Top 10 Akto Alternatives
APIs have become more than just technical endpoints; they are now pivotal business drivers. Research shows that API first organizations grow revenue 2 to 3x faster than competitors and achieve up to 50% higher customer retention. With DevOps, microservices, and cloud native architectures powering rapid software delivery, APIs are central to both growth and operational resilience. Studies indicate that over 60% of enterprises generate direct revenue from APIs, and for nearly 25% of firms, APIs account for more than 75% of total revenue.
However, this acceleration introduces significant risk. 70% of API breaches result from unmanaged or poorly tested endpoints, and unsecured APIs can expose sensitive data, delay releases, and inflate operational costs by up to 30% due to remediation overhead. As APIs increasingly carry personal, financial, and healthcare information, regulatory expectations are rising, with frameworks like GDPR, HIPAA, and PCI DSS mandating continuous security, privacy controls, and proactive threat detection. Traditional scan-based or generic API testing solutions are no longer sufficient.
Akto, while offering automated endpoint discovery and pre built test libraries, often falls short of enterprise needs. Coverage remains surface level, complex logic and business critical endpoints go untested, and deployments require weeks of manual configuration. High privacy risk, absence of continuous monitoring, limited shift left capabilities, and heavy operational overhead can leave organizations exposed, with remediation cycles stretching from months to weeks.
Organizations that treat application and API security as a driver of uptime, revenue, and customer trust need an approach that delivers real time protection, full lifecycle coverage, automated remediation, minimal manual effort, rapid deployment, and privacy first data handling.
This blog highlights the Top 10 Akto Alternatives, evaluated on coverage, scalability, deployment ease, cost efficiency, and alignment with API first, DevSecOps driven delivery models.
When evaluating Akto’s approach to API security, several recurring limitations begin to impact security maturity, deployment speed, cost efficiency, and alignment with modern DevSecOps practices. These challenges often indicate the need to consider alternatives that offer continuous protection, deeper coverage, lower manual effort, and privacy first architectures.
The table below highlights key triggers and explains why they matter, from incomplete discovery to slow remediation cycles, helping teams identify where Akto may fall short in real world API driven environments.
Akto provides automated endpoint discovery and pre built test libraries, but its coverage and operational model often leave enterprise APIs partially untested and exposed. For organizations operating in fast moving DevOps and CI/CD environments, relying solely on Akto can increase remediation cycles, privacy risk, and operational overhead. Modern enterprises are increasingly leaning toward platforms that offer full lifecycle API security, continuous protection, and low manual effort while maintaining privacy and cost efficiency.
Below are the Top Akto Alternatives that deliver broader coverage, end to end SDLC security, automated remediation, and privacy first architectures:
These platforms support automated discovery, real time vulnerability detection, and integrated remediation, allowing organizations to secure APIs without slowing releases.
Here’s a side by side comparison of Akto vs leading alternatives across key dimensions including business value, deployment agility, privacy risk, TCO, API visibility, and SDLC coverage, helping teams quickly identify which solutions offer the best fit for modern API first, security driven engineering models.
For modern API driven ecosystems, teams are evaluating platforms that offer deeper API visibility, faster security validation, and broader protection coverage than Qualys.
Here are the top Qualys alternatives that unify API discovery, automated testing, and runtime defense for cloud native and rapidly scaling environments.
Levo.ai is designed for modern, API first enterprises that require full lifecycle API security, not just post scan detection. Unlike Akto, which relies on scheduled scans and generic test libraries, Levo secures APIs end to end from pre production testing to runtime protection without slowing down teams or compromising privacy.
Powered by an eBPF based sensor, Levo delivers deep, kernel level visibility into every API, including internal, external, partner, and low traffic endpoints. It automatically generates API documentation, maps sensitive data flows, and detects vulnerabilities early in development. In contrast, Akto’s visibility depends on traffic capture and user defined entry points, leaving dynamic, ephemeral, and low traffic APIs untested and undocumented.
Levo transforms API security from reactive to proactive. Instead of relying on raw scan results like Akto, Levo continuously validates APIs through exploit aware, real data testing. Alerts are verified before being raised, minimizing false positives and shrinking remediation cycles from months to days. Its inline protection blocks only confirmed threats, ensuring zero disruption to legitimate traffic or application performance.
Levo’s privacy first design keeps sensitive data within the customer environment, processing less than 1% of metadata in its SaaS control plane. This eliminates the vendor induced exposure risks that Akto introduces through full traffic captures and test recordings. Enterprises also see up to 10x lower infrastructure and egress costs, saving $100K to $500K annually while simplifying compliance.
