Software and data · 22 links
Things you can run or download
Repositories and datasets only. Language and licence are as shown on the repository page when I last checked it.
Neither star counts nor last-commit dates are recorded here. Both go stale within days, neither can be updated in bulk once it is written into prose, and a directory printing a stale number is worse than one telling you to go and look. Where a project was visibly dormant when I checked, the annotation says so.
The index
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Tools (17)
Open-source software with a public repository.
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Crosswalk from deception-based detections to ATT&CK techniques across Windows, Linux and macOS, with a worked deception story for each. MIT. Dormant for years, and nothing has replaced the mapping.
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LLM-powered web honeypot: generates a plausible HTTP response to whatever arrives instead of emulating fixed applications. Go, Apache-2.0.
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Reading list built around the lethal trifecta framing: MCP CVEs, defensive tooling, documented incidents. A fork with almost no history, so treat the selection as one person's.
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Low-code deception runtime, Go, GPL-3.0. The interesting part is the MCP bait tooling: decoys aimed at AI agents rather than human intruders. A commercial product sits on top.
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The environment behind the multinational CAGE Challenges for autonomous cyber defence agents. MIT. Challenge 4 adds multi-agent RL.
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Hosted honeytoken generator, free: files, URLs, credentials, cloud keys that alert when touched.
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The default SSH and Telnet honeypot. Emulated shell, a proxy mode fronting a real host, an experimental LLM backend. Python, actively developed.
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Abstract simulated network for agents moving laterally, built for reinforcement learning rather than realism. MIT. The abstraction is deliberate and it does limit transfer.
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The Engage matrix as machine-readable data, plus the site tooling. Apache-2.0.
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ICS/SCADA honeypot emulating industrial protocol stacks. Python, GPL-2.0. The usual starting point for OT deception.
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NVIDIA's LLM vulnerability scanner. Prompt injection, jailbreaks, training-data leakage, glitch tokens. Apache-2.0.
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The long-running index of honeypot software by protocol and environment, with a section on anti-honeypot detection tools. Breadth over curation.
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The Mantis decoys as running code: tarpitted FTP, deliberately vulnerable web apps, weak telnet, injection payloads, reverse-shell listeners.
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Around thirty honeypot daemons bundled with Elasticsearch, Kibana and Suricata behind one installer. GPL-3.0.
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Multi-protocol honeypot daemon light enough for a Raspberry Pi. BSD-3-Clause. The open counterpart to Thinkst's commercial Canary.
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Threat-Actors-use-of-Artificial-Intelligence
Documented threat-actor AI use mapped to ATT&CK, from Microsoft, OpenAI, Anthropic, GTIG and Kaspersky reporting. Narrower than it looks: attacks on AI systems and influence operations are excluded by design.
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The UK AI Security Institute's evaluation framework. CVE-Bench and several other cyber evals are written against it. MIT.
Datasets and benchmarks (5)
Data and evaluation suites with a canonical landing page.
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A 4-Month Dataset of SSH Botnet Interactions and Command Payloads
145,425 events from an SSH honeypot over four months. Command payloads, credential patterns, attack sequences. CC BY 4.0.
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AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
Ninety-seven realistic agent tasks paired with 629 security test cases, built so attacks and defences can be swapped independently — which is what makes it reusable rather than a one-off result. The standard reference environment for agent hijacking work.
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CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities
Sandboxed reproductions of critical-severity web CVEs with automated success checks. State-of-the-art agent frameworks resolved up to 13%. That figure is the most defensible number currently available for end-to-end autonomous exploitation, and it is a long way below what the threat reporting implies.
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Task descriptions across six CTF categories, run instructions, evaluation logs, a frontier-model leaderboard. Start here rather than the paper if you mean to run it.
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Cowrie captures from ~50 nodes at EU and US universities and companies, May 2019 to February 2020.
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