research unit.
Miggo’s research team has two independently documented disclosures. SecurityWeek and The Hacker News covered ALBeast, a configuration issue Miggo disclosed to AWS in April 2024 and said could expose as many as 15,000 applications using AWS load balancer authentication. AWS told both outlets that significantly fewer customers had potentially misconfigured applications than the researchers estimated, so the 15,000 figure is Miggo’s estimate and AWS disputes it. Grafana Labs thanked Miggo’s head of research, Liad Eliyahu, for disclosing CVE-2026-27876.
Calcalist reported 25 employees in its article on the Series A, most at a development center in Israel and the rest in the United States. [s22, s11, s2, s12, s13, s14, s15]
Miggo’s homepage footer lists an AICPA SOC badge. No trust portal or SOC report appears on the probed trust surfaces.
Miggo’s products process sensitive runtime content. Its AI detection monitors prompts and model interactions, and its application platform maps where sensitive data flows. [s1, s29, s4]
| Company | Relationship | Note | Compare |
|---|---|---|---|
| Operant AI | competes with | Named with Miggo among key application detection and response vendors in Latio Pulse’s 2025 runtime security review, competing for the same runtime security buyer. | |
| Oligo Security | competes with | Named with Miggo by Latio Pulse as a main company using the application detection and response label, competing for the same runtime application security budget. | N/AWe captured the evidence for these companies under different evidence-model versions (v1 vs v2), so the totals were scored under different conditions and are not directly comparable. |
| Pillar Security | competes with | Competes with Miggo’s AI runtime product for the enterprise security team that secures AI agents and models. | N/AWe captured the evidence for these companies under different evidence-model versions (v1 vs v2), so the totals were scored under different conditions and are not directly comparable. |
| Wiz | adjacent | Adjacent vendor selling to the same enterprise security teams that buy Miggo’s runtime products. | |
| Palo Alto Networks | adjacent | Adjacent vendor selling to the same enterprise security teams that buy Miggo’s runtime application and AI defense. | N/AWe scored these companies at different scopes, so the totals measure different things. |
Add analyzed competitors to compare them side by side with Miggo Security.
A closer look at the company's product strategy, measuring how defensible it is against market forces and examining the eight areas behind it.
reinforce or reposition
Regulated enterprises in healthcare and finance buy Miggo Security’s software, a sensor in their applications plus firewall rules, and their own security teams run it and own the outcome. That software checks in real time which vulnerable functions a running application calls and detects malicious execution inside it, with inline blocking in early preview. A customer that routes vulnerability triage and stopgap firewall rules through Miggo could need to rebuild that workflow on another product. Miggo positions the context its sensor collects inside the application as something endpoint, firewall and cloud security tools do not provide. Its rules run in the customer’s firewall, so a firewall provider shipping comparable exploit-specific rules could replace that part of the product.
