Adversa AI

Adversa AI is an autonomous AI red-teaming and security company (founded 2021, Tel Aviv) that provides continuous security assessment for AI agents, LLMs, and GenAI applications. Its platform runs 300+ attack techniques — jailbreaks, prompt injection, and adversarial attacks — is OWASP- and NIST-mapped, runs its detection models on-prem so customer data is never exposed to external AI providers, and prioritizes every finding by real business impact with auto-generated remediation. Offerings include AI Threat Modelling, Continuous Security Assessment, Hardening & Remediation, and the AI Risk Quadrant (AIRQ) scoring framework. Adversa AI experts are co-leads and core members of NIST AI RMF, OWASP ASI, CoSAI, and CSA AI initiatives, and the company ships the open-source SecureClaw plugin/skill for hardening OpenClaw agents.

Adversa AI is profiled on the APIs.io network. Tagged areas include Company, AI Security, AI Red Teaming, LLM Security, and AI Agents.

Adversa AI’s developer surface includes engineering blog, signup flow, CLI, and 13 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

22.2/100 emerging ▬ flat Agent 4/100 human only Front door AI 6/6 dominant Heartbeat 61/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

0 APIs 1 Agent Skills

Company AI Security AI Red Teaming LLM Security AI AgentsAdversarial Machine LearningAI Governance Cybersecurity

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 22.2/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 2.8 / 17

Access Clarity 6.7 / 17

Operational Transparency 1.5 / 11

Contract Governance 1.9 / 10

Discoverability 4.7 / 9

Regulatory Posture 3.8 / 15

Agent readiness — 4/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 5 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes

12 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points
Developer Ergonomics scores 16.7 — up to +16.7 composite points
Access Clarity scores 39.5 — up to +12.1 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/adversa-ai/apis.yml: open an issue on github.com/api-evangelist/adversa-ai to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
Agent Skills (SKILL.md packages)	distribution	9.6 (thin)	-	1

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

Agent Skills

measured — observed by APIs.io (published)

Agent Skills 1

Packaged agent skills for driving this provider's APIs from an AI assistant.

secureclaw

AGENT SKILL

Security Posture 3

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Adversa Ai Domain Security

TLSv1.3 · DMARC

SECURITY

Adversa Ai Vulnerability Disclosure

Hackerone · contact published

SECURITY

Adversa Ai Trust Center

SOC 2 Type I, SOC 2 Type II, ISO 27001, GDPR, CCPA

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

SignUp

SignUp

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

AgentSkill

AgentSkill

LLMsTxt

LLMsTxt

WellKnown

WellKnown

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

CLI

CLI

Access & Security 5

Authentication, authorization, and security posture

TrustCenter

TrustCenter

Compliance

Compliance

DomainSecurity

DomainSecurity

VulnerabilityDisclosure

VulnerabilityDisclosure

Security

Security

Commercial 1

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: adversa-ai
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - security
  generated: '2026-11-06'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/adversa-ai.png
name: Adversa AI
description: Adversa AI is an autonomous AI red-teaming and security company (founded 2021, Tel Aviv) that provides continuous
  security assessment for AI agents, LLMs, and GenAI applications. Its platform runs 300+ attack techniques — jailbreaks,
  prompt injection, and adversarial attacks — is OWASP- and NIST-mapped, runs its detection models on-prem so customer data
  is never exposed to external AI providers, and prioritizes every finding by real business impact with auto-generated remediation.
  Offerings include AI Threat Modelling, Continuous Security Assessment, Hardening & Remediation, and the AI Risk Quadrant
  (AIRQ) scoring framework. Adversa AI experts are co-leads and core members of NIST AI RMF, OWASP ASI, CoSAI, and CSA AI
  initiatives, and the company ships the open-source SecureClaw plugin/skill for hardening OpenClaw agents.
url: https://raw.githubusercontent.com/api-evangelist/adversa-ai/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- foundry-group
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-17'
tags:
- Company
- AI Security
- AI Red Teaming
- LLM Security
- AI Agents
- Adversarial Machine Learning
- AI Governance
- Cybersecurity
tags_raw:
- Company
- Ai Security
- AI Red Teaming
- LLM Security
- Agentic AI
- Adversarial Machine Learning
- AI Governance
- Cybersecurity
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://adversa.ai
- type: Blog
  url: https://adversa.ai/topic/trusted-ai-blog/
- type: SignUp
  url: https://adversa.ai/get-demo/
- type: PrivacyPolicy
  url: https://adversa.ai/privacy-policy
- type: GitHubOrganization
  url: https://github.com/adversa-ai
- type: TrustCenter
  url: https://adversa.ai/security-trust/
- type: Compliance
  url: https://adversa.ai/security-trust/
- type: Packages
  url: packages/adversa-ai-packages.yml
- type: CLI
  url: cli/adversa-ai-cli.yml
- type: AgentSkill
  url: skills/_index.yml
- type: LLMsTxt
  url: llms/adversa-ai-llms.txt
- type: WellKnown
  url: well-known/adversa-ai-well-known.yml
- type: DomainSecurity
  url: security/adversa-ai-domain-security.yml
- type: VulnerabilityDisclosure
  url: security/adversa-ai-vulnerability-disclosure.yml
- type: Security
  url: security/adversa-ai-vulnerability-disclosure.yml
- type: Conformance
  url: conformance/adversa-ai-conformance.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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