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Cosmipher AI Security Platform

See the risk. Prove the weakness. Control the action.

Four products share one inventory, risk graph, policy model, and evidence chain, so security teams can move from an unknown AI asset to a verified control without losing context.

Assess an AI systemDiscuss your architecture

One connected evidence system

Follow one risk from discovery to verified control.

The Cosmipher Decision Evidence Graph is the shared platform foundation: every product adds evidence to the same asset, authority, policy, release, and decision history.

COSMIPHER DECISION EVIDENCE GRAPHOne illustrative system · evidence preserved across every product
Shared platform foundation, not a fifth product
  1. 01DiscoverAgentSPM
  2. 02VerifySupply Chain Security
  3. 03AttackAI Security Testing
  4. 04DecideAI Firewall
  5. 05ControlAI Firewall
  6. 06ProveTesting + shared evidence
01 / AgentSPM

A support agent has excessive reach.

Discover
INPUT EVIDENCE

Connected asset, identity, tool, data, ownership, and approval evidence

PRODUCT TRANSFORMATION

Resolve the path from the agent sponsor through delegated identity and MCP tool to restricted customer records.

DECISION OUTPUT

Inspectable exposure path with an accountable owner

02 / Supply Chain Security

The deployed model receives version-bound trust context.

Verify
INPUT EVIDENCE

Artifact identity, composition, genealogy, inspection evidence, approvals, and limitations

PRODUCT TRANSFORMATION

Bind upstream provenance and inherited conditions to the exact model version used by the agent.

DECISION OUTPUT

Release evidence attached to the production asset

03 / AI Security Testing

A relevant attack follows the real path to impact.

Attack
INPUT EVIDENCE

Authorized target, graph context, exact model version, approved techniques, and recovery constraints

PRODUCT TRANSFORMATION

Use reconnaissance and multi-step testing to exercise the observed retrieval, identity, MCP, and export path.

DECISION OUTPUT

Reproduced consequence with exact trace and starting state

04 / AI Firewall

The finding becomes a reviewed runtime boundary.

Decide
INPUT EVIDENCE

Attack mechanism, affected identity, tool arguments, data class, destination, and permitted business action

PRODUCT TRANSFORMATION

Draft and review a policy that restricts bulk export while retaining the case-limited support workflow.

DECISION OUTPUT

Versioned candidate policy with owner, reason, and rollback

05 / AI Firewall

The unsafe action is held before execution.

Control
INPUT EVIDENCE

Live interaction, retrieved instruction, agent identity, delegated purpose, tool request, and policy

PRODUCT TRANSFORMATION

Evaluate content together with authority and consequence at the runtime decision boundary.

DECISION OUTPUT

Bulk export held; case-limited read remains permitted

06 / Testing + shared evidence

The original attack verifies the changed control.

Prove
INPUT EVIDENCE

Original attack, reviewed policy, changed system version, legitimate control case, and runtime trace

PRODUCT TRANSFORMATION

Replay the attack unchanged and confirm both the prohibited and permitted outcomes.

DECISION OUTPUT

Control-verification record and permanent regression case

Illustrative operating model using non-customer data. Products are available for deployment; connector choice, automation depth, deployment coverage, and measured control results are confirmed for each environment.

Flagship pair

Start with visibility. Expand into control.

AgentSPM is the system of record and first market-entry product. AI Firewall is the runtime enforcement layer that becomes stronger with posture and identity context.

01 / DISCOVERFlagship · available

AgentSPM

Discover and continuously govern AI systems, agents, tools, identities, dependencies, and data connections from one living risk graph.

AgentSPM gives security and AI teams a current inventory of what exists, who owns it, what it can reach, and where configuration, permission, or approval gaps create exposure.

  • Discovery
  • Risk Graph
  • Exposure & Permissions
  • Governance
  • AI Onboarding
Explore AgentSPM
AgentSPMIllustrative product view
Discover and governGRAPHrelationship evidence
Selected path requires review
  1. 01
    support-agent-prodAgent → MCP → customer records
    Review
  2. 02
    research-assistantOwner verified · authority bounded
    Clear
  3. 03
    vendor-model-07Approval expired · dependency changed
    Action
02 / CONTROLFlagship · available

Cosmipher AI Firewall

Inspect, authorize, control, and explain AI interactions and autonomous actions at the runtime decision boundary.

Cosmipher AI Firewall evaluates prompts, responses, retrieval, memory, identities, tools, and agent behavior together, then applies the policy decision before impact.