Integrated directly into CI/CD pipelines, Levo automates shift left security with YAML and Python based customization, rapid deployment, and hybrid or on prem options. No inline agents, DPIAs, or long rollout cycles are required. Deployments complete in under an hour with minimal DevSecOps effort. By comparison, Akto’s deployment model requires configuring on-prem collectors, traffic connectors, and manual test setups, which increase operational complexity and extend time to value.
Where Akto stops at surface level detection, Levo secures the full API journey, helping enterprises build, test, and operate APIs faster, safer, and with greater cost and privacy efficiency.
Selecting the right API security platform depends on whether your priorities center on proactive prevention, runtime visibility, compliance assurance, or operational efficiency.
Each platform serves a distinct maturity level and team focus, and understanding where they excel or fall short helps align tools with enterprise security and growth goals.
Provides full API visibility and discovery: internal, external, shadow, zombie, and third party APIs, enriched with auth, sensitivity, reachability, and runtime context.
Akamai provides API protection rooted in its edge and WAF ecosystem, focusing on production side detection, rate limiting, and mitigation through gateway traffic patterns. It offers visibility into externally exposed APIs but relies solely on edge telemetry, so internal, partner, low traffic, and dynamically generated endpoints never enter the inventory. Since traffic is observed post encryption and without application context, monitoring is reactive, detection is limited to generic anomalies, and deeper access control or sensitive data risks go unnoticed.
Akto approaches API security through gateway feeds, spec imports, and periodic scans, offering surface level visibility into APIs that are explicitly documented or exercised. Discovery misses shadow, zombie, internal, and low traffic APIs, and tests rely on fixed payload bundles that cannot capture complex logic, role based flows, or chained exploit paths. Because Akto lacks continuous monitoring and depends heavily on manual config, new risks often go undetected until endpoints are already in production.
Both platforms improve production side visibility but only within the slice of APIs they can observe. Akamai excels in external API detection and WAF driven protection but lacks depth, context, and internal coverage. Akto provides lightweight scanning and policy checks but misses runtime behavior, sensitive data insights, and end to end shift left coverage. Neither platform delivers true API first security, automated remediation, or comprehensive discovery across internal, partner, and business critical flows, leaving significant blind spots across the SDLC.
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Read More: Top 10 Akamai Security Alternatives
Akamai has long been a market leader in CDN, WAF, and edge delivery, with API protection added post-2024 through Noname technology. Its API security remains post-production focused, relying on traffic mirroring at the edge. While this suits enterprises seeking edge performance and DDoS protection, it delivers minimal API visibility, little CI/CD integration, and elevated operational costs.
Salt Security, another early entrant in API security, emphasizes production monitoring and compliance reporting. However, it lacks a native API security testing engine and has limited ability to shift left into development or staging environments. As a result, most vulnerabilities still reach production, creating a gap between compliance visibility and true runtime protection.
Both solutions offer value for organizations with specific priorities, but for enterprises looking to treat APIs as core revenue drivers, their limitations are significant compared to modern API-first security platforms.
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Read More: Top 10 Salt Security Alternatives
Traceable.ai delivers runtime first API protection, focusing on detecting attacks, anomalies, and fraud in production. It provides SOC friendly dashboards, full traffic capture for forensics, and runtime discovery for externally active APIs, but low traffic, internal, and partner endpoints are often missed. Testing is reactive and pattern based, lacking deep behavioral simulation, multi step exploit detection, or automated remediation, while deployment requires inline agents or network mirroring, adding operational complexity and lengthening rollout times. Documentation is generated from runtime traffic only, offering limited metadata and leaving drift and integration gaps. Shift left coverage is minimal, with pre production testing largely absent, forcing reliance on production monitoring and post incident triage.
Akto delivers automated pre production API testing, discovery, and validation across CI/CD pipelines with built in test libraries, static analysis, and endpoint coverage. It identifies misconfigurations, access control flaws, and schema deviations using policy driven payloads but lacks runtime monitoring and anomaly detection. APIs with low traffic or ephemeral usage may remain untested, and remediation guidance is generic, requiring manual effort. Deployment is simpler than full traffic ingestion models but still requires setup of test libraries, authentication, and NTA agents. Documentation generation is basic, often missing dynamic or internal endpoint metadata, and shift left security is partial, relying on scheduled scans and static spec imports.
Both platforms enhance API security in complementary ways: Traceable.ai excels in SOC centric runtime detection and forensic analysis, while Akto focuses on pre production validation, CI/CD integration, and automated endpoint testing. Neither alone provides full SDLC coverage with context aware remediation, leaving gaps across production runtime, low traffic, internal, and complex business critical APIs.
