Chakra · Attack it safely
Attack it safely.
Probe AI agents for adversarial paths, unsafe tool use and trust-boundary failures before release.
Probe AI agents for adversarial paths, unsafe tool use and trust-boundary failures before release.
Illustrative Chakra evidence
Input
AI model/application + threat surface
Evidence
Attack transcript + control result
Output
Security finding
What it checks
Concrete checks, not a black-box score.
Prompt injection
Unsafe actions and model exploitation
Privilege and permission boundaries
Policy and guardrail behaviour
Data and trust-boundary exposure
Adversarial recovery paths
What you get
An artefact your engineering team can act on.
- Reproducible attack evidence
- Control-level findings
- Business-impact context
- Security signals connected to release decisions
FAQ
Questions about Chakra.
Does Chakra replace a security programme?
No. It is a technical AI-agent security testing capability within a broader security programme.
What systems can it target?
Machine-learning models, generative AI applications, RAG and retrieval pipelines, multimodal systems, AI agents and tool-using workflows where adversarial behaviour can affect outputs, data or execution.
How are findings used?
Findings are connected to evidence and remediation priorities rather than treated as an isolated score.