Software Alternatives & Startups

Onam Security VS Plexicus

Compare Onam Security VS Plexicus and see what are their differences

Onam Security

Unified CNAPP platform: CSPM, CIEM, DSPM, CWPP, SSPM, agentless workload scanning, attack paths, threat detection & compliance across AWS, Azure, GCP, OCI, Alibaba, IBM, Kubernetes and SaaS. 100% agentless.

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0 reviews
Pricing
$24 / Monthly (1 resource)
Plexicus

Plexicus is an Application Security Posture Management (ASPM) and Cloud-Native Application Protection Platform (CNAPP) that provides a single, correlated view of risk across your entire software development lifecycle.

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Which is more popular?

Cyber Security popularity
49% vs 51%
alternatives listed
16 vs 18

Base details

Website, pricing, platforms and company facts side by side.

Onam Security
Plexicus
Website onamsecurity.com plexicus.ai
Pricing
$24 / Monthly (1 resource) Official pricing
Company Startup from India · 1 - 9 employees · 2022 —
Listed in

About Onam Security and Plexicus

In their own words, as submitted to SaaSHub.

Onam Security
Plexicus

Onam Security is a unified cloud security platform — CSPM, CNAPP and SSPM on a single security graph instead of six stitched-together products. One deployment covers posture management, attack-path analysis, identity and entitlements (CIEM), data security posture, container and Kubernetes...

Read more about Onam Security

No description of Plexicus yet.

Features and specs

What each product offers, as listed by its team.

Onam Security 14 features
Plexicus 5 features
  • Posture rules
    11,346 rule definitions across 7 clouds
  • Cloud providers
    7-- AWS, Azure, GCP, OCI, Alibaba Cloud, IBM Cloud, Kubernetes
  • Cloud services covered
    549
  • SaaS platforms (SSPM)
    8 — Microsoft 365, SharePoint, Google Workspace, GitHub, GitLab, Snowflake, Dynamics 365, Okta
  • CIS SaaS Benchmark rules
    433 across six SaaS benchmarks
  • Compliance frameworks
    78, mapped to a single control set
  • Deployment
    Agentless — read-only cloud credentials, no sidecars or per-module agents
  • Attack Path Visualization
    MITRE ATT&CK-mapped paths with hops-to-breach and blast radius
  • Identity security (CIEM)
    Overprivileged identities, admins without MFA, wildcard policy detection
  • Data security (DSPM)
    PII discovery, public buckets, unencrypted and cross-region stores
  • Container & Kubernetes
    1,508 container/K8s rules — image CVEs, RBAC violations, privileged pods
  • Cloud detection & response
    Runtime detection on the same graph as posture
  • Risk quantification
    FAIR-model annual loss expectancy, in dollars
  • Optional host agent
    Opt-in onam-agent for OS package-level vuln depth (Linux, macOS, Windows)
  • AI-Powered Vulnerability Detection
    Plexicus leverages artificial intelligence to automatically scan codebases and identify security vulnerabilities, potentially catching issues that traditional static analysis tools might miss.
  • Automated Remediation Suggestions
    The platform reportedly offers AI-generated fix suggestions or automated patching for detected vulnerabilities, which can significantly speed up the remediation process for development teams.
  • Integration with Development Workflows
    Plexicus is designed to integrate into existing CI/CD pipelines and developer tools, allowing security checks to be embedded directly into the software development lifecycle rather than being a separate, disruptive process.
  • Reduced Manual Security Review Time
    By automating vulnerability scanning and prioritization, the platform can reduce the amount of time security teams need to spend manually reviewing code, allowing them to focus on more complex issues.
  • Continuous Monitoring Capabilities
    The platform supports ongoing, continuous security monitoring of applications and infrastructure, helping organizations catch new vulnerabilities as code changes rather than relying solely on periodic audits.

Possible disadvantages

  • Limited Public Track Record
    As a relatively newer entrant in the AI-driven application security space, Plexicus may have a smaller customer base and fewer publicly available case studies or independent reviews compared to established competitors.
  • Potential for False Positives/Negatives
    AI-based vulnerability detection systems, while powerful, can sometimes generate false positives or miss context-specific issues, requiring human security experts to still validate findings.
  • Learning Curve for Full Feature Utilization
    Teams unfamiliar with AI-driven security tools may need time to learn how to effectively configure, interpret, and act on the platform's outputs and recommendations.
  • Dependency on AI Model Quality
    The effectiveness of the platform is closely tied to the quality and training of its underlying AI models, meaning results could vary based on the types of codebases or vulnerabilities being analyzed.
  • Integration Complexity for Legacy Systems
    Organizations with older, legacy codebases or non-standard development environments may face challenges integrating Plexicus smoothly into their existing security and development infrastructure.

Analysis

An editorial look at what each product does well and who it suits.

Onam Security
Plexicus

No analysis of Onam Security yet.

Overall verdict

  • Plexicus is an AI-driven application security platform focused on automating vulnerability detection, remediation, and code security workflows; it appears to be a solid choice for organizations looking to integrate AI into their AppSec pipeline, though as with any specialized security tool, it's best evaluated against your specific tech stack and compliance needs before full adoption.

