AI and Agentic Threat Detection
Straiker's detection engine analyzes agentic traces and AI interactions to catch attacks that other solutions miss with >98% accuracy and sub-second latency.
Why detection benchmarks matter
Model vulnerability benchmarks tell you which LLM is inherently safer. This detection benchmark tells you how well your security layer actually stops AI and agentic threats, regardless of which model you deploy.
Agentic & GenAI Create New Attack Surfaces
Traditional security tools weren't built for AI agents & LLM-based applications. They can't see inside multi-step agent interactions, don't understand tool calls, and miss the subtle patterns that indicate an attack in progress. Straiker was purpose-built for this world.
Company
Accuracy
The percentage of all predictions the system gets right across both positive and negative cases.
False negative rate
The percentage of real issues the system fails to detect and incorrectly labels as safe.
False positive rate
The percentage of safe or benign cases the system incorrectly flags as an issue.
Straiker Defend AI's AI Detections
98.4%
0.4%
1.2%
Straiker Defend AI's Agentic Detections
98%
1%
1%
Similar companies, including Lakera and NOMA Security
72.9-90.2%
5.5-9%
4.3-21.6%
Straiker combines multiple expert models to deliver industry-leading accuracy at >98%, maintaining a healthy balance between detecting real threats and avoiding false alerts.
How Straiker Detects AI and Agentic AI Threats
Straiker’s detection engine was built specifically for generative AI and agentic AI. There is no retrofitting from legacy security tools.
Agentic Trace Analysis
Full visibility into multi-step agent interactions. We analyze both the complete trace and individual spans to catch attacks that unfold across multiple steps.
Real-Time Classification
Sub-second detection powered by our vision-language model approach, which compresses traces by 3-7x without sacrificing accuracy.
Comprehensive Threat Coverage
Full coverage across the OWASP Top 10 for Agentic AI. Purpose-built detectors for prompt injection, tool misuse, data exfiltration, resource exhaustion, and emerging threat patterns.
What AI and Agentic Threats Do We Detect
Agent goal hijacking
Attacks that manipulate an agent's objectives or decision logic through malicious inputs including indirect prompt injection via documents, emails, or retrieved data.
Tool misuse & Exploitation
Agents misusing legitimate tools due to prompt injection, misalignment, or unsafe delegation that leads to unauthorized actions or data exfiltration.
Identity misuse & Exploitation
Exploitation of inherited credentials, cached tokens, or delegated permissions that allow attackers to escalate privileges or move laterally.
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Supply chain compromise
Compromised tools, plugins, MCP servers, or model components that alter agent behavior or expose sensitive data.
Resource exhaustion
Denial-of-service patterns including excessive API calls, infinite loops, and compute abuse that drain system resources.
Built for Real-World Deployment
While others are still benchmarking model vulnerabilities and risk, Straiker's AI detection engine identifies and flags threats in real-time wherever they occur in your application stack.
Deployment flexibility
Deploy via AI Gateway, API/SDK, eBPF sensors, or lightweight proxy. Straiker integrates at the layer that makes sense for your architecture. There’s no rip-and-replace required.
Protection at every layer
From fine-tuned models for data leak and safety detection, to behavioral context analysis, to purpose-built agentic threat detection. Straiker covers the full attack surface.
Enterprise-proven
Built by the team protecting enterprise AI agent and LLM-based application deployments in production.
Join the Frontlines of Agentic Security
