01
Connect your agent endpoints
FortifAI integrates with LangChain, AutoGen, CrewAI, OpenAI Agents, and custom APIs.
Platform Architecture
Runtime Security For AI Agents
FortifAI integrates into your existing agent stack without forcing framework rewrites and enforces controls when agents actually act.
How FortifAI Works
Four runtime stages to move from exposure to enforceable security.
02
Run adversarial testing
The attack engine sends realistic payloads that target prompt boundaries, tools, memory, and output paths.
03
Detect runtime vulnerabilities
Findings are generated with evidence for prompt hijack, tool misuse, memory poisoning, and data exfiltration.
04
Map to threat benchmark categories
Each finding is aligned to established agentic threat benchmarks for triage and governance.
100% Coverage
Agentic Threat Coverage Map
Every attack surface category is covered by runtime controls. See the full threat model.
| ID | Threat | FortifAI Defense | Status |
|---|---|---|---|
| AA1 | Goal and Prompt Hijacking | Prompt guardrails and instruction boundary enforcement | Covered |
| AA2 | Memory Poisoning | Memory write controls and trusted-source validation | Covered |
| AA3 | Tool Misuse | Permission scoping with deny-by-default checks | Covered |
| AA4 | Privilege Escalation | Identity isolation and least-privilege roles | Covered |
| AA5 | Context Manipulation | Input/output sanitization and context integrity checks | Covered |
| AA6 | Unauthorized Exfiltration | Outbound data pattern detection and policy blocking | Covered |
| AA7 | Repudiation | Immutable execution logs with audit metadata | Covered |
| AA8 | Supply Chain Poisoning | Tool and dependency provenance validation | Covered |
| AA9 | Cascading Agent Failures | Containment controls and workflow circuit breakers | Covered |
| AA10 | Insufficient Observability | Decision telemetry, posture scoring, and runtime traces | Covered |
Why Traditional Security Falls Short
Legacy web-app controls do not model autonomous tool-using agent behavior.
Traditional tools
Traditional AppSec tools focus on static web surfaces.
FortifAI
FortifAI secures dynamic agent execution paths.
Traditional tools
SAST/DAST detect code defects before runtime.
FortifAI
FortifAI enforces controls during runtime agent behavior.
Traditional tools
Legacy tooling does not understand memory and tool chains.
FortifAI
FortifAI models memory, tools, and identity boundaries natively.
Traditional tools
General scanners do not align to agentic threat benchmarks.
FortifAI
FortifAI reports with standardized agentic threat framing by default.
Competitive Comparison
FortifAI vs AI Security Tools
FortifAI emphasizes deterministic adversarial testing and runtime evidence without exposing sensitive responses to secondary models.
| Capability | FortifAI | Promptfoo | Lakera Guard | Protect AI | LLM Guardrails |
|---|---|---|---|---|---|
| Adversarial testing for AI agents | Yes | Limited | No | Partial | No |
| Prompt injection testing | Yes | Yes | Yes | Yes | Yes |
| Tool abuse detection | Yes | No | Partial | Partial | No |
| Memory poisoning detection | Yes | No | No | Partial | No |
| CLI workflow support | Yes | Yes | No | No | No |
| CI/CD integration | Yes | Limited | No | Partial | No |
| Evidence-based reports | Yes | Partial | No | Partial | No |
| No secondary LLM leakage | Yes | No | No | No | No |
Zero Secondary LLM Leakage
FortifAI does not require forwarding sensitive outputs to another model for classification. Analysis is evidence-driven and deterministic.
Ready To Secure Your Agent Pipeline?
Add runtime defenses built specifically for autonomous agent behavior across tools, memory, and orchestration layers.