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Runs autonomous AI agents in isolated containers with declarative YAML policies that enforce filesystem, network, process, and inference controls. Provides credential providers, inference routing, hot-reloadable network/policy updates, and formal verification of policy changes for auditable agent execution.
Primes Claude with drop-in SKILL.md files that encode concise offensive-security methodology across 78 skills in 23 categories, enabling Claude to act as a context-aware red team operator. Intended for authorized red team engagements, bug-bounty triage, security research and CTF practice.
Provides a sanitized, labeled SOC capture and merged provenance graph for intrusion-detection research, including 2,011,674 live signals, 51,371 incident graphs, MITRE ATT&CK mappings, and deterministic attack reports.
Audits deployed AI agents for governance and operational misalignment, running up to 60 inspections that detect deception, manipulation, fabrication, unpredictability and opacity; outputs JSON/Markdown scorecards, a graded A–F score, and optional Pro reports and dashboards.
A 16 GB, 507-file PhD‑level cybersecurity knowledge base for training and evaluating security-focused LLMs and automation. Covers offensive/defensive/forensics/cloud/iot and AI-security across 30+ domains with real-world labs and framework mappings.
Turns a coding agent into a multi-phase security auditor that orchestrates isolated sub-agents for reconnaissance, coverage-led hunting, adversarial validation, structured JSON findings, and independent verification. Requires Node.js and a sandboxed runtime.
Separates host-layer policy from model behavior in DeepSeek Harness by installing reversible local patches and editable prompt-injects for red-team evaluation of LLM hosts. Includes a Clean/Drill side dock, rule sets, skill import, and Apply/Restore controls for official web and desktop hosts.
Autonomous multimodal GUI agent that executes natural-language interface tasks across mobile apps, web domains, and desktop OS. Expands environment coverage (170+ multilingual apps, 4,000+ web domains), uses function-grounded task generation and keypoint-based multi-model verification to produce reliable RL rewards for real-world deployment.
Drop-in abliterated (refusal-removed) build of GLM-5.3-Flash that bakes refusal-direction removal into block-FP8 safetensors, yielding an uncensored 320B (18B active) multimodal MoE model with a 1M-token context. Intended for red-teaming, interpretability, and robustness research; MIT license; not for production without added guardrails.
Provides a cybersecurity-focused CRACK variant of GLM-5.3 FP8 that reduces refusals for offensive-security, red-team, exploit-development and malware-analysis queries while retaining native FP8 speed on Hopper GPUs; MIT-licensed for authorized security work.
Provides 997 chain-of-thought cybersecurity reasoning records distilled from the Kimi K3 model, each with an explicit <think> trace and a technical resolution or structured tool invocation. Includes verified tool-call objects, diffs, cross-domain coverage, and token-level metadata for fine-tuning and evaluating reasoning models.
Provides 23,625 semi-structured smart-contract audit findings (title, description, PoC, recommendation, normalized severity) for defensive-security research; requires cleaning, deduplication, and PoC filtering before model training.