# AI Red Team Assessment Executive Summary
Executive Summary
This executive summary turns adversarial AI testing into a business decision. It does not dump raw payloads or theatrics. It shows what was tested, which attack paths were validated, what impact matters, what blocks launch, what must be fixed, and what requires retest.
The assessment found two critical issues: retrieval authorization is not yet proven end-to-end, and sensitive tool actions can be queued with insufficient approval context.
Release recommendation
Continue controlled pilot use, but do not expand enterprise rollout until critical retrieval and tool-authority findings are remediated and retested.
Assessment Snapshot
Executive meaning
Assessment scope
Assessment scope
| Area | Tested | Executive concern |
|---|---|---|
| Prompt injection | yes | untrusted instructions influencing model behavior |
| Retrieval manipulation | yes | poisoned or malicious content changing answers |
| Cross-tenant exposure | yes | restricted content appearing in generated responses |
| Tool misuse | yes | AI authority exceeding intended user action |
| Approval bypass | yes | weak human review before sensitive actions |
| Trace reconstruction | yes | inability to investigate AI behavior after incident |
| Provider boundary | yes | unclear customer-facing claims about model data use |
Assessment summary chart
The chart summarizes critical, high, and medium findings, plus release blockers and retest needs.
Validated findings
Validated Findings
Retrieval authorization evidence is incomplete
The assessment could not confirm that authorization always survives indexing, chunking, retrieval, reranking, and prompt assembly.
Impact
Sensitive tool actions can be queued with insufficient approval context
The agent can prepare high-impact actions, but approval screens do not always show enough context for meaningful human review.
Indirect prompt injection can alter retrieved-answer behavior
Malicious instructions embedded in retrieved content can influence generated responses when source trust and instruction priority are not clearly separated.
AI traces contain sensitive data without complete retention policy
Prompt, retrieval, model output, and tool-call traces may include customer-sensitive data and do not yet have complete AI-specific retention and access rules.
Model provider boundary claims are not ready for security review
Engineering and legal assumptions about provider data handling are not yet consolidated into a buyer-ready statement.
Validated attack paths
Validated attack paths
| Attack path | Severity | Blocked by |
|---|---|---|
| Indirect prompt injection through retrieved content | High | source trust labeling and retrieval instruction isolation |
| Unauthorized retrieval to generated data leak | Critical | authorization-preserving retrieval and source ACL tests |
| Thin approval to sensitive action execution | Critical | approval context bundle and human-only critical approvals |
Safe reporting note
Release blockers
Blocker 1: Retrieval authorization must be proven
Do not expand source coverage until sources have enforceable ACL metadata and end-to-end retrieval authorization tests.
Blocker 2: Critical tool actions remain blocked
Do not enable customer-visible, billing-impacting, destructive, privileged, or third-party webhook execution until approval bundles and trace evidence are validated.
Blocker 3: AI traces need sensitive evidence controls
Do not broaden production logging until AI traces have clear classification, access control, retention, redaction, and incident-response handling.
Remediation plan
Required remediation before retest
Executive remediation roadmap
| Priority | Remediation | Owner | Required before |
|---|---|---|---|
| 1 | Prove retrieval authorization end-to-end | Search Platform | enterprise rollout |
| 2 | Enforce action classes in AI gateway | AI Platform Engineering | expanding agent authority |
| 3 | Add approval context bundles | Product Operations | sensitive actions |
| 4 | Classify AI traces | Security Engineering | broad production logging |
| 5 | Approve provider boundary statement | Vendor Management and Legal | procurement review |
Retest criteria
Retest criteria
Related artifact: AI Risk Register
The red-team summary produces validated findings. The risk register turns those findings into owned remediation and executive risk decisions.
Related artifact: Agent Tool Permission Matrix
The permission matrix defines which tool actions remain blocked, conditional, approved, or denied after red-team findings.