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Read More: Top 10 Traceable Alternatives
Orca Security provides cloud first API visibility and misconfiguration detection by analyzing cloud assets, network paths, and data mappings, but offers only surface level API insight and limited depth across internal, partner, and low traffic endpoints. It can flag exposed services and misconfigured API gateways, yet it lacks real time monitoring, behavioral context, and shift left integration, making its coverage reactive and dependent on cloud metadata rather than actual API behavior or traffic. Documentation, runtime insights, and sensitive data flows remain incomplete, while discovery misses most east-west and non internet facing APIs.
Akto focuses on periodic scans, user supplied specs, and policy driven tests, offering baseline schema checks but missing business logic flaws, access control issues, and dynamic API behaviors. Because discovery depends on uploads, gateway imports, and NTA logs, internal, third party, and low traffic APIs remain untested, and remediation cycles stall due to generic findings without payload repro or developer mapping. The lack of automated monitoring, runtime telemetry, or context aware test generation results in large blind spots across critical endpoints.
Both platforms help security teams map parts of their surface area, but in different ways: Orca surfaces cloud level API exposure risks by analyzing misconfigurations and cloud metadata, while Akto provides periodic policy based scans tied to known specs and gateway entries. However, neither platform delivers continuous runtime visibility, behavior driven discovery, or automated context rich testing, leaving gaps across complex internal services, business logic flows, and sensitive data handling paths.
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Escape Security focuses on pre production analysis by generating static API schemas from source code and performing lightweight checks on inferred patterns. It helps teams catch basic design flaws early, but lacks runtime intelligence, real traffic awareness, and end to end API context. Because discovery is code based only, over 50 percent of actual APIs remain invisible, especially dynamic, partner, third party, and feature flagged routes that never appear in repositories. Without runtime payloads, auth flows, or behavioral signals, the platform cannot detect access control issues, multi step logic flaws, or real data exposure. Documentation quickly drifts because schemas are generated once and never reconciled with live behavior, and remediation slows down as teams must manually interpret static violations without payload reproduction or developer mapping.
Akto provides broader pre production scanning but remains limited as well, relying on policy driven payloads and periodic scans rather than environment aware test generation. Because discovery depends on traffic capture and operator supplied entry points, low traffic and dynamic APIs remain missed. Its testing engine uses generic payload bundles and static templates, missing deep business logic, role based flows, and chained attack paths. Runtime monitoring is absent, so drift, misconfigurations, and sensitive data exposures make it to production undetected. Remediation remains manual because results lack context, developer ownership, and reproducible payloads.
Both platforms focus on pre production security but remain incomplete in different ways. Escape is static, code centric, and blind to actual runtime behavior, while Akto is scan centric, traffic dependent, and blind to complex logic flows. Neither offers continuous visibility, real time drift detection, sensitive data tracing, or environment grounded attack simulation, leaving significant blind spots across internal services, business critical workflows, and rapidly changing microservice architectures.
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Inviciti delivers API security through periodic scans, spec driven testing, and network sampling, offering baseline coverage for documented and frequently used endpoints. Its inventory depends on uploaded specs, gateway imports, and sampled traffic, so shadow, internal, low traffic, and feature flagged APIs often remain undiscovered. Documentation and discovery drift quickly because there is no real time reconciliation with actual API behaviour or sensitive data flows. Monitoring and anomaly detection are not built in, leaving teams dependent on external logs and manual investigation when new API risks emerge.
Testing depth remains surface level, driven by static policies and limited payload generation. Stateful, multi step, and role aware attack paths that dominate modern API breaches remain untested, and findings lack payload reproduction or automated developer mapping. Remediation slows as teams must decode generic reports and manually assign fixes across services.
Deployment is heavy for on prem environments, requiring multiple components and continuous maintenance, which pushes out time to value.
Compared to Akto, which also relies on static specs and periodic scans, Inviciti offers broader enterprise modules and deeper integration options but suffers from the same structural gaps: incomplete discovery, no live traffic intelligence, limited detection of sensitive data exposure, and minimal testing depth. Both platforms struggle with internal, partner, and low traffic APIs and lack continuous monitoring. Where Akto emphasizes lightweight gateway centric scanning, Inviciti emphasizes broader scanning modules, but neither provides automated behavioural testing, context aware remediation, or shift left coverage grounded in runtime realities. As a result, both solutions leave critical logic and access control flaws undetected until production, slowing remediation and elevating breach risk.
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Qualys provides scheduled, scan driven API security stitched onto its broader VM, cloud, and EASM ecosystem, but lacks the real time telemetry, behavioral context, and deep API first testing needed to secure modern services. Inventory is assembled from crawls, gateway connectors, and uploaded specs, which means over half of internal, partner, low traffic, and shadow APIs never enter the catalog. Because discovery is not traffic aware and testing is retrofit from a generic web app scanner, visibility is fragmented and critical logic, stateful, and authorization flaws routinely go undetected.
