Know what your agent can do wrong
before it runs in production.

Pre-deployment security analysis for AI agents. We audit your agent's code, tool configurations, and permission model — surfacing prompt injection paths, privilege escalation risks, and multi-agent trust chain vulnerabilities before you ship.

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What we analyze

Three layers of risk,
audited before deployment.

AI agents introduce attack surfaces that traditional security tools don't understand. We analyze the layers specific to agentic systems — before they're live.

Tool & API Security

Can your agent be manipulated into executing unauthorized tool calls via prompt injection? We trace every tool call path for SSRF, RCE, and API abuse vectors — including indirect injection through retrieved context and chained tool outputs.

Prompt injection → tool call · SSRF · RCE · API abuse

Permission & Privilege Model

We audit every tool's permission scope against the least-privilege principle. Over-permissioned tools, missing tool-level IAM boundaries, and dynamic authorization gaps are mapped before they become blast radius in production.

Least privilege audit · tool-level IAM · privilege escalation paths

Multi-Agent & Memory Risk

In multi-agent systems, one compromised agent can pollute the trust chain of the entire system. We also assess long-term context memory for poisoning vectors and malicious knowledge injection paths that shift agent behavior over time.

Trust chain analysis · context poisoning · knowledge injection

What we surface

Agentic attack surface
mapped before it's exploited.

Agent systems introduce a new class of vulnerabilities that don't appear in traditional code review. Our analysis covers all of them.

Agent attack surface

What attackers target in agentic AI systems

Tool call manipulation — prompt injection forces unauthorized API, shell, or DB calls
Privilege escalation via tool chaining — combining limited-scope tools to reach sensitive resources
SSRF via external tool inputs — agent-initiated requests reaching internal infrastructure
Long-term context poisoning — gradual corruption of agent memory to shift behavior
Multi-agent trust chain pollution — one compromised agent propagating malicious instructions
Auto-execution of sensitive operations — delete, transfer, modify without human-in-the-loop controls

What our analysis delivers

Pre-deployment findings with actionable fix guidance

CVE-class findings mapped to your specific agent configuration
Reproduction steps for each identified attack path
Permission model gaps and recommended least-privilege scoping
Tool-level IAM recommendations per agent role
Multi-agent trust boundary assessment with isolation recommendations
Memory and context handling risk assessment with remediation guidance

How it works

Three-stage analysis
before you deploy.

① Code & Config Ingestion

We ingest your agent code, tool definitions, permission configurations, and system prompts. No production access required — analysis runs against your codebase and configuration files in a controlled environment.

Agent code · tool schemas · permission configs · system prompts

② Multi-Layer Analysis

Static code audit finds structural vulnerabilities. Behavioral simulation traces prompt injection and tool-chaining attack paths. Permission model review maps privilege escalation routes across all tool combinations.

Static audit · behavioral simulation · permission graph analysis

③ Pre-Deployment Report

You receive a prioritized findings report with severity classification, reproduction steps, and concrete fix guidance — before a single line of your agent touches production infrastructure.

Severity-ranked · reproducible · fix-ready · signed evidence entry

After deployment: Evidence-AIDR takes over.

Agent Security covers everything before your agent goes live. Once deployed, Evidence-AIDR monitors runtime behavior continuously — detecting prompt injection attempts, policy bypass, and anomalous tool usage in real traffic, while maintaining a tamper-evident audit trail any regulator can independently verify.

Together, they cover the full agent lifecycle: security-tested before deployment, monitored and auditable after.

See Evidence-AIDR →

Know what your agent can do wrongbefore it runs in production.

Three layers of risk,audited before deployment.