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COSMIPHER AI SECURITY ASSESSMENT

Turn one consequential AI boundary into a decision-ready security record.

Select an AI estate, an agent action path, or an exact release candidate. Define the boundary, examine the relevant exposure and failure paths, and structure the evidence required for an adoption, runtime-control, or release decision.

  • 01One bounded decision
  • 02Written authority before testing
  • 03Evidence tied to material change
ASSESSMENT BOUNDARYILLUSTRATIVE METHOD
STARTING OBJECTOne consequential AI boundary
AUTHORITY STATEScope required
  1. 01
    BOUNDDecision, owner, target, authority
  2. 02
    MAPContext, reachability, controls
  3. 03
    EXERCISEAuthorized failure paths
  4. 04
    DECIDEEvidence, conditions, limits
  5. 05
    VERIFYReplay, expiry, next action
DECISION RECORDEvidence remains tied to scope, versions, environment, owner, limitations, and change triggers.
Reference assessment structure. No access or testing is authorized through the public website.
CHOOSE THE STARTING DECISION

One assessment system. Three precise entry boundaries.

The selected path changes the scope, method, evidence structure, participating teams, limitations, and next conversation, not only the card title.

SELECTED ASSESSMENT / 01

AI Adoption Exposure Assessment

Connect discovered AI to purpose, owner, identity, data, tools, exposure, and the conditions required for a defensible adoption decision.

Boundary
One business unit, environment, AI estate, or suspected shadow-AI boundary
Method
Bound → Map → Exercise → Decide → Verify
Output
AI adoption exposure and decision record
Owner
Security and AI platform
Next step
Qualify fit, then agree written scope
DECISION QUESTIONWhich AI systems may proceed, under whose authority, and with which review conditions?

AI use is expanding faster than inventory, ownership, approval, or risk review can follow.

SCOPE TOPOLOGY

Follow the evidence from starting object to decision record.

  1. 01
    PurposeApproved business use
  2. 02
    OwnerAccountable decision maker
  3. 03
    AI systemAgent, model, app, or service
  4. 04
    AuthorityIdentity and permissions
  5. 05
    ReachabilityData, tools, and actions
  6. 06
    Decision recordConditions, exceptions, renewal

Illustrative assessment boundary. It is not a customer environment, product capture, supported-technology statement, or measured result.

QUESTIONS EXAMINED

Coverage begins with decision questions, not unsupported compatibility claims.

01
Estate

Which AI systems and dependencies are inside the named boundary?

02
Ownership

Who owns the business purpose, system, exception, and resulting decision?

03
Identity

Which human, service, and agent identities can exercise authority?

04
Data

What information can the system retrieve, transform, retain, or expose?

05
Action

Which tools and consequential operations are reachable from the system?

06
Validity

Which change to purpose, owner, model, access, or environment reopens approval?

These are assessment questions. Actual target, method, depth, access, and evidence are established through written scope.

BOUNDARY CONTROL

Specific enough to evaluate. Narrow enough to authorize.

IN SCOPE
  • Named agents, models, applications, MCP servers, tools, and AI services inside the agreed boundary
  • Business purpose, accountable owner, delegated identity, permissions, reachable data, and consequential actions
  • Existing approvals, exceptions, evidence sources, review dates, and material-change triggers
CONDITIONAL
  • Artifact provenance and dependency evidence when a model, dataset, package, or adapter affects approval
  • Targeted adversarial testing when an exposure must be validated rather than recorded
  • Runtime control analysis for systems already permitted to perform consequential actions
OUT BY DEFAULT
  • Unrelated business units, tenants, repositories, endpoints, or production systems
  • Legal certification, universal compliance conclusions, or a complete enterprise inventory outside scope
  • Credentials, production data, or confidential architecture submitted through the public website
ASSESSMENT METHOD

Bound. Map. Exercise. Decide. Verify.

  1. 01Bound

    Name the estate boundary, adoption decision, accountable owner, environment, exclusions, and evidence period.

    Authorized scope record
  2. 02Map

    Relate each observed AI system to purpose, ownership, identity, data reachability, tools, dependencies, and current controls.