  • Runtime Inspection
  • Guardrail Studio
  • MCP & Tool Control
  • Agent Identity
  • RAG & Data Protection
  • Response & Forensics
Explore AI Firewall
AI FirewallIllustrative product view
Control and investigateHOLDdecision before execution
Human approval required
  1. 01
    Prompt and retrievalIndirect instruction isolated
    Review
  2. 02
    Agent identityPurpose verified · scope limited
    Clear
  3. 03
    Tool requestWrite action exceeds session authority
    Action

Complete the platform

Add validation and asset trust without adding silos.

03 / TESTAvailable for deployment

Cosmipher AI Security Testing

Continuously discover, reproduce, remediate, and retest exploitable weaknesses across AI systems and agents.

Combine attacker-style reconnaissance, automated multi-step testing, reproducible evidence, and managed expert escalation in one assurance workflow.

  • Recon
  • Automated Red Teaming
  • Attack Atlas
  • CI/CD Assurance
  • Managed RTaaS
Explore AI Security Testing
04 / VERIFYAvailable for deployment

Cosmipher AI Supply Chain Security

Verify the integrity, provenance, safety, and ownership of models, datasets, artifacts, and dependencies before and after release.

Build one trust decision from AI-BOM and genealogy, deep artifact inspection, poisoning and backdoor evidence, model-IP risk, and signed release records.

  • AI-BOM & Genealogy
  • Artifact Scanning
  • Poison & Backdoor Detection
  • Model IP Protection
  • Attestation
Explore AI Supply Chain Security

Deployment and data flow

Available products. Environment-specific implementation.

Cosmipher does not require a buyer to infer readiness from a roadmap. The products are available for deployment; the exact interfaces, permissions, data path, failure behavior, and operating handoff are confirmed before implementation.

Discuss your deployment boundary
  1. 01

    Confirm the control point

    Identify the owned system, authoritative sources, available interfaces, and the decision Cosmipher must support.

  2. 02

    Set the data boundary

    Agree the fields, permissions, purpose, location, retention, and destinations before access or technical exchange begins.

  3. 03

    Deploy the selected product

    Connect the approved sources or insertion point, apply least privilege, and configure observation, testing, enforcement, or release controls.

  4. 04

    Validate and hand over

    Exercise the legitimate and unsafe paths, document failure behavior and limitations, then give the operating team an inspectable decision trail.

The Cosmipher advantage

A finding should make the next control smarter.

Point products stop at their own dashboard. Cosmipher is structured so discovery directs testing, testing improves enforcement, and every decision strengthens the shared evidence chain.

  1. 01

    One risk graph

    Asset, owner, identity, permission, data, dependency, test, and runtime context stay connected across the products you use.

  2. 02

    Test-to-protect loop

    Turn a confirmed attack into a candidate policy, deploy it through review, then replay the same attack to prove the control.

  3. 03

    Identity-aware runtime

    Evaluate a tool action against the agent owner, delegated authority, approved purpose, live behavior, and target data.

  4. 04

    Supply-to-runtime lineage

    Carry model, dataset, artifact, provenance, and approval evidence from build-time trust into production decisions.

  5. 05

    One evidence chain

    Keep posture, testing, enforcement, and investigation events in a traceable record instead of separate reports and screenshots.

Works with the security stack

Keep the controls you trust. Add the AI decision context they cannot provide.

Cosmipher operates as a connected AI-security decision layer, not a replacement for cloud, identity, network, application, data, or security-operations foundations.

Existing controlWhat it already seesAI decision gapCosmipher contribution
CNAPP / CSPM

Infrastructure, configuration, workload, and cloud identity

Agent purpose, delegated tool reach, AI ownership, and action paths

AgentSPM adds the AI asset and relationship decision layer.

WAF / API gateway

Requests, routes, schemas, rate, and network policy

Retrieved instructions, model context, agent authority, and tool consequence

AI Firewall adds context-aware authorization and proportionate action.

IAM / DLP

Identity entitlement and sensitive-data patterns

Whether this agent action serves the approved purpose across a multi-step session

AgentSPM and AI Firewall connect authority, purpose, data, and behavior.

SAST / SCA

Application code and conventional software dependencies

Model artifacts, weights, datasets, AI genealogy, and version-bound trust

Supply Chain Security extends release evidence to AI-specific assets.

Pentest / model evaluation

A bounded test or quality result at a point in time

Continuous attacker context, exact control replay, and retained regression evidence

AI Security Testing turns a reproduced failure into durable assurance.

Start with one consequential system

Map the risk, choose the first control, and define what proof looks like.

Request a scoped assessmentTalk to Cosmipher