Why this product is good

  • Uses AI to automate detection and remediation of security vulnerabilities in code, reducing manual review time
  • Integrates security scanning into existing developer workflows (CI/CD, IDEs) for a shift-left security approach
  • Aims to reduce false positives common in traditional static analysis tools through smarter AI-driven triage
  • Provides actionable remediation guidance rather than just flagging issues, helping developers fix problems faster
  • Designed to scale across large codebases and multiple repositories, useful for growing engineering teams

Recommended for

  • Development teams wanting to embed automated security checks directly into their CI/CD pipelines
  • Organizations aiming to reduce the burden of manual code security reviews using AI assistance
  • AppSec and DevSecOps teams looking for faster vulnerability remediation workflows
  • Companies scaling engineering teams that need consistent, automated security coverage across many repos
  • Teams evaluating modern AI-based alternatives to traditional static/dynamic analysis tools

Videos

Walkthroughs and reviews on video.

Onam Security 5 videos + Add
Plexicus 0 videos + Add

SaaS Security Posture Management: Why Your CSPM Stops at the Cloud Account

More videos

  • - Agentless Cloud Security: Why Rollout Time Is Exposure Time
  • - Cloud Security Prioritization: Built to Find, Not to Decide
  • - Cloud Security Prioritisation: Which Finding Do You Fix First?
  • - Cloud Attack Path Remediation: Fix the Link, Not the Finding

No Plexicus videos yet. You could help us improve this page by suggesting one.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Onam Security
Plexicus
49% 49%
51% 51%
100% 100%
0% 0%
49% 49%
51% 51%
0% 0%
100% 100%

Questions & Answers

As answered by people managing Onam Security and Plexicus.

What makes your product unique?

Onam Security's answer

One security graph, not a suite. Most "unified" platforms are acquisitions stitched behind a single login — separate data models, separate consoles, findings that never meet. Onam was built from one inventory and one rule model, so connecting a single cloud account activates every capability at once: posture, attack paths, identity, data, containers, SaaS and detection. That design produces things a stitched suite structurally cannot. SaaS posture sits on the same graph as cloud posture, so a Google Workspace admin without MFA and an over-permissive IAM role can be scored as hops on one attack path. And coverage goes deep where others go wide — 11,346 posture rules across 549 services on seven clouds, including OCI, Alibaba Cloud and IBM Cloud, which most competitors treat as a checkbox.

Why should a person choose your product over its competitors?

Onam Security's answer

Three reasons. First, consolidation that is real: one agentless connection replaces six tools and five dashboards, and there is nothing to install — read-only credentials, no sidecars, no daemons on your nodes. Second, prioritisation you can act on. Attack-path analysis cuts thousands of findings to the handful an attacker could actually chain, each mapped to MITRE ATT&CK with hops-to-breach and blast radius, and risk is expressed in dollars via the FAIR model rather than another severity label. Third, breadth without shallowness: 78 compliance frameworks from a single control set, 7 clouds and 8 SaaS platforms on one graph, and rules defined in versioned YAML rather than hardcoded — so coverage is auditable and extensible instead of a marketing number.

How would you describe the primary audience of your product?

Onam Security's answer

Small and mid-sized security teams carrying enterprise-sized cloud estates. The typical user is a cloud security engineer, security architect or head of security at an organisation running two or more clouds plus a heavy SaaS footprint, responsible for thousands of assets with a team of two to twenty people. They are the teams for whom the six-product approach never worked — not because they could not buy the tools, but because nobody had the headcount to wire them together and triage five queues. Compliance leads are a strong secondary audience, particularly at organisations under multiple overlapping regimes that need one control set to answer to all of them.

What's the story behind your product?

Onam Security's answer

Onam was built by people who have run incident response, threat hunts and cloud architecture reviews — not by a marketing team that later hired security. The frustration that started it was specific: paying for six products, wiring five dashboards, and still missing the finding that mattered. The conclusion was that fragmentation is not a UI problem to be solved with another dashboard; it is a data-model problem. Findings cannot be correlated if each product holds its own inventory in its own schema. So Onam started at the other end — one inventory, one rule model, one graph — and built the capabilities on top of that rather than bolting them together afterwards.

Which are the primary technologies used for building your product?

Onam Security's answer

Python and FastAPI power the backend, with a single backend-for-frontend gateway exposing roughly 166 endpoints across 60 routers, plus Pydantic for validation and SQLAlchemy over PostgreSQL for the inventory and findings data model. Attack-path analysis runs on a Neo4j property graph, per tenant, with roughly 25 catalog-driven edge derivers. All 11,346 posture rules are defined in human-readable YAML and versioned in a catalog — the platform loads and evaluates rules, never hardcodes them. Cloud collection uses provider SDKs and read-only APIs: the AWS SDK, Azure Management API, GCP Cloud Asset API and equivalents. The console is TypeScript, React and Next.js with Tailwind CSS. The platform runs as multi-tenant SaaS.

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