Monitoring is periodic and relies on dashboards rather than passive detection of anomalies or access control drift, so new attack patterns, sensitive data exposures, and east west API movements remain invisible until after deployment. Documentation depends entirely on user supplied OpenAPI files with no auto reconciliation to live behavior, causing spec drift, broken integrations, and audit failures. Remediation stalls because findings are generic vulnerability lists without payload reproduction, developer mapping, or automated ticketing.
Compared to Akto, which already suffers from limited monitoring, partial discovery, and static test payloads, Qualys further reduces accuracy by spreading API visibility across multiple modules without real time context or unified telemetry. The result is a heavy, multi app deployment that increases operational overhead, raises TCO due to per module licensing, and still misses most internal and business critical APIs. Both solutions struggle with shift left coverage and deep behavioral testing, but Qualys is more fragmented, slower to deploy, and heavily dependent on manual curation, leaving large gaps in pre production and runtime API security.
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Rapid7 delivers periodic, scan driven API security that is built primarily for compliance rather than continuous protection. Its API coverage is constrained by crawler based discovery, which misses internal, low visibility, inactive, and partner APIs, leaving large gaps that attackers can exploit. With no runtime monitoring, no anomaly detection, and no ability to stop misconfigured or exposed APIs from going live, security remains reactive and dependent on the next scheduled scan cycle.
Security testing is retrofit onto a web app scanner and fails to address complex authentication, business logic abuse, or multi step flows. Payloads are generic, coverage is shallow, and developers are left interpreting static reports without service mapping, ticket automation, or reproducible evidence.
As a result, remediation slows, vulnerabilities linger across releases, and teams operate with a false sense of security between scans.
Compared to Akto’s traffic based discovery and broad test libraries, Rapid7 remains even more limited: its discovery misses non linked routes and internal APIs, testing is surface level, and no continuous monitoring exists. Both platforms leave critical blind spots, but in different ways. Rapid7 is constrained by crawler based scans and static templates, while Akto relies on traffic presence and manual configurations that fail to surface low traffic or undocumented routes. Neither provides continuous runtime defense, behavioral simulation, or true shift left security, creating material gaps across pre production, internal environments, and complex business critical APIs.
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StackHawk focuses on pre production API testing, generating scans from code derived specs and static analysis. It identifies common injection flaws and schema issues before deployment, but coverage is narrow because testing is limited to code declared endpoints and single request payloads. Dynamic or runtime registered APIs remain untested, authentication must be manually configured, and false positives are frequent due to lack of traffic context. With no runtime discovery, no monitoring, and no visibility into sensitive data flows, critical internal, partner, and low traffic APIs often ship without any security validation.
Akto offers broader API visibility and policy driven scanning through OpenAPI imports, API gateway connectors, and network traffic analysis, but it also misses internal, low traffic, and shadow endpoints. Testing relies on generic payload bundles that fail to simulate chained, stateful, or business logic attacks. Without runtime telemetry or continuous monitoring, new drift, misconfigurations, and sensitive data exposures remain undetected until customers or logs surface issues. Akto’s pre production coverage is periodic and dependent on manual documentation, and remediation requires teams to interpret static findings and map fixes manually.
Both platforms improve API security before release but in different ways. StackHawk is developer centric and code focused, offering fast but shallow scans rooted in static schemas, while Akto provides broader surface level visibility with broader but generic scans. Neither platform delivers behavioral testing, adaptive payload generation, or continuous runtime monitoring, leaving gaps across complex authentication flows, sensitive data paths, and business critical API behavior.
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APIs now power the backbone of digital systems, but lightweight testing tools like Akto often leave critical security gaps. Limited depth of API coverage, surface level test libraries, and manual setup requirements slow teams operating in fast moving microservices and cloud native environments.
Levo.ai solves these challenges by unifying API discovery, shift left testing, runtime protection, sensitive data detection, and automated remediation in one platform. Teams eliminate manual configuration, reduce false positives, and secure APIs continuously from design to production.
For organizations that need complete, enterprise grade API security rather than basic test automation, Levo delivers full spectrum coverage aligned with modern engineering velocity.
Choosing the right API security platform requires automation, context, and lifecycle level visibility. Unlike Akto, which relies on predefined templates and lacks advanced logic testing, Levo provides real time insights, exploit aware detection, and seamless CI CD integration for proactive defense.
Adopting Levo enables teams to accelerate releases, reduce operational burden, and secure every API endpoint without the constraints of template based or manually tuned tools. Achieve true end to end API protection with Levo and future proof your API ecosystem.
Book your DEMO today to implement API security seamlessly.