CAI is a Python framework for building and running AI agents that perform security operations, positioned primarily for offensive/red-team work (pentesting, CTFs, bug bounty). It belongs to the "AI-for-security" subsegment — agents that do security work — which is distinct from the "security-for-AI" guardrail tools (e.g., input/output firewalls that protect LLM apps); buyers should not treat CAI as a defensive guardrail. Vendor claims: support for 300+ models (OpenAI, Anthropic, DeepSeek, Ollama/local), multi-agent coordination with handoff mechanisms, built-in prompt-injection guardrails, human-in-the-loop intervention (Ctrl+C), and real-time tracing via OpenTelemetry/Phoenix; the vendor cites CTF and bug-bounty results as evidence of capability (treat competition results as vendor-reported). Licensing caveat (buyer-critical): despite the public repo, the core code carries a non-commercial Research-Use License — commercial, professional, or production use is prohibited without a separate paid commercial license from Alias Robotics; only the vendored agents subdirectory is MIT. Teams intending production/commercial pentest use must license accordingly. Telemetry caveat: the framework collects usage data (stated for research/model-training) by default; disable with CAI_TELEMETRY=false. Best fit for security researchers and red-teamers evaluating LLM-driven offensive automation who can honor the research-use terms or buy the commercial license.
CAI (Cybersecurity AI)
AI agent framework for offensive security and penetration testing
Alias Robotics' agent framework for building AI-driven offensive-security workflows — reconnaissance, exploitation, privilege escalation, and lateral movement — with multi-agent handoffs and human-in-the-loop control. Source-available, but the core is licensed for non-commercial research use only.
Pricing
Community Edition free (open-repo, pip install) for non-commercial research/academic use. Professional Edition €350/month (unlimited "alias1" tokens, priority support). Commercial/production use of the core requires a separate commercial license (contact Alias Robotics).
Platforms
Python; Linux, macOS, Windows (WSL), and Android. Model-agnostic (300+ LLMs, incl. local via Ollama). CLI-driven with HITL.
Categories
Tags
Alternatives
Shannon
Autonomous AI pentester for web apps and APIs
Shannon is an autonomous white-box AI pentesting tool for web applications and APIs. It analyzes authorized source code, identifies attack vectors, attempts proof-by-exploitation, and produces remediation-ready reports. Shannon Lite is AGPL-3.0 for local use, while Shannon Pro is the commercial Keygraph platform for continuous security testing.
FuzzyAI
CyberArk's open-source LLM fuzzing framework for AI security testing
FuzzyAI is CyberArk's Apache-2.0 framework for fuzzing LLM APIs to identify jailbreaks and related security vulnerabilities. Current README examples cover Ollama/local models, OpenAI, Anthropic, custom REST endpoints, and attacks such as ManyShot, Taxonomy, and ArtPrompt. Use it as a repeatable security-testing starting point, not a complete AI risk-management system.
Agentic Security
LLM vulnerability scanner and red teaming kit
Agentic Security is an open-source vulnerability scanner for LLM agent workflows that tests AI systems against jailbreaks, fuzzing, and multimodal attacks. It probes weaknesses across text, image, and audio inputs through multi-step jailbreak simulations, randomized stress testing, and reinforcement learning-powered adaptive attacks. The toolkit connects directly to LLM APIs for high-volume real-world attack scenarios, helping developers identify and patch safety gaps before deployment.
Related Tools
Anamorpher
Craft image-scaling prompt-injection payloads to red-team multimodal AI systems
Open-source red-team toolkit from Trail of Bits that generates image-scaling attack payloads â images that look benign at full resolution but reveal a hidden prompt injection once a multimodal model downscales them during preprocessing.
MEDUSA
AI-first security scanner for LLM, agent, MCP, and RAG codebases
MEDUSA is an AGPL-3.0 AI-first security scanner from Pantheon Security that checks AI and machine-learning applications, LLM agents, MCP workflows, RAG pipelines, repository-poisoning risks, secrets, and agent-specific compromise patterns.
iFixAi
Open-source diagnostic for AI operational misalignment
iFixAi is an Apache-2.0 diagnostic tool for scoring AI agents and models against operational-misalignment risks such as hallucination, manipulation, sabotage, sandbagging, and oversight evasion.
Inspect AI
UK AI Security Institute framework for LLM safety evaluations
Inspect AI is an MIT-licensed framework from the UK AI Security Institute for running large language model evaluations, including tool use, multi-turn dialogue, model-graded scoring, and reusable evaluation tasks.
Presidio
Open-source PII detection and anonymization for AI data flows
Presidio is an MIT-licensed privacy framework for identifying and anonymizing personally identifiable information in text, images, and structured data. It can act as a de-identification layer around LLM prompts, logs, RAG corpora, and customer-data workflows.
Agent Governance Toolkit
Microsoft’s public-preview runtime governance toolkit for policy, identity, sandboxing, audit, and MCP security around AI agents.
Agent Governance Toolkit is Microsoft’s MIT-licensed public-preview toolkit for governing AI agent runtimes. It adds policy enforcement, zero-trust identity, execution sandboxing, audit, reliability, and MCP security-gateway patterns around tool calls and autonomous actions, helping platform teams move beyond prompt-only guardrails while preserving architecture review requirements.