Synack: AI Agents and How They Are Used in Pentesting Effectively
Category:Research & Analysis
Synack breaks down agentic AI in pentesting, contrasting it with standard LLMs. What's interesting: agents can autonomously chain tools (nmap→hashcat→curl), learn from results, and adapt—going beyond just answering questions to forming hypotheses and executing multi-step plans. They deploy multi-agent architectures where specialized agents handle recon, scanning, and exploitation in parallel (horizontal topology) or in hierarchical workflows (vertical topology). The catch: agents hallucinate vulnerabilities constantly and miss business logic flaws that require human judgment. Synack's model keeps humans in the loop for high/critical issue validation.
CORTEX Protocol Intelligence Assessment
This represents the maturation of AI-assisted offensive security—moving from advisory tools to autonomous operators. The key tension is speed vs accuracy: agents excel at breadth and repetitive tasks but struggle with context-dependent vulnerabilities that require business understanding.
Strategic Intelligence Guidance
- Focus agentic AI on high-volume, repeatable tasks: asset discovery, parameter fuzzing, CVE correlation across large attack surfaces.
- Build governance around agent actions: sandbox execution environments, require human validation for privilege escalation and data exfiltration findings.
- Accept that agents will generate false positives—invest in human expertise to filter hallucinated vulnerabilities and validate exploitability.
- Watch for adversarial use: the same agents defenders deploy can accelerate attacker reconnaissance and vulnerability chaining.
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Intelligence Source: AI Agents and How They Are Used in Pentesting Effectively | Oct 31, 2025