| Dimension | Score | Rationale |
|---|---|---|
| Value Delivery Does the product sell software as the product, or judgment, trust, or accountability with software as the delivery mechanism. | 1/3 | Miggo delivers software the customer’s security team operates, a runtime sensor, a detection platform, and generated firewall rules, and that team owns the outcome. Miggo tests rules in its own lab before release as part of building the product, and no managed service that accepts accountability appears in the reviewed sources. |
| Switching Cost How expensive leaving is for a customer: data portability, integrations, learned workflows, network effects, regulatory data residency. | 2/3 | A customer that routes vulnerability triage and virtual patching through Miggo’s sensor and rule generation could need to rebuild that workflow on another product, which is integration and learned-workflow friction. The generated rules run in the customer’s own AWS, Cloudflare, Azure, or Akamai firewall, and the reviewed sources do not size what leaving Miggo would cost. |
| Compliance Moat Whether certifications, liability acceptance, or audit trails block an easy replacement. | 1/3 | Miggo’s homepage footer lists an AICPA SOC badge, and no report or trust portal appears on the probed trust surfaces. A SOC attestation is one a funded competitor can also obtain, so it does not block a replacement, and the reviewed sources name no regulation that requires this product. |
| Problem Complexity Whether the product requires ML, optimization, real-time systems, or years of specialized expertise. | 3/3 | Function-level reachability analysis across running microservices, runtime detection inside applications with inline blocking in early preview, and rules validated against exploit variations are real-time systems work. SecurityWeek relays the DeepTracing design for application services, Latio Pulse describes Miggo’s detections between microservice calls, and Miggo says its AI runtime detection extends the same engine. |
| Buyer Profile Whether buyers are SMB operators, mid-market IT teams, or regulated enterprises and governments with procurement gates. | 3/3 | Miggo’s Series A release quotes the CISO of LifeLabs, a Canadian healthcare company, as a Miggo customer, and Miggo names SoFi among the companies that rely on it. Miggo says it secures mission-critical applications in highly regulated industries including financial services, a claim SecurityWeek relays, so the evidenced buyer class is regulated enterprises in healthcare and financial services. |
| Layer Whether the product is an end-user application, a platform with application features, or infrastructure other applications depend on. | 2/3 | Miggo is a platform with detection, prioritization, and mitigation features that runs a sensor inside customer applications and pushes rules into firewalls. Miggo describes the sensor as non-disruptive and its rules as additions to a WAF the customer already runs, and the reviewed sources describe no other software that depends on Miggo to operate. |
| Proprietary Data, Content, or IP Whether the product accumulates datasets, content licenses, or IP that a rival cannot recreate from scratch. | 1/3 | Miggo’s Predictive Vulnerability Database is a curated repository of vulnerability analysis from its research pipeline. Miggo publishes the database’s entries on a public web page, so the reviewed sources show it as a published asset rather than a retained non-public one. DeepTracing is called patent-pending in a FinSMEs interview and patented in a Miggo release, and the reviewed sources contain no granted patent record, so no retained IP asset is evidenced. |
Miggo sells to enterprise security teams that defend production applications, and Miggo names industries including financial services and healthcare. SecurityWeek relays Miggo’s statement that it secures applications in highly regulated industries such as financial services, e-commerce, and SaaS, and Miggo’s CEO told FinSMEs it had onboarded major customers in finance, healthcare, and SaaS.
The named customers operate in those industries. Miggo’s Series A release quotes the CISO of LifeLabs, which it describes as a Canadian healthcare company, as a Miggo customer, and its Series A post and homepage also name SoFi, Patreon, Riskified, and Eitan Medical.
The segment widened as the product line grew. Miggo markets its AI runtime product to security teams as well, and its homepage lists financial services, healthcare, technology and SaaS, retail, e-commerce, and insurance among its industries.
DeepTracing is Miggo’s core engine for application defense. Miggo says it tracks application behavior, detects high-risk paths, and enforces runtime protection. SecurityWeek reports that DeepTracing models how microservices, APIs, and authentication paths should interact and cuts off anything outside those baselines.
Miggo’s AI runtime product applies runtime monitoring to agents and models. Miggo’s release says the AI and agentic defense extends its patented DeepTracing capabilities. Its pages describe a runtime AI bill of materials, detection of prompt injection and model misuse, and blocking of harmful execution in real time before unauthorized actions impact production systems. Miggo correlates each agentic incident into a forensic chain from user input to agent decision to system action.
Miggo’s vulnerability intelligence comes from its research pipeline. Miggo Pulse, its vulnerability intelligence feed, enriches each vulnerability with Miggo’s research, including vulnerable function mapping and predicted attack mutations, drawn from the Predictive Vulnerability Database that Miggo publishes on its website.
Miggo names its customers in its own materials. Its Series A post names SoFi, Patreon, and Lifelabs, and its homepage lists LifeLabs, SoFi, Riskified, and Eitan Medical under a Trusted by Industry Leaders heading. Its Series A release quotes the LifeLabs CISO as a Miggo customer.