    Scoped relationship graph
  3. 03Exercise

    Examine the exposures that could materially change approval; add targeted validation only when separately authorized.

    Exposure and validation register
  4. 04Decide

    Separate supported adoption, conditional adoption, exception, remediation, and unresolved evidence states.

    Adoption decision record
  5. 05Verify

    Assign owners, evidence expiry, material-change triggers, renewal conditions, and the next required control action.

    Review and renewal plan
ILLUSTRATIVE OUTPUT STRUCTURE

Inspect the record before discussing the engagement.

NOT A PRODUCT CAPTURE OR CUSTOMER RECORDAI adoption exposure and decision record
DECISION ARTIFACT

AI adoption decision record

A bounded record joining the observed system, accountable owner, reachable consequence, supporting evidence, unresolved conditions, and next review trigger.

ILLUSTRATIVE DECISIONConditional adoption
01System boundaryRecorded
Business support agent / approved tenant / named workflow
02Owner and purposeRecorded
Owner recorded; intended customer-support purpose bounded
03Reachable consequenceReview
Customer records and ticket update action require joint review
04Decision conditionsReview
Restrict write authority; retain review evidence; assign renewal date
05Change triggerOpen
Reassess after model, tool, permission, data-source, or purpose change

The record remains tied to its named system, versions, environment, evidence sources, owner, limitations, observation period, and change trigger.

PRODUCT PATHAgentSPM + AI Supply Chain Security when artifact trust changes the decision

Supporting teams: Business owner, IAM, privacy, procurement, and GRC.

RESPONSIBILITY MODEL

Authority and evidence remain shared, explicit, and bounded.

The assessment begins only when the people responsible for the system, evaluation, safeguards, and resulting decision understand their part.

01

Authorized system owner

  • Confirm lawful authority and accountable ownership
  • Describe the intended business purpose and unacceptable consequence
  • Approve the environment, access route, evidence handling, and participant list
02

Cosmipher

  • Propose the minimum useful assessment boundary
  • Define the method, evidence structure, safeguards, and limitations
  • Keep observations tied to the agreed system, versions, environment, and period
03

Agreed jointly

  • Rules of engagement and excluded systems
  • Stop conditions, escalation contacts, schedule, and communication
  • Decision owner, remediation handoff, evidence validity, retest, and closure
ASSESSMENT READINESS

Prepare the decision before preparing the data.

A detailed technical transfer is not the first step. Start with authority, ownership, the decision to be made, the unacceptable consequence, and the smallest useful boundary.

  • A named owner can authorize the target.
  • One adoption, action, or release decision is explicit.
  • A safe environment or controlled method can be discussed.
  • The relevant technical and business owners can participate.
  • Detailed evidence can move through an approved channel after scope.
  • Stop conditions and escalation contacts can be agreed before testing.
ENGAGEMENT DISTINCTIONUnderstand what each first step does.
PathPurposeTesting authorityOutput
Website requestQualify the decision and responsible peopleNoScoping conversation
Product demoExplain workflows using approved or simulated materialNoProduct-fit discussion
AI Security AssessmentEvaluate one agreed AI boundaryOnly after separate written scopeDecision-specific evidence record
Penetration test or red teamExercise an authorized target under engagement-specific rulesYes, when separately contracted and authorizedTechnical findings and reproducible evidence
Certification or legal auditProvide a formal independent or legal conclusionNot implied by this assessmentOutside the assessment claim
EVIDENCE VALIDITY

A decision is only as current as the system it describes.

The record must expose what was examined, what remained outside scope, and which change requires replay or renewal.

  1. 01
    Baseline bound

    System, versions, environment, evidence sources, owner, scope, and limitations are recorded.

  2. 02
    Evidence assembled

    Observed exposure, exercised cases, control state, remediation, and unresolved questions are joined.

  3. 03
    Decision recorded

    The accountable owner can interpret the result within the stated boundary and validity period.

  4. 04
    Material change

    A model, prompt, retrieval, identity, permission, tool, artifact, data, policy, purpose, or environment changes.

