Glacien · AgentShield — AI Security Testing on AWS
AgentShield

Red-team and prove every AI agent before it ships.

Glacien AgentShield tests enterprise AI agents against prompt injection, jailbreaks, data leakage, tool misuse, RAG poisoning, and approval bypass — and produces the evidence risk, audit, and compliance need to clear production.

InjecAgent · MINJA · OWASP ASIMITRE ATLAS v5.4Bedrock Guardrails · AgentCore Identity
Leakage cited as risk
83%
of enterprise leaders cite data leakage as the top AI agent adoption concern.
Over-privileged access
80%
cite agents having too much access as a critical adoption barrier.
Security slows adoption
69%
say security concerns are actively slowing AI agent rollout in their organisation.
Past-year incidents
88%
reported a confirmed or suspected AI agent security incident in the last 12 months.

Industry references — Okta & Zenity AI Agent Security 2026 survey of enterprise leaders. The risk surface is real; the remediation gap is bigger. AgentShield closes it before agents touch production.

In 30 seconds

What is AgentShield?

AI security testing for enterprise agents. Real attack patterns, real business misuse scenarios, real regulatory risk — tested before the agent reaches your customers, employees, or examiners.

Question 01

Can it be tricked by prompt injection?

We run the InjecAgent battery plus targeted scenarios on your prompts, system instructions, and retrieval pipeline — and we tighten guardrails until they hold.

Question 02

Can a user extract sensitive data?

Leakage scenarios test PII exposure, cross-user data access, regulated-content disclosure, and confidential document extraction.

Question 03

Can the agent call the wrong tool?

Tool-misuse testing exercises permissions, time-of-day controls, prerequisite checks, and unauthorised workflow execution paths.

Question 04

Can poisoned content steer it?

RAG poisoning scenarios test whether malicious or misleading documents in the retrieval corpus can alter responses or trigger unsafe actions.

Question 05

Can it bypass human approval?

Approval-bypass testing validates that sensitive actions actually require the right approvers, not just nominally.

Question 06

Do we have evidence for risk & audit?

Every test scenario, control mapping, finding, remediation, and re-test produces structured evidence ready for risk, audit, and compliance review.

The problem

App-sec testing was not designed for AI agents. AI agents need their own.

01

New attack surface

Prompts. Retrieval pipelines. Tool calls. Memory writes. Multi-agent flows. Each is a vector. None of them existed for SAST, DAST, or pen-test playbooks.

02

Risk teams cannot accept the unknown

“Can the agent be tricked?” is not an opinion. It needs structured testing, evidence, and a remediation plan — before risk approves production.

03

Production today, headline tomorrow

88% of organisations report an AI agent incident in the past year. The first time a finding becomes visible to a regulator, an auditor, or a journalist — it is too late.

AgentShield exists so risk, security, and engineering can put AI agents into production with the same confidence they put applications into production today.

One platform. Three outcomes.

Test for real attacks. Harden the agent. Produce examiner-grade evidence.

When risk, compliance, or the board asks “is this safe enough to ship,” AgentShield is the answer.

Outcome 1

Test against real attacks.

Prompt injection (InjecAgent), jailbreaks, tool misuse, data leakage, RAG poisoning (MINJA), identity bypass, HITL bypass, guardrail effectiveness — all run against your agent.

Red-teamATLASOWASP ASI
Outcome 2

Harden the agent.

Findings come with mitigation recommendations, Bedrock Guardrails tuning, prompt and retrieval hardening, policy controls, and approval-workflow design. Re-tested until they hold.

HardenGuardrails
Outcome 3

Produce defensible evidence.

Structured findings, test scenarios, control mapping, remediation status, and production-readiness evidence — for risk, audit, compliance, and regulator engagement.

Evidence
Attack families we test

Eight test families. One coverage report.

Each family is a discrete battery with hundreds of scenarios drawn from industry-standard frameworks. Coverage and findings appear in one structured report.

01

Prompt injection

Tests whether malicious instructions can override system prompts, business rules, retrieval constraints, or policy boundaries.

02

Jailbreak

Evaluates whether users can bypass restrictions, force unsafe outputs, or manipulate the agent into unauthorised behaviour.

03

Tool misuse

Checks whether the agent can call the wrong tool, at the wrong time, with excessive permissions, or execute unintended workflows.

04

Data leakage

Tests whether the agent exposes confidential, personal, regulated, or cross-user information across query patterns.

05

RAG poisoning

Assesses whether malicious or misleading documents in the retrieval corpus can influence responses or workflow decisions.

06

Identity & permissions

Validates that user identity, access controls, authorisation boundaries, and system permissions are actually enforced.

07

HITL bypass

Tests whether sensitive actions truly require the right approvals, escalations, and review points — or whether they can be skipped.

08

Guardrail effectiveness

Validates content filters, sensitive-information controls, grounding checks, and policy checks are working as expected.

What you get

A red-team report your risk team can act on.

Structured findings, mitigation, re-test, and evidence for production approval. Not a PDF with vague warnings.

Agent architecture & threat-model review
Prompt-injection & jailbreak test results
Tool misuse & identity test results
Data leakage & RAG poisoning scenarios
Human-approval bypass test results
Guardrail effectiveness review
Prioritised findings with remediation plan
Control mapping to internal policy & regulator
Production-readiness evidence pack
Where it lands first

Six typical AgentShield engagements.

Most enterprises engage AgentShield ahead of a specific production milestone — a launch, a regulator review, or a customer-facing pilot.

Pre-production security review

Test a new enterprise agent before release to employees, customers, or partners. Findings + remediation + re-test before sign-off.

Contact-centre agent red-team

Validate that customer-facing agents handle sensitive information, complaints, escalation, and compliance scenarios safely under attack.

Knowledge agent leakage testing

Check whether internal knowledge agents expose restricted documents, confidential policy content, or cross-tenant answers.

Workflow agent control testing

Test agents connected to ticketing, CRM, finance, HR, or operational workflows for unintended writes, escalations, and approvals.

Regulated industry AI readiness

Create risk evidence for banking, insurance, healthcare, government, and other regulated organisations — examiner-defensible.

Quarterly AI security assurance

Recurring red-team testing as prompts, models, knowledge sources, tools, and business workflows change — risk-controlled by design.

Built on AWS

AWS-native. Tested in your account.

AgentShield extends Bedrock Guardrails, AgentCore Identity, and AgentCore Policy. Tests run inside your AWS environment. Evidence is signed and stays in your control.

Bedrock Guardrails

Content filters, sensitive-information masking, contextual grounding checks, and Automated Reasoning policy validation — tuned against findings.

AgentCore Identity & Policy

Per-agent OAuth, on-behalf-of authentication, NHI governance, and Cedar policy enforcement validated against tool-misuse and bypass scenarios.

Observability & evidence

AgentCore Observability, CloudWatch, CloudTrail, and S3 capture the trace of every test scenario — reproducible, signed evidence ready for audit.

Security operations

AWS Security Hub, IAM Access Analyzer, Amazon Macie — findings published into your SOC workflow for ongoing assurance.

Layer
Service / capability
Guardrails
Amazon Bedrock Guardrails — content filters, sensitive-info masking
Grounding checks
Contextual grounding · Automated Reasoning policy validation
Sensitive data
Bedrock Guardrails sensitive-information filters · Amazon Macie
Agent identity
Amazon Bedrock AgentCore Identity
Policy enforcement
Amazon Bedrock AgentCore Policy · Cedar
Observability & evidence
AgentCore Observability · CloudWatch · CloudTrail · Amazon S3
Security operations
AWS Security Hub · IAM Access Analyzer · Amazon Macie
Workflow controls
AWS Step Functions · Lambda · API Gateway
Test frameworks
InjecAgent · MINJA · OWASP ASI · MITRE ATLAS v5.4 · custom industry scenarios
Procurement
AWS Marketplace · EDP commit applies
Start where you are

Four ways to engage AgentShield.

From a pre-launch security review to recurring quarterly assurance for organisations running multiple production agents.

Path 01 · Assess

Agent security assessment

For customers preparing to launch an AI agent.
  • Agent architecture review
  • Prompt & guardrail review
  • Retrieval & RAG risk review
  • Tool & API control testing
  • Identity & permission review
  • Risk findings + mitigation plan
Time to outcome
3-4 weeks
Path 03 · Govern

Governance & evidence

For enterprises that need audit-ready AI controls.
  • Guardrail design
  • Policy & control mapping
  • Evidence logging model
  • Approval workflow design
  • Compliance reporting dashboard
Time to outcome
2-3 months
Path 04 · Assure

Quarterly AI assurance

For organisations running multiple production agents.
  • Recurring security testing
  • Control-effectiveness review
  • New attack-scenario testing
  • Guardrail tuning
  • Executive assurance report
Cadence
Quarterly

Procurement via AWS Marketplace — Private Offers and Channel Partner Private Offers supported. Existing AWS commit (EDP) applies.

About Glacien

We red-team AI agents so risk teams can sign off.

Glacien builds, governs, operates, and tests AI agents for regulated enterprises. AgentShield is the security assurance step that turns “we built an agent” into “we built an agent risk has cleared, audit has signed, and the regulator has seen.”

AWS Select Partner with Agentic AI specialisation. Singapore-headquartered with onshore leadership and offshore engineering across India. We do not advise. We build, test, govern, and stand behind what we deliver.

Agentic AI, tested.

Ready to prove your agents are
safe enough to ship?

Book a 30-minute walkthrough. We will show a live red-team run against a reference agent, share the structured report risk teams use to sign off, and scope a security assessment for your highest-risk production candidate. No slides that waste your time.