AWS gives Miggo a marketplace route to buyers. Miggo’s partner-managed rule sets are available through AWS Marketplace inside the AWS WAF console, and Miggo’s release says AWS chose it as one of a select group of providers for integrated WAF protection.
Miggo’s disclosed commercial figures are growth rates. Calcalist reports 3x revenue growth in 2024 after a 4.5x increase the year before. Miggo does not disclose the revenue base behind those rates. Miggo says it is recognized in Gartner’s Cool Vendors in AI Security report dated 24 September 2025.
No public price list appears in the cited sources, and its pages ask buyers to book a demo or, for WAF Copilot, request a special offer. AWS WAF customers can subscribe to Miggo’s rule sets through AWS Marketplace.
Miggo states its value in exposure time and effort. Its releases say Miggo reduces exposure windows by up to 99% and cuts operational overhead by 30% or more, which are the company’s own figures.
Deployment is designed to be quick. Miggo describes agentless deployment that gives application ecosystem visibility in minutes with no code required, and a single lightweight sensor that adds function-level reachability analysis to threat investigation and response.
Rule delivery follows a test-then-deploy workflow. Miggo says it generates each rule from public or Miggo-generated proof-of-concept code and tests it against bypass and mutation variations in Miggo Lab before release. WAF Copilot lets a team review a validated rule and push it to its firewall with a single click.
Response work combines vulnerability intelligence and incident evidence. Pulse checks whether a new vulnerability is exploitable in the customer’s running applications and generates protection. For agentic AI incidents, Miggo correlates events into a forensic chain from user input to agent decision to system action.
Miggo’s homepage footer lists an AICPA SOC badge. No trust portal or SOC report appears on the probed trust surfaces.
Miggo’s products process sensitive runtime content. Its AI detection monitors prompts and model interactions, and its application platform maps where sensitive data flows.
Miggo places its mitigation inside firewalls customers already run. WAF Copilot pushes rules to AWS WAF, Cloudflare, Azure, or Akamai. Miggo’s rule sets are available inside the AWS WAF console, and Miggo’s Defense-in-Depth release describes turning a WAF an organization already owns into a real-time response.
Miggo also connects to observability data. Its site markets Runtime Intelligence with Grafana Cloud, which it describes as risk decisions powered by Grafana telemetry.
Miggo’s AI runtime product instruments the AI applications a customer runs in production. Miggo describes tracing model loading, tool invocation, file access, and network behavior across agents and MCP toolchains, the connectors agents use to reach tools.
Miggo’s founders are Unit 8200 alumni, Calcalist reports. CEO Daniel Shechter told FinSMEs he served a decade in Israel’s 8200 cyber unit and then worked as a strategy consultant at McKinsey. Calcalist reports that CTO Itai Goldman, a Talpiot graduate, previously led a cyber research unit.
Miggo’s research team has two independently documented disclosures. SecurityWeek and The Hacker News covered ALBeast, a configuration issue Miggo disclosed to AWS in April 2024 and said could expose as many as 15,000 applications using AWS load balancer authentication. AWS told both outlets that significantly fewer customers had potentially misconfigured applications than the researchers estimated, so the 15,000 figure is Miggo’s estimate and AWS disputes it. Grafana Labs thanked Miggo’s head of research, Liad Eliyahu, for disclosing CVE-2026-27876.
Calcalist reported 25 employees in its article on the Series A, most at a development center in Israel and the rest in the United States.
| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | Miggo Security homepage | official | 2026-09-15 |
| f2 | SecurityWeek on Miggo Series A (launched 2023) | press | 2026-09-15 |
| f3 | FinSMEs: interview with Miggo Security CEO Daniel Shechter | press | 2026-09-15 |
| f4 | GlobeNewswire on Miggo $17M Series A led by SYN Ventures | official | 2026-09-15 |
| f5 | AI Defense Matrix Catalog mapping | other | 2026-09-15 |
| f6 | Miggo why ADR page | official | 2026-09-15 |
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