  5. 05
    Renew or invalidate

    Affected evidence is replayed, renewed, superseded, or explicitly marked no longer sufficient.

ASSESSMENT BOUNDARY

An assessment does not certify that an AI system is universally secure, safe, compliant, or free from future failure. It supports a decision inside the named scope, versions, environment, methods, evidence sources, exclusions, and observation period.

CLAIM AND PROOF STATE

Know what is published, scoped, and demonstrated by evidence.

The public method defines how the decision is structured. The engagement determines the exact boundary. Only observed evidence can support a finding or outcome.

01

Published method

Decision paths, boundary model, responsibility, assessment stages, record structure, limitations, and evidence-validity logic.

02

Defined during scope

Target, environment, access, testing depth, safeguards, stop conditions, participants, evidence handling, output format, and retest treatment.

03

Supported by engagement evidence

Observed findings, exercised coverage, control response, performance, remediation state, replay result, and the decision the evidence can support.

EVALUATOR QUESTIONS

Resolve the operating questions before detailed scoping.

These boundaries keep the first conversation useful without turning a public request into an unsafe technical handoff.

01What should we share through the website or first email?

Share only the decision, system type, lifecycle stage, responsible team, and high-level non-sensitive context. Do not send credentials, source code, production data, customer records, vulnerability details, exploit material, or confidential architecture through the public channel.

02Does contacting Cosmipher authorize access or testing?

No. A message or form submission begins qualification only. Access, scanning, installation, connection, testing, or exploitation requires the authorized owner, written scope, an approved environment, rules of engagement, safeguards, contacts, and stop conditions.

03Can an assessment begin outside production?

The environment is selected during scoping according to the decision, representative behavior required, available safeguards, and the system owner's authorization. The website does not imply that production access is necessary or accepted.

04Which teams should participate?

The accountable system or release owner should participate. Depending on the path, the working group can include security, AI platform, application engineering, AppSec, IAM, SecOps, MLOps, data owners, model risk, privacy, GRC, and the business control owner.

05How is this different from a product demo?

A demo explains product workflows using approved or simulated material. An assessment considers one agreed customer boundary and can include examination or testing only after separate written authorization. A demo request never authorizes assessment activity.

06Does an assessment certify that the system is secure or compliant?

No. The resulting evidence is limited to the agreed target, environment, versions, methods, evidence sources, exclusions, and time period. Framework mapping can organize technical evidence but does not create legal advice, certification, or a universal guarantee.

07What happens when the AI system changes?

The decision record identifies material-change triggers. A relevant change can invalidate all or part of the earlier evidence and require targeted replay, evidence renewal, or a newly bounded assessment.

08How are detailed evidence and access information handled?

The first public contact does not collect them. If detailed material is required, the parties first agree the approved channel, purpose, access method, participants, handling restrictions, retention, and deletion expectations as part of scope.

START WITH SCOPE

Bring the decision. Keep sensitive material out of the first message.

Share the assessment path, system type, lifecycle stage, responsible team, and high-level decision. Access details and technical evidence belong in an approved channel after authority, scope, safeguards, and handling conditions are agreed.

  • No credentials, source code, datasets, vulnerability details, or customer records
  • No production access implied or requested
  • No testing before written authorization and rules of engagement
AFTER YOU CONTACT COSMIPHER
  1. 01
    Initial context

    Share the path, decision, owner, lifecycle stage, and non-sensitive system context.

  2. 02
    Mutual fit

    Confirm that the decision and boundary match the assessment method and responsible teams.

  3. 03
    Written scope

    Agree target, authority, exclusions, safeguards, stop conditions, evidence handling, and decision owner.

  4. 04
    Authorized start

    Assessment activity begins only after the approved scope and rules of engagement are in place.

DIRECT SCOPING CHANNEL

Discuss one assessment boundary with Cosmipher.

The prepared email includes only the decision fields needed for an initial, non-sensitive scoping conversation.

Start the scoping email
Contact
Services@cosmipher.com
Request state
Qualification only
Testing authority
Not granted
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Cosmipher AI Security Assessment - Cosmipher