DefenseEye.ai

Enterprise AI security consulting

AI Security Consulting for AI Agents and LLM Applications

DefenseEye assesses and secures AI agents and LLM applications before and after they go live: threat modeling, adversarial testing for prompt injection and tool misuse, review of agent identities and permissions, and a prioritized remediation plan with re-test evidence. For CISOs, security architects and enterprise risk leaders.

Security questions AI agents raise

  • Prompt injection through what the agent reads: Instructions hidden in emails, documents or web pages can redirect an agent that retrieves them.
  • Excessive agency: Agents often hold more tools, permissions or autonomy than their task needs, so a mistake or manipulation has a large blast radius.
  • Sensitive information exposure: Customer and internal data can leave through a response, a tool argument or an outbound call.
  • Non-human identities nobody owns: Agent credentials are shared, long-lived or untracked, and rarely reviewed like human accounts.

How an AI security assessment works

A focused assessment of one agent or application, or a program-level review across several.

  • 1. Scope: Agree the agents, tools, data and environments in scope, and the rules of engagement for testing. Deliverables: Scope and rules of engagement; Asset and data-flow inventory.
  • 2. Threat model: Map how each agent could be misused, using OWASP LLM risks and MITRE ATLAS techniques. Deliverables: Agentic threat model; Trust-boundary diagram.
  • 3. Test: Run authorized adversarial tests: direct and indirect injection, tool misuse, data exposure and approval bypass. Deliverables: Test cases and results with redacted evidence.
  • 4. Prioritize: Rank findings by business impact and exploitability, not only by technical severity. Deliverables: Prioritized findings; Remediation plan with owners.
  • 5. Remediate and verify: Support the fixes, then re-run the failed tests to prove they hold. Deliverables: Re-test results; Evidence pack for risk and audit.

Agentic AI threats and the controls we assess

  • Prompt injection (OWASP LLM01): Example in an AI agent — A retrieved document tells the agent to ignore its rules. Controls we test — Input inspection, trusted instructions, retrieval source rules.
  • Sensitive information disclosure (LLM02): Example in an AI agent — An answer includes another customer's data. Controls we test — Session-bound data access, output redaction, response checks.
  • Excessive agency (LLM06): Example in an AI agent — An agent can send external email it never needs. Controls we test — Tool allowlists, scoped permissions, approval for high-impact actions.
  • Identity misuse: Example in an AI agent — An agent runs on a shared admin credential. Controls we test — Per-agent identities, short-lived tokens, access reviews.
  • Missing oversight: Example in an AI agent — A payment executes with no checker. Controls we test — Bound human approval, audit records, separation of duties.

Evidence, not just recommendations

  • Tested in a working demonstration: DefenseEye's DefyAIRisk runs these tests end to end in a synthetic banking environment: a cross-customer data request is caught, sent for approval, fixed and closed only after a passing re-test.
  • Banking scenarios: Payment without checker approval, unapproved external sends and instructions hidden in documents are part of the same demonstration.
  • Consulting and software are separate: An assessment does not require DefyAIRisk. We test with your tools or ours, and you own the findings.

Before we test

  • Written authorization and rules of engagement for any testing
  • A test or staging environment, or agreed limits for production
  • Architecture notes or a walkthrough of the agent and its tools
  • A security contact who can triage urgent findings

Frequently asked questions

What does an AI security assessment cover?
The agent's inputs, instructions, tools, permissions, data access, outputs and logging. We threat-model them, test the highest-risk paths and deliver prioritized findings with a remediation plan.
How is AI security testing different from a penetration test?
It adds attacks that target the model's behavior, such as prompt injection and goal hijacking, and checks what the agent can do with its tools, not only whether the surrounding application is exploitable.
Do we need to buy DefyAIRisk?
No. DefyAIRisk is DefenseEye's product; the consulting engagement stands on its own. Some clients may choose to use it for repeatable testing.
Do you test production systems?
Only with written authorization and agreed limits. We prefer a test environment and never run destructive tests against live systems.
Which frameworks do you use?
OWASP Top 10 for LLM Applications, MITRE ATLAS and the NIST AI RMF, mapped to your existing security controls. Mapping to a framework is not